From cd4766394c10b7bd04ecff4365b60b1ce0e4abcb Mon Sep 17 00:00:00 2001 From: Andre Date: Thu, 1 Dec 2022 17:28:49 +0800 Subject: [PATCH 001/189] Remove SE from being combined during extendAnno --- R/bambu-extendAnnotations-utilityCombine.R | 17 +++++++++-------- 1 file changed, 9 insertions(+), 8 deletions(-) diff --git a/R/bambu-extendAnnotations-utilityCombine.R b/R/bambu-extendAnnotations-utilityCombine.R index 7f1a521a..cdf0c5ef 100644 --- a/R/bambu-extendAnnotations-utilityCombine.R +++ b/R/bambu-extendAnnotations-utilityCombine.R @@ -19,14 +19,15 @@ isore.combineTranscriptCandidates <- function(readClassList, min.readCount, min.readFractionByGene, min.txScore.multiExon, min.txScore.singleExon, verbose) %>% data.table() combinedSplicedTranscripts[,confidenceType := "highConfidenceJunctionReads"] - combinedUnsplicedTranscripts <- - combineUnsplicedTranscriptModels(readClassList, bpParameters, - stranded, min.readCount, min.readFractionByGene, - min.txScore.multiExon, min.txScore.singleExon, verbose) %>% data.table() - combinedUnsplicedTranscripts[, confidenceType := "unsplicedNew"] - combinedTranscripts <- as_tibble(rbindlist(list(combinedSplicedTranscripts, - combinedUnsplicedTranscripts), fill = TRUE)) - return(combinedTranscripts) + return(combinedSplicedTranscripts) + # combinedUnsplicedTranscripts <- + # combineUnsplicedTranscriptModels(readClassList, bpParameters, + # stranded, min.readCount, min.readFractionByGene, + # min.txScore.multiExon, min.txScore.singleExon, verbose) %>% data.table() + # combinedUnsplicedTranscripts[, confidenceType := "unsplicedNew"] + # combinedTranscripts <- as_tibble(rbindlist(list(combinedSplicedTranscripts, + # combinedUnsplicedTranscripts), fill = TRUE)) + # return(combinedTranscripts) } From cbec873835e600e4d83e23860f9454ef6c0bafd1 Mon Sep 17 00:00:00 2001 From: Andre Date: Fri, 14 Apr 2023 16:11:39 +0800 Subject: [PATCH 002/189] Copy over rowdata from equal read classes above NDR threshold --- R/bambu-extendAnnotations-utilityExtend.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/R/bambu-extendAnnotations-utilityExtend.R b/R/bambu-extendAnnotations-utilityExtend.R index 01310fa9..beb2893f 100644 --- a/R/bambu-extendAnnotations-utilityExtend.R +++ b/R/bambu-extendAnnotations-utilityExtend.R @@ -95,7 +95,7 @@ filterTranscriptsByAnnotation <- function(rowDataCombined, annotationGrangesList } else { if(is.null(NDR)) NDR = 0.5 } - filterSet = (rowDataCombined$NDR <= NDR) + filterSet = (rowDataCombined$NDR <= NDR | rowDataCombined$readClassType == "equal:compatible") exonRangesCombined <- exonRangesCombined[filterSet] rowDataCombined <- rowDataCombined[filterSet,] #calculate relative subset read count after filtering (increase speed, subsets are not considered here) From c7306eda7cbad3a8c8ba538d618b75af2a6eaf6e Mon Sep 17 00:00:00 2001 From: Andre Date: Fri, 14 Apr 2023 17:37:22 +0800 Subject: [PATCH 003/189] Add lowConfidenceTranscripts to metadata and speed up relSubsetCount --- R/bambu-extendAnnotations-utilityExtend.R | 73 +++++++++++++++-------- 1 file changed, 49 insertions(+), 24 deletions(-) diff --git a/R/bambu-extendAnnotations-utilityExtend.R b/R/bambu-extendAnnotations-utilityExtend.R index beb2893f..902c34a0 100644 --- a/R/bambu-extendAnnotations-utilityExtend.R +++ b/R/bambu-extendAnnotations-utilityExtend.R @@ -80,42 +80,52 @@ filterTranscriptsByAnnotation <- function(rowDataCombined, annotationGrangesList #calculate relative read count before any filtering rowDataCombined <- group_by(rowDataCombined, GENEID) %>% mutate(relReadCount = readCount/sum(readCount)) + + #filter out subset reads if (remove.subsetTx) { # (1) based on compatibility with annotations - notCompatibleIds <- which(!grepl("compatible", rowDataCombined$readClassType) | + notCompatibleIds <- (!grepl("compatible", rowDataCombined$readClassType) | rowDataCombined$readClassType == "equal:compatible") #keep equal for FDR calculation + # subsetTranscripts <- combindRowDataWithRanges( + # rowDataCombined[!notCompatibleIds,], + # exonRangesCombined[!notCompatibleIds]) exonRangesCombined <- exonRangesCombined[notCompatibleIds] rowDataCombined <- rowDataCombined[notCompatibleIds,] } #(2) remove transcripts below NDR threshold/identical junctions to annotations rowDataCombined = calculateNDROnTranscripts(rowDataCombined, useTxScore = length(annotationGrangesList)==0) - if(length(annotationGrangesList)>0){ #only recommend an NDR if its possible to calculate an NDR NDR = recommendNDR(rowDataCombined, baselineFDR, NDR, defaultModels, verbose) } else { if(is.null(NDR)) NDR = 0.5 } filterSet = (rowDataCombined$NDR <= NDR | rowDataCombined$readClassType == "equal:compatible") + lowConfidenceTranscripts <- combindRowDataWithRanges( + rowDataCombined[!filterSet,], + exonRangesCombined[!filterSet]) exonRangesCombined <- exonRangesCombined[filterSet] rowDataCombined <- rowDataCombined[filterSet,] - #calculate relative subset read count after filtering (increase speed, subsets are not considered here) + mcols(exonRangesCombined)$txid <- seq_along(exonRangesCombined) - minEq <- getMinimumEqClassByTx(exonRangesCombined)$eqClassById - rowDataCombined$relSubsetCount <- rowDataCombined$readCount/unlist(lapply(minEq, function(x){return(sum(rowDataCombined$readCount[x]))})) - #post extend annotation filters applied here (currently only subset filter) - if(min.readFractionByEqClass>0 & sum(filterSet)>0) { # filter out subset transcripts based on relative expression - filterSet <- rowDataCombined$relSubsetCount > min.readFractionByEqClass - exonRangesCombined <- exonRangesCombined[filterSet] - rowDataCombined <- rowDataCombined[filterSet,] - } + if(sum(filterSet==0) & length(annotationGrangesList)==0) stop( "WARNING - No annotations were provided. Please increase NDR threshold to use novel transcripts") if(sum(filterSet)==0) message("WARNING - No novel transcripts meet the given thresholds. Try a higher NDR.") # (3) combine novel transcripts with annotations + extendedAnnotationRanges <- combindRowDataWithRanges(rowDataCombined, exonRangesCombined) extendedAnnotationRanges <- combineWithAnnotations( - rowDataCombined, exonRangesCombined, + rowDataCombined, extendedAnnotationRanges, annotationGrangesList, prefix) + minEqClasses <- + getMinimumEqClassByTx(extendedAnnotationRanges) # get eqClasses + if(!identical(names(extendedAnnotationRanges),minEqClasses$queryTxId)) warning('eq classes might be incorrect') + mcols(extendedAnnotationRanges)$eqClassById <- minEqClasses$eqClassById + extendedAnnotationRanges <- calculateRelSubsetCount(extendedAnnotationRanges, minEqClasses$eqClassById, min.readFractionByEqClass) + mcols(extendedAnnotationRanges) <- mcols(extendedAnnotationRanges)[, + c("TXNAME", "GENEID", "NDR", "novelGene", "novelTranscript", "txClassDescription","readCount","relReadCount", "relSubsetCount", "txid", "eqClassById")] metadata(extendedAnnotationRanges)$NDRthreshold = NDR + #if (remove.subsetTx) metadata(extendedAnnotationRanges)$subsetTranscripts = subsetTranscripts + metadata(extendedAnnotationRanges)$lowConfidenceTranscripts = lowConfidenceTranscripts end.ptm <- proc.time() if (verbose) message("transcript filtering in ", round((end.ptm - start.ptm)[3] / 60, 1), " mins.") @@ -612,10 +622,9 @@ includeOverlapReadClass <- function(candidateList, filteredOverlapList) { return(temp) } -#' combine annotations with predicted transcripts +#' extract the important row range columns and add them to the ranges for final output #' @noRd -combineWithAnnotations <- function(rowDataCombinedFiltered, - exonRangesCombinedFiltered,annotationGrangesList, prefix){ +combindRowDataWithRanges <- function(rowDataCombinedFiltered, exonRangesCombinedFiltered){ rowDataCombinedFiltered$txClassDescription <- rowDataCombinedFiltered$readClassType rowDataCombinedFiltered$txClassDescription[rowDataCombinedFiltered$readClassType == "unsplicedNew" & rowDataCombinedFiltered$novelGene] <- @@ -626,7 +635,14 @@ combineWithAnnotations <- function(rowDataCombinedFiltered, extendedAnnotationRanges <- exonRangesCombinedFiltered mcols(extendedAnnotationRanges) <- rowDataCombinedFiltered[, c("GENEID", "novelGene", "novelTranscript", "txClassDescription","readCount", "NDR", - "relReadCount", "relSubsetCount")] + "relReadCount")] + return(extendedAnnotationRanges) +} + +#' combine annotations with predicted transcripts +#' @noRd +combineWithAnnotations <- function(rowDataCombinedFiltered, + extendedAnnotationRanges,annotationGrangesList, prefix){ equalRanges = rowDataCombinedFiltered[!is.na(rowDataCombinedFiltered$TXNAME),] #remove extended ranges that are already present in annotation extendedAnnotationRanges <- extendedAnnotationRanges[is.na(rowDataCombinedFiltered$TXNAME)] @@ -642,7 +658,7 @@ combineWithAnnotations <- function(rowDataCombinedFiltered, mcols(annotationRangesToMerge[equalRanges$TXNAME])$NDR = equalRanges$NDR mcols(annotationRangesToMerge[equalRanges$TXNAME])$readCount = equalRanges$readCount mcols(annotationRangesToMerge[equalRanges$TXNAME])$relReadCount = equalRanges$relReadCount - mcols(annotationRangesToMerge[equalRanges$TXNAME])$relSubsetCount = equalRanges$relSubsetCount + #mcols(annotationRangesToMerge[equalRanges$TXNAME])$relSubsetCount = equalRanges$relSubsetCount } if (length(extendedAnnotationRanges)) { mcols(extendedAnnotationRanges)$TXNAME <- paste0( @@ -655,17 +671,26 @@ combineWithAnnotations <- function(rowDataCombinedFiltered, extendedAnnotationRanges <- annotationRangesToMerge mcols(extendedAnnotationRanges)$txid <- seq_along(extendedAnnotationRanges) mcols(extendedAnnotationRanges)$relReadCount = NA - mcols(extendedAnnotationRanges)$relSubsetCount = NA + #mcols(extendedAnnotationRanges)$relSubsetCount = NA } - minEqClasses <- - getMinimumEqClassByTx(extendedAnnotationRanges) # get eqClasses - if(!identical(names(extendedAnnotationRanges),minEqClasses$queryTxId)) warning('eq classes might be incorrect') - mcols(extendedAnnotationRanges)$eqClassById <- minEqClasses$eqClassById - mcols(extendedAnnotationRanges) <- mcols(extendedAnnotationRanges)[, - c("TXNAME", "GENEID", "NDR", "novelGene", "novelTranscript", "txClassDescription","readCount","relReadCount", "relSubsetCount", "txid", "eqClassById")] return(extendedAnnotationRanges) } +#' calculate relative subset read count after filtering (increase speed, subsets are not considered here)' +#' @noRd +calculateRelSubsetCount = function(extendedAnnotationRanges, minEq, min.readFractionByEqClass){ + filter = !is.na(mcols(extendedAnnotationRanges)$readCount) + mcols(extendedAnnotationRanges)$relSubsetCount <- NA + mcols(extendedAnnotationRanges)$relSubsetCount[filter] <- + mcols(extendedAnnotationRanges)$readCount[filter]/ + unlist(lapply(minEq[filter], function(x){return(sum(mcols(extendedAnnotationRanges)$readCount[x], na.rm = TRUE))})) + #post extend annotation filters applied here (currently only subset filter) + if(min.readFractionByEqClass>0) { # filter out subset transcripts based on relative expression + filterSet <- is.na(mcols(extendedAnnotationRanges)$relSubsetCount) | mcols(extendedAnnotationRanges)$relSubsetCount > min.readFractionByEqClass + extendedAnnotationRanges <- extendedAnnotationRanges[filterSet] + } + return(extendedAnnotationRanges) +} #' Estimate distance between read class and annotations #' @param seReadClass seReadClass From 44f76aba0f2889568564e7c18254006983767cfb Mon Sep 17 00:00:00 2001 From: Andre Date: Fri, 14 Apr 2023 17:44:59 +0800 Subject: [PATCH 004/189] subset transcripts are added to metadata --- R/bambu-extendAnnotations-utilityExtend.R | 14 ++++++++++---- 1 file changed, 10 insertions(+), 4 deletions(-) diff --git a/R/bambu-extendAnnotations-utilityExtend.R b/R/bambu-extendAnnotations-utilityExtend.R index 902c34a0..ee9b45e1 100644 --- a/R/bambu-extendAnnotations-utilityExtend.R +++ b/R/bambu-extendAnnotations-utilityExtend.R @@ -85,9 +85,9 @@ filterTranscriptsByAnnotation <- function(rowDataCombined, annotationGrangesList if (remove.subsetTx) { # (1) based on compatibility with annotations notCompatibleIds <- (!grepl("compatible", rowDataCombined$readClassType) | rowDataCombined$readClassType == "equal:compatible") #keep equal for FDR calculation - # subsetTranscripts <- combindRowDataWithRanges( - # rowDataCombined[!notCompatibleIds,], - # exonRangesCombined[!notCompatibleIds]) + subsetTranscripts <- combindRowDataWithRanges( + rowDataCombined[!notCompatibleIds,], + exonRangesCombined[!notCompatibleIds]) exonRangesCombined <- exonRangesCombined[notCompatibleIds] rowDataCombined <- rowDataCombined[notCompatibleIds,] } @@ -124,7 +124,7 @@ filterTranscriptsByAnnotation <- function(rowDataCombined, annotationGrangesList mcols(extendedAnnotationRanges) <- mcols(extendedAnnotationRanges)[, c("TXNAME", "GENEID", "NDR", "novelGene", "novelTranscript", "txClassDescription","readCount","relReadCount", "relSubsetCount", "txid", "eqClassById")] metadata(extendedAnnotationRanges)$NDRthreshold = NDR - #if (remove.subsetTx) metadata(extendedAnnotationRanges)$subsetTranscripts = subsetTranscripts + if (remove.subsetTx) metadata(extendedAnnotationRanges)$subsetTranscripts = subsetTranscripts metadata(extendedAnnotationRanges)$lowConfidenceTranscripts = lowConfidenceTranscripts end.ptm <- proc.time() if (verbose) message("transcript filtering in ", @@ -633,9 +633,15 @@ combindRowDataWithRanges <- function(rowDataCombinedFiltered, exonRangesCombined == "allNew" & rowDataCombinedFiltered$novelGene] <- "newGene-spliced" extendedAnnotationRanges <- exonRangesCombinedFiltered + if("NDR" %in% colnames(rowDataCombinedFiltered)){ mcols(extendedAnnotationRanges) <- rowDataCombinedFiltered[, c("GENEID", "novelGene", "novelTranscript", "txClassDescription","readCount", "NDR", "relReadCount")] + } else{ + mcols(extendedAnnotationRanges) <- + rowDataCombinedFiltered[, c("GENEID", "novelGene", "novelTranscript", "txClassDescription","readCount", + "relReadCount")] + } return(extendedAnnotationRanges) } From 7e32425520abeadce806606e8ee7ff24eb7bf356 Mon Sep 17 00:00:00 2001 From: Andre Date: Fri, 14 Apr 2023 18:01:55 +0800 Subject: [PATCH 005/189] Add helper function to set NDR on extendedAnnotations --- NAMESPACE | 1 + R/transcriptToGeneExpression.R | 12 ++++++------ 2 files changed, 7 insertions(+), 6 deletions(-) diff --git a/NAMESPACE b/NAMESPACE index b4c51d05..c360bde7 100755 --- a/NAMESPACE +++ b/NAMESPACE @@ -8,6 +8,7 @@ export(transcriptToGeneExpression) export(writeBambuOutput) export(writeToGTF) export(trainBambu) +export(setNDR) export(compareTranscripts) importFrom(stats,predict) importFrom(BiocGenerics,basename) diff --git a/R/transcriptToGeneExpression.R b/R/transcriptToGeneExpression.R index 9cf7604b..e91efca5 100644 --- a/R/transcriptToGeneExpression.R +++ b/R/transcriptToGeneExpression.R @@ -20,12 +20,12 @@ transcriptToGeneExpression <- function(se) { rowDataSe <- as.data.table(rowData(se)) counts <- rowDataSe[, .(TXNAME, GENEID)][counts, on = "TXNAME"] - incompatibleCounts <- metadata(se)$incompatibleCounts - incompatibleCounts[, TXNAME := "incompatible"] - counts_incompatible <- melt(incompatibleCounts, id.vars = c("GENEID","TXNAME"), - measure.vars = setdiff(colnames(incompatibleCounts), c("GENEID","TXNAME"))) - # GENEID, TXNAME, variable, value - counts <- rbind(counts, counts_incompatible[variable %in% unique(counts$variable)]) + # incompatibleCounts <- metadata(se)$incompatibleCounts + # incompatibleCounts[, TXNAME := "incompatible"] + # counts_incompatible <- melt(incompatibleCounts, id.vars = c("GENEID","TXNAME"), + # measure.vars = setdiff(colnames(incompatibleCounts), c("GENEID","TXNAME"))) + # # GENEID, TXNAME, variable, value + # counts <- rbind(counts, counts_incompatible[variable %in% unique(counts$variable)]) counts[, valueGene := sum(value), by = list(variable, GENEID)] counts[, valueGeneCPM := valueGene / max(sum(value), 1) * 10^6, by = list(variable)] From f5d4f173a3bcb5c75a04fcec49ab7565e8dcd5d9 Mon Sep 17 00:00:00 2001 From: Andre Date: Mon, 17 Apr 2023 09:26:57 +0800 Subject: [PATCH 006/189] function to set NDR threshold on extendedAnno --- R/bambu-extendAnnotations-utilityExtend.R | 22 ++++++++++++++++++++++ 1 file changed, 22 insertions(+) diff --git a/R/bambu-extendAnnotations-utilityExtend.R b/R/bambu-extendAnnotations-utilityExtend.R index ee9b45e1..54d7e9e4 100644 --- a/R/bambu-extendAnnotations-utilityExtend.R +++ b/R/bambu-extendAnnotations-utilityExtend.R @@ -778,3 +778,25 @@ addGeneIdsToReadClassTable <- function(readClassTable, distTable, round((end.ptm - start.ptm)[3] / 60, 1), " mins.") return(readClassTable) } + +#' Function to change NDR threshold on extendedAnnotations +#' @title Function to change NDR threshold on extendedAnnotations +#' @description This function train a model for use on other data +#' @param extendedAnnotations A GRangesList object produced from bambu(quant = FALSE) or rowRanges(se) +#' @param NDR The maximum NDR for novel transcripts to be in extendedAnnotations (0-1) +#' Output - returns a similiar GRangesList object with entries swapped into or out of metadata(extendedAnnotations)$lowConfidenceTranscripts +#' @details +#' @return extendedAnnotations with a new NDR threshold +#' @export +setNDR = function(extendedAnnotations, NDR){ + toRemove = (mcols(extendedAnnotations)$NDR > NDR & mcols(extendedAnnotations)$txClassDescription != "annotation") + toAdd = mcols(metadata(extendedAnnotations)$lowConfidenceTranscripts)$NDR <= NDR + + temp = c(metadata(extendedAnnotations)$lowConfidenceTranscripts[!toAdd], extendedAnnotations[toRemove]) + extendedAnnotations = c(extendedAnnotations[!toRemove], metadata(extendedAnnotations)$lowConfidenceTranscripts[toAdd]) + metadata(extendedAnnotations)$lowConfidenceTranscripts = temp + + metadata(extendedAnnotations)$NDR = NDR + + return(extendedAnnotations) +} \ No newline at end of file From ba7c084c25725a99729b1b6e88849e11f8bcc034 Mon Sep 17 00:00:00 2001 From: Andre Date: Fri, 14 Apr 2023 18:01:55 +0800 Subject: [PATCH 007/189] Revert "Add helper function to set NDR on extendedAnnotations" This reverts commit 9b865dfa334e22774a9e51fd829afd23b7e27181. --- NAMESPACE | 1 - R/transcriptToGeneExpression.R | 12 ++++++------ 2 files changed, 6 insertions(+), 7 deletions(-) diff --git a/NAMESPACE b/NAMESPACE index c360bde7..b4c51d05 100755 --- a/NAMESPACE +++ b/NAMESPACE @@ -8,7 +8,6 @@ export(transcriptToGeneExpression) export(writeBambuOutput) export(writeToGTF) export(trainBambu) -export(setNDR) export(compareTranscripts) importFrom(stats,predict) importFrom(BiocGenerics,basename) diff --git a/R/transcriptToGeneExpression.R b/R/transcriptToGeneExpression.R index e91efca5..9cf7604b 100644 --- a/R/transcriptToGeneExpression.R +++ b/R/transcriptToGeneExpression.R @@ -20,12 +20,12 @@ transcriptToGeneExpression <- function(se) { rowDataSe <- as.data.table(rowData(se)) counts <- rowDataSe[, .(TXNAME, GENEID)][counts, on = "TXNAME"] - # incompatibleCounts <- metadata(se)$incompatibleCounts - # incompatibleCounts[, TXNAME := "incompatible"] - # counts_incompatible <- melt(incompatibleCounts, id.vars = c("GENEID","TXNAME"), - # measure.vars = setdiff(colnames(incompatibleCounts), c("GENEID","TXNAME"))) - # # GENEID, TXNAME, variable, value - # counts <- rbind(counts, counts_incompatible[variable %in% unique(counts$variable)]) + incompatibleCounts <- metadata(se)$incompatibleCounts + incompatibleCounts[, TXNAME := "incompatible"] + counts_incompatible <- melt(incompatibleCounts, id.vars = c("GENEID","TXNAME"), + measure.vars = setdiff(colnames(incompatibleCounts), c("GENEID","TXNAME"))) + # GENEID, TXNAME, variable, value + counts <- rbind(counts, counts_incompatible[variable %in% unique(counts$variable)]) counts[, valueGene := sum(value), by = list(variable, GENEID)] counts[, valueGeneCPM := valueGene / max(sum(value), 1) * 10^6, by = list(variable)] From 46d9167df37784dc1d9167f7b82e36feb1581c61 Mon Sep 17 00:00:00 2001 From: Andre Date: Mon, 17 Apr 2023 09:28:06 +0800 Subject: [PATCH 008/189] export setNDR --- NAMESPACE | 1 + 1 file changed, 1 insertion(+) diff --git a/NAMESPACE b/NAMESPACE index b4c51d05..c360bde7 100755 --- a/NAMESPACE +++ b/NAMESPACE @@ -8,6 +8,7 @@ export(transcriptToGeneExpression) export(writeBambuOutput) export(writeToGTF) export(trainBambu) +export(setNDR) export(compareTranscripts) importFrom(stats,predict) importFrom(BiocGenerics,basename) From 82fe064d7902e97b48fd408c359a9f0ed3cd0aa5 Mon Sep 17 00:00:00 2001 From: Andre Date: Tue, 18 Apr 2023 13:51:49 +0800 Subject: [PATCH 009/189] readClass warnings kept only when rcFile is made and not when loaded in --- R/bambu.R | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/R/bambu.R b/R/bambu.R index e61d0bfa..b7fe05d4 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -154,6 +154,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, readClassList = reads isRDSs = all(sapply(reads, class)=="RangedSummarizedExperiment") isBamFiles = !isRDSs + warnings = NULL if(!isRDSs) isBamFiles = ifelse(!is(reads, "BamFileList"), all(grepl(".bam$", reads)), FALSE) if (isBamFiles | is(reads, "BamFileList")) { if (length(reads) > 10 & (is.null(rcOutDir))) { @@ -170,8 +171,8 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, bpParameters, stranded, verbose, isoreParameters, trackReads = trackReads, fusionMode = fusionMode, lowMemory = lowMemory) + warnings = handleWarnings(readClassList, verbose) } - warnings = handleWarnings(readClassList, verbose) if (!discovery & !quant) return(readClassList) if (discovery) { message("--- Start extending annotations ---") From 50677f4027ec4fa7c487dbbb411e4755f4bf6fe0 Mon Sep 17 00:00:00 2001 From: Andre Date: Thu, 20 Apr 2023 09:39:24 +0800 Subject: [PATCH 010/189] set seqlevels of reads to only seqnames in the reads to reduce warnings --- R/prepareDataFromBam.R | 1 + 1 file changed, 1 insertion(+) diff --git a/R/prepareDataFromBam.R b/R/prepareDataFromBam.R index 09cf5ae7..d4f7fa4f 100755 --- a/R/prepareDataFromBam.R +++ b/R/prepareDataFromBam.R @@ -42,6 +42,7 @@ prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE, use.n # remove microexons of width 1bp from list readGrgList <- readGrgList[width(readGrgList) > 1] mcols(readGrgList)$id <- seq_along(readGrgList) + seqlevels(readGrgList)=as.character(unique(getChrFromGrList(readGrgList))) return(readGrgList) } From d17cbf19f63162d823c8fa7f07c24a65a3467a2d Mon Sep 17 00:00:00 2001 From: Andre Date: Wed, 26 Apr 2023 13:54:09 +0800 Subject: [PATCH 011/189] write NDR to gtf --- R/readWrite.R | 11 +++++++++-- 1 file changed, 9 insertions(+), 2 deletions(-) diff --git a/R/readWrite.R b/R/readWrite.R index 44e98de9..d3bce597 100644 --- a/R/readWrite.R +++ b/R/readWrite.R @@ -85,8 +85,13 @@ writeToGTF <- function(annotation, file, geneIDs = NULL) { } else if (!is(annotation, "CompressedGRangesList")) { stop("The inputted GRangesList is of the wrong class.") } + NDR = NULL df <- as_tibble(annotation) df$exon_rank <- paste('exon_number "', df$exon_rank, '";', sep = "") + if(!is.null(mcols(annotation)$NDR)){ + NDR = rep(mcols(annotation)$NDR, unname(elementNROWS(annotation))) + df$NDR <- paste('NDR "', as.character(NDR), '";', sep = "") + } if (missing(geneIDs)) { if (!is.null(mcols(annotation, use.names = FALSE)$GENEID)) { geneIDs <- as_tibble(mcols(annotation, use.names = FALSE)[, @@ -100,7 +105,7 @@ writeToGTF <- function(annotation, file, geneIDs = NULL) { df$group_name <- paste('transcript_id "', df$group_name, '";', sep = "") df$GENEID <- paste('gene_id "', df$GENEID, '";', sep = "") dfExon <- mutate(df, source = "Bambu", feature = "exon", score = ".", - frame = ".", attributes = paste(GENEID, group_name, exon_rank)) %>% + frame = ".", attributes = paste(GENEID, group_name, exon_rank, NDR)) %>% select(seqnames, source, feature, start, end, score, strand, frame, attributes, group_name) dfTx <- as.data.frame(range(ranges(annotation))) @@ -109,9 +114,11 @@ writeToGTF <- function(annotation, file, geneIDs = NULL) { dfTx$group_name <- paste('transcript_id "', dfTx$group_name, '";', sep = "") dfTx$GENEID <- paste('gene_id "', dfTx$GENEID, '";', sep = "") + if(!is.null(mcols(annotation)$NDR)) dfTx$NDR <- + paste('NDR "', mcols(annotation)$NDR, '";', sep = "") dfTx <- mutate(dfTx,source = "Bambu", feature = "transcript", score = ".", - frame = ".", attributes = paste(GENEID, group_name)) %>% + frame = ".", attributes = paste(GENEID, group_name, NDR)) %>% select(seqnames, source, feature, start, end, score, strand, frame, attributes, group_name) From 232c1603500737b5860e7c68c51fdfef1104f514 Mon Sep 17 00:00:00 2001 From: Andre Date: Wed, 26 Apr 2023 14:29:45 +0800 Subject: [PATCH 012/189] Read in NDR if in gtf --- R/prepareAnnotations_utilityFunctions.R | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/R/prepareAnnotations_utilityFunctions.R b/R/prepareAnnotations_utilityFunctions.R index ffa2f48d..0cdfd969 100644 --- a/R/prepareAnnotations_utilityFunctions.R +++ b/R/prepareAnnotations_utilityFunctions.R @@ -27,6 +27,9 @@ prepareAnnotationsFromGTF <- function(file) { data$strand[data$strand == "."] <- "*" data$GENEID <- gsub("gene_id (.*?);.*", "\\1", data$attribute) data$TXNAME <- gsub(".*transcript_id (.*?);.*", "\\1", data$attribute) + data$NDR <- NULL + hasNDR = all(grepl("NDR ", data$attribute)) + if(hasNDR) data$NDR <- gsub(".*NDR (.*?);.*", "\\1", data$attribute) multiTxCheck <- as_tibble(data) %>% select(seqname, GENEID) %>% distinct() %>% group_by(GENEID) %>% mutate(n=n(), id=paste0('-',row_number())) if(any(multiTxCheck$n>1)) { # identical TXNAMES @@ -45,6 +48,8 @@ prepareAnnotationsFromGTF <- function(file) { data$GENEID <- uniqueNamesTbl$gene_unique } geneData <- unique(data[, c("TXNAME", "GENEID")]) + geneData <- if(hasNDR) { unique(data[, c("TXNAME", "GENEID", "NDR")]) + } else {unique(data[, c("TXNAME", "GENEID")])} grlist <- makeGRangesListFromDataFrame( data[, c("seqname", "start", "end", "strand", "TXNAME")], split.field = "TXNAME", keep.extra.columns = TRUE) From 0ae5c371ab57f24a96226859198e20005c43c432 Mon Sep 17 00:00:00 2001 From: Andre Date: Wed, 26 Apr 2023 17:42:51 +0800 Subject: [PATCH 013/189] Allow setNDR to work on gtf files that are read in --- R/bambu-extendAnnotations-utilityExtend.R | 24 ++++++++++++++++++++--- 1 file changed, 21 insertions(+), 3 deletions(-) diff --git a/R/bambu-extendAnnotations-utilityExtend.R b/R/bambu-extendAnnotations-utilityExtend.R index 54d7e9e4..007e0c00 100644 --- a/R/bambu-extendAnnotations-utilityExtend.R +++ b/R/bambu-extendAnnotations-utilityExtend.R @@ -784,13 +784,31 @@ addGeneIdsToReadClassTable <- function(readClassTable, distTable, #' @description This function train a model for use on other data #' @param extendedAnnotations A GRangesList object produced from bambu(quant = FALSE) or rowRanges(se) #' @param NDR The maximum NDR for novel transcripts to be in extendedAnnotations (0-1) +#' @param includeRef A boolean which if TRUE will also filter out reference annotations based on their NDR +#' @param prefix A string which determines which transcripts are considered novel by bambu and will be filtered (by default = 'Bambu') #' Output - returns a similiar GRangesList object with entries swapped into or out of metadata(extendedAnnotations)$lowConfidenceTranscripts #' @details #' @return extendedAnnotations with a new NDR threshold #' @export -setNDR = function(extendedAnnotations, NDR){ - toRemove = (mcols(extendedAnnotations)$NDR > NDR & mcols(extendedAnnotations)$txClassDescription != "annotation") - toAdd = mcols(metadata(extendedAnnotations)$lowConfidenceTranscripts)$NDR <= NDR +setNDR = function(extendedAnnotations, NDR, includeRef = FALSE, prefix = 'Bambu'){ + + if(is.null(mcols(extendedAnnotations)$NDR)){ + warning("Annotations were not extended by Bambu. NDR can not be set") + return(extendedAnnotations) + } + + if(is.null(metadata(extendedAnnotations)$lowConfidenceTranscripts)) + metadata(extendedAnnotations)$lowConfidenceTranscripts = GRangesList() + + if(includeRef){ + toRemove = (mcols(extendedAnnotations)$NDR > NDR) + toAdd = mcols(metadata(extendedAnnotations)$lowConfidenceTranscripts)$NDR <= NDR + } else { + toRemove = (mcols(extendedAnnotations)$NDR > NDR & + grepl(prefix, mcols(extendedAnnotations)$TXNAME)) + toAdd = (mcols(metadata(extendedAnnotations)$lowConfidenceTranscripts)$NDR <= NDR & + grepl(prefix, mcols(extendedAnnotations)$TXNAME)) + } temp = c(metadata(extendedAnnotations)$lowConfidenceTranscripts[!toAdd], extendedAnnotations[toRemove]) extendedAnnotations = c(extendedAnnotations[!toRemove], metadata(extendedAnnotations)$lowConfidenceTranscripts[toAdd]) From 3f464e07a261502383316b5c37988bd8f9febee6 Mon Sep 17 00:00:00 2001 From: Andre Date: Wed, 26 Apr 2023 18:01:28 +0800 Subject: [PATCH 014/189] Allow NDR filtering in NDR quant only mode --- R/bambu.R | 2 ++ 1 file changed, 2 insertions(+) diff --git a/R/bambu.R b/R/bambu.R index b7fe05d4..cb9c71cc 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -183,6 +183,8 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, } if (quant) { message("--- Start isoform quantification ---") + if(!is.null(NDR) & !discovery) + annotations = setNDR(annotations, NDR, prefix = isoreParameters$prefix) if(length(annotations)==0) stop("No valid annotations, if running de novo please try less stringent parameters") countsSe <- bplapply(readClassList, bambu.quantify, From 3043a1d53549059aeb7307b50e95e2940801cdb0 Mon Sep 17 00:00:00 2001 From: Andre Date: Thu, 27 Apr 2023 13:53:26 +0800 Subject: [PATCH 015/189] Add txScore to mcols --- R/bambu-extendAnnotations-utilityExtend.R | 12 +++++++++--- 1 file changed, 9 insertions(+), 3 deletions(-) diff --git a/R/bambu-extendAnnotations-utilityExtend.R b/R/bambu-extendAnnotations-utilityExtend.R index 007e0c00..73828750 100644 --- a/R/bambu-extendAnnotations-utilityExtend.R +++ b/R/bambu-extendAnnotations-utilityExtend.R @@ -122,7 +122,9 @@ filterTranscriptsByAnnotation <- function(rowDataCombined, annotationGrangesList mcols(extendedAnnotationRanges)$eqClassById <- minEqClasses$eqClassById extendedAnnotationRanges <- calculateRelSubsetCount(extendedAnnotationRanges, minEqClasses$eqClassById, min.readFractionByEqClass) mcols(extendedAnnotationRanges) <- mcols(extendedAnnotationRanges)[, - c("TXNAME", "GENEID", "NDR", "novelGene", "novelTranscript", "txClassDescription","readCount","relReadCount", "relSubsetCount", "txid", "eqClassById")] + c("TXNAME", "GENEID", "NDR", "novelGene", "novelTranscript", + "txClassDescription","readCount","relReadCount", + "relSubsetCount", "txid", "eqClassById", "maxTxScore", "maxTxScore.noFit")] metadata(extendedAnnotationRanges)$NDRthreshold = NDR if (remove.subsetTx) metadata(extendedAnnotationRanges)$subsetTranscripts = subsetTranscripts metadata(extendedAnnotationRanges)$lowConfidenceTranscripts = lowConfidenceTranscripts @@ -636,11 +638,11 @@ combindRowDataWithRanges <- function(rowDataCombinedFiltered, exonRangesCombined if("NDR" %in% colnames(rowDataCombinedFiltered)){ mcols(extendedAnnotationRanges) <- rowDataCombinedFiltered[, c("GENEID", "novelGene", "novelTranscript", "txClassDescription","readCount", "NDR", - "relReadCount")] + "maxTxScore", "maxTxScore.noFit", "relReadCount")] } else{ mcols(extendedAnnotationRanges) <- rowDataCombinedFiltered[, c("GENEID", "novelGene", "novelTranscript", "txClassDescription","readCount", - "relReadCount")] + "maxTxScore", "maxTxScore.noFit", "relReadCount")] } return(extendedAnnotationRanges) } @@ -659,11 +661,15 @@ combineWithAnnotations <- function(rowDataCombinedFiltered, mcols(annotationRangesToMerge)$novelTranscript <- FALSE mcols(annotationRangesToMerge)$novelGene <- FALSE mcols(annotationRangesToMerge)$NDR <- NA + mcols(annotationRangesToMerge)$maxTxScore <- NA + mcols(annotationRangesToMerge)$maxTxScore.noFit <- NA mcols(extendedAnnotationRanges) <- mcols(extendedAnnotationRanges)[,colnames(mcols(extendedAnnotationRanges))] #copy over stats to annotations from read classes mcols(annotationRangesToMerge[equalRanges$TXNAME])$NDR = equalRanges$NDR mcols(annotationRangesToMerge[equalRanges$TXNAME])$readCount = equalRanges$readCount mcols(annotationRangesToMerge[equalRanges$TXNAME])$relReadCount = equalRanges$relReadCount + mcols(annotationRangesToMerge[equalRanges$TXNAME])$maxTxScore = equalRanges$maxTxScore + mcols(annotationRangesToMerge[equalRanges$TXNAME])$maxTxScore.noFit = equalRanges$maxTxScore.noFit #mcols(annotationRangesToMerge[equalRanges$TXNAME])$relSubsetCount = equalRanges$relSubsetCount } if (length(extendedAnnotationRanges)) { From 21187ce99429455b2a7fb2d9b28d518655941083 Mon Sep 17 00:00:00 2001 From: Andre Date: Thu, 27 Apr 2023 14:36:44 +0800 Subject: [PATCH 016/189] read and write the txScore to GTF --- R/prepareAnnotations_utilityFunctions.R | 10 ++++++++-- R/readWrite.R | 18 +++++++++++++----- 2 files changed, 21 insertions(+), 7 deletions(-) diff --git a/R/prepareAnnotations_utilityFunctions.R b/R/prepareAnnotations_utilityFunctions.R index 0cdfd969..2436024e 100644 --- a/R/prepareAnnotations_utilityFunctions.R +++ b/R/prepareAnnotations_utilityFunctions.R @@ -28,8 +28,14 @@ prepareAnnotationsFromGTF <- function(file) { data$GENEID <- gsub("gene_id (.*?);.*", "\\1", data$attribute) data$TXNAME <- gsub(".*transcript_id (.*?);.*", "\\1", data$attribute) data$NDR <- NULL + data$maxTxScore <- NULL + data$maxTxScore.noFit <- NULL hasNDR = all(grepl("NDR ", data$attribute)) - if(hasNDR) data$NDR <- gsub(".*NDR (.*?);.*", "\\1", data$attribute) + if(hasNDR) { + data$NDR <- gsub(".*NDR (.*?);.*", "\\1", data$attribute) + data$maxTxScore <- gsub(".*maxTxScore (.*?);.*", "\\1", data$attribute) + data$maxTxScore.noFit <- gsub(".*maxTxScore.noFit (.*?);.*", "\\1", data$attribute) + } multiTxCheck <- as_tibble(data) %>% select(seqname, GENEID) %>% distinct() %>% group_by(GENEID) %>% mutate(n=n(), id=paste0('-',row_number())) if(any(multiTxCheck$n>1)) { # identical TXNAMES @@ -48,7 +54,7 @@ prepareAnnotationsFromGTF <- function(file) { data$GENEID <- uniqueNamesTbl$gene_unique } geneData <- unique(data[, c("TXNAME", "GENEID")]) - geneData <- if(hasNDR) { unique(data[, c("TXNAME", "GENEID", "NDR")]) + geneData <- if(hasNDR) { unique(data[, c("TXNAME", "GENEID", "NDR", "maxTxScore", "maxTxScore.noFit")]) } else {unique(data[, c("TXNAME", "GENEID")])} grlist <- makeGRangesListFromDataFrame( data[, c("seqname", "start", "end", "strand", "TXNAME")], diff --git a/R/readWrite.R b/R/readWrite.R index d3bce597..4f6087d2 100644 --- a/R/readWrite.R +++ b/R/readWrite.R @@ -86,11 +86,17 @@ writeToGTF <- function(annotation, file, geneIDs = NULL) { stop("The inputted GRangesList is of the wrong class.") } NDR = NULL + txScore = NULL + txScore.noFit = NULL df <- as_tibble(annotation) df$exon_rank <- paste('exon_number "', df$exon_rank, '";', sep = "") if(!is.null(mcols(annotation)$NDR)){ NDR = rep(mcols(annotation)$NDR, unname(elementNROWS(annotation))) df$NDR <- paste('NDR "', as.character(NDR), '";', sep = "") + txScore = rep(mcols(annotation)$maxTxScore, unname(elementNROWS(annotation))) + df$txScore <- paste('maxTxScore "', as.character(txScore), '";', sep = "") + txScore.noFit = rep(mcols(annotation)$maxTxScore.noFit, unname(elementNROWS(annotation))) + df$txScore.noFit <- paste('maxTxScore.noFit "', as.character(txScore.noFit), '";', sep = "") } if (missing(geneIDs)) { if (!is.null(mcols(annotation, use.names = FALSE)$GENEID)) { @@ -105,7 +111,7 @@ writeToGTF <- function(annotation, file, geneIDs = NULL) { df$group_name <- paste('transcript_id "', df$group_name, '";', sep = "") df$GENEID <- paste('gene_id "', df$GENEID, '";', sep = "") dfExon <- mutate(df, source = "Bambu", feature = "exon", score = ".", - frame = ".", attributes = paste(GENEID, group_name, exon_rank, NDR)) %>% + frame = ".", attributes = paste(GENEID, group_name, exon_rank, NDR, txScore, txScore.noFit)) %>% select(seqnames, source, feature, start, end, score, strand, frame, attributes, group_name) dfTx <- as.data.frame(range(ranges(annotation))) @@ -114,11 +120,13 @@ writeToGTF <- function(annotation, file, geneIDs = NULL) { dfTx$group_name <- paste('transcript_id "', dfTx$group_name, '";', sep = "") dfTx$GENEID <- paste('gene_id "', dfTx$GENEID, '";', sep = "") - if(!is.null(mcols(annotation)$NDR)) dfTx$NDR <- - paste('NDR "', mcols(annotation)$NDR, '";', sep = "") - + if(!is.null(mcols(annotation)$NDR)) { + dfTx$NDR <- paste('NDR "', mcols(annotation)$NDR, '";', sep = "") + dfTx$txScore <- paste('txScore "', mcols(annotation)$txScore, '";', sep = "") + dfTx$txScore.noFit <- paste('txScore.noFit "', mcols(annotation)$txScore.noFit, '";', sep = "") + } dfTx <- mutate(dfTx,source = "Bambu", feature = "transcript", score = ".", - frame = ".", attributes = paste(GENEID, group_name, NDR)) %>% + frame = ".", attributes = paste(GENEID, group_name, NDR, txScore, txScore.noFit)) %>% select(seqnames, source, feature, start, end, score, strand, frame, attributes, group_name) From 0c288a7283bc309c17f6187a785f1e1a2a70799a Mon Sep 17 00:00:00 2001 From: Andre Date: Thu, 27 Apr 2023 15:15:32 +0800 Subject: [PATCH 017/189] NA's are loaded in as NAs from GTF --- R/prepareAnnotations_utilityFunctions.R | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/R/prepareAnnotations_utilityFunctions.R b/R/prepareAnnotations_utilityFunctions.R index 2436024e..dbf4b083 100644 --- a/R/prepareAnnotations_utilityFunctions.R +++ b/R/prepareAnnotations_utilityFunctions.R @@ -32,9 +32,9 @@ prepareAnnotationsFromGTF <- function(file) { data$maxTxScore.noFit <- NULL hasNDR = all(grepl("NDR ", data$attribute)) if(hasNDR) { - data$NDR <- gsub(".*NDR (.*?);.*", "\\1", data$attribute) - data$maxTxScore <- gsub(".*maxTxScore (.*?);.*", "\\1", data$attribute) - data$maxTxScore.noFit <- gsub(".*maxTxScore.noFit (.*?);.*", "\\1", data$attribute) + data$NDR <- as.numeric(gsub(".*NDR (.*?);.*", "\\1", data$attribute)) + data$maxTxScore <- as.numeric(gsub(".*maxTxScore (.*?);.*", "\\1", data$attribute)) + data$maxTxScore.noFit <- as.numeric(gsub(".*maxTxScore.noFit (.*?);.*", "\\1", data$attribute)) } multiTxCheck <- as_tibble(data) %>% select(seqname, GENEID) %>% distinct() %>% group_by(GENEID) %>% mutate(n=n(), id=paste0('-',row_number())) From 1741376b45234ce9e4e2771345424867159136cd Mon Sep 17 00:00:00 2001 From: Andre Date: Thu, 27 Apr 2023 15:15:54 +0800 Subject: [PATCH 018/189] setNDR can now recommend NDR --- R/bambu-extendAnnotations-utilityExtend.R | 32 +++++++++++++++++++---- 1 file changed, 27 insertions(+), 5 deletions(-) diff --git a/R/bambu-extendAnnotations-utilityExtend.R b/R/bambu-extendAnnotations-utilityExtend.R index 73828750..85641973 100644 --- a/R/bambu-extendAnnotations-utilityExtend.R +++ b/R/bambu-extendAnnotations-utilityExtend.R @@ -177,6 +177,20 @@ recommendNDR <- function(combinedTranscripts, baselineFDR = 0.1, NDR = NULL, def return(NDR) } +recommendNDR.onAnnotations = function(annotations, prefix = "Bambu", baselineFDR = 0.1, NDR = NULL, defaultModels2 = defaultModels2){ + mcols = mcols(annotations)[!is.na(mcols(annotations)$maxTxScore),] + equal = !grepl(prefix, mcols$TXNAME) + #add envirnment so poly() works + attr(defaultModels2$lmNDR[["terms"]], ".Environment") <- new.env(parent = parent.env(globalenv())) + baseline = predict(defaultModels2$lmNDR, newdata=data.frame(NDR=baselineFDR)) + attr(defaultModels2$lmNDR[["terms"]], ".Environment") = c() + score = mcols$maxTxScore.noFit + NDRscores = calculateNDR(score, equal) + NDR.rec = predict(lm(NDRscores~poly(score,3,raw=TRUE)), newdata=data.frame(score=baseline)) + NDR.rec = round(NDR.rec,3) + return(NDR.rec) +} + #' Calculate NDR based on transcripts #' @noRd @@ -789,23 +803,31 @@ addGeneIdsToReadClassTable <- function(readClassTable, distTable, #' @title Function to change NDR threshold on extendedAnnotations #' @description This function train a model for use on other data #' @param extendedAnnotations A GRangesList object produced from bambu(quant = FALSE) or rowRanges(se) -#' @param NDR The maximum NDR for novel transcripts to be in extendedAnnotations (0-1) +#' @param NDR The maximum NDR for novel transcripts to be in extendedAnnotations (0-1). If not provided a recommended NDR is calculated. #' @param includeRef A boolean which if TRUE will also filter out reference annotations based on their NDR #' @param prefix A string which determines which transcripts are considered novel by bambu and will be filtered (by default = 'Bambu') #' Output - returns a similiar GRangesList object with entries swapped into or out of metadata(extendedAnnotations)$lowConfidenceTranscripts #' @details #' @return extendedAnnotations with a new NDR threshold #' @export -setNDR = function(extendedAnnotations, NDR, includeRef = FALSE, prefix = 'Bambu'){ - +setNDR = function(extendedAnnotations, NDR = NULL, includeRef = FALSE, prefix = 'Bambu', baselineFDR = 0.1, defaultModels2 = defaultModels){ + #Check to see if the annotations/gtf are dervived from Bambu if(is.null(mcols(extendedAnnotations)$NDR)){ - warning("Annotations were not extended by Bambu. NDR can not be set") + warning("Annotations were not extended by Bambu (or the wrong prefix was provided). NDR can not be set") return(extendedAnnotations) } - + if(is.null(metadata(extendedAnnotations)$lowConfidenceTranscripts)) metadata(extendedAnnotations)$lowConfidenceTranscripts = GRangesList() + #recommend an NDR (needed when users read in Bambu GTF) + if(is.null(NDR)){ + tempAnno = c(metadata(extendedAnnotations)$lowConfidenceTranscripts, extendedAnnotations) + NDR = recommendNDR.onAnnotations(tempAnno, prefix = prefix, baselineFDR = baselineFDR, NDR = NDR, defaultModels2 = defaultModels2) + message("Recommending a novel discovery rate (NDR) of: ", NDR) + } + + #If reference annotations should be filtered too (note that reference annotations with no read support arn't filtered) if(includeRef){ toRemove = (mcols(extendedAnnotations)$NDR > NDR) toAdd = mcols(metadata(extendedAnnotations)$lowConfidenceTranscripts)$NDR <= NDR From 8266e69b3e66719b72cee4e2805fd31e15164862 Mon Sep 17 00:00:00 2001 From: Andre Date: Thu, 27 Apr 2023 16:03:56 +0800 Subject: [PATCH 019/189] Add documentation to setNDR and carry arguments over --- R/bambu-extendAnnotations-utilityExtend.R | 2 ++ R/bambu.R | 4 +++- 2 files changed, 5 insertions(+), 1 deletion(-) diff --git a/R/bambu-extendAnnotations-utilityExtend.R b/R/bambu-extendAnnotations-utilityExtend.R index 85641973..316cbe1b 100644 --- a/R/bambu-extendAnnotations-utilityExtend.R +++ b/R/bambu-extendAnnotations-utilityExtend.R @@ -806,6 +806,8 @@ addGeneIdsToReadClassTable <- function(readClassTable, distTable, #' @param NDR The maximum NDR for novel transcripts to be in extendedAnnotations (0-1). If not provided a recommended NDR is calculated. #' @param includeRef A boolean which if TRUE will also filter out reference annotations based on their NDR #' @param prefix A string which determines which transcripts are considered novel by bambu and will be filtered (by default = 'Bambu') +#' @param baselineFDR a value between 0-1. Bambu uses this FDR on the trained model to recommend an equivilent NDR threshold to be used for the sample. By default, a baseline FDR of 0.1 is used. This does not impact the analysis if an NDR is set. +#' @param defaultModels a bambu trained model object that bambu will use when fitReadClassModel==FALSE or the data is not suitable for training, defaults to the pretrained model in the bambu package #' Output - returns a similiar GRangesList object with entries swapped into or out of metadata(extendedAnnotations)$lowConfidenceTranscripts #' @details #' @return extendedAnnotations with a new NDR threshold diff --git a/R/bambu.R b/R/bambu.R index cb9c71cc..c7c06206 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -184,7 +184,9 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, if (quant) { message("--- Start isoform quantification ---") if(!is.null(NDR) & !discovery) - annotations = setNDR(annotations, NDR, prefix = isoreParameters$prefix) + annotations = setNDR(annotations, NDR, prefix = isoreParameters$prefix, + baselineFDR = isoreParameters[["baselineFDR"]], + defaultModels2 = isoreParameters[["defaultModels"]]) if(length(annotations)==0) stop("No valid annotations, if running de novo please try less stringent parameters") countsSe <- bplapply(readClassList, bambu.quantify, From e159b480af524014b25db3ede29fd8a3f60f8e8c Mon Sep 17 00:00:00 2001 From: Andre Date: Thu, 27 Apr 2023 16:04:25 +0800 Subject: [PATCH 020/189] Update test cases to include metadata and new warnings --- ...onGranges_txdbGrch38_91_chr9_1_1000000.rds | Bin 3876 -> 4512 bytes ...rectRNA_replicate5_run1_chr9_1_1000000.rds | Bin 4688 -> 4500 bytes ...rectRNA_replicate5_run1_chr9_1_1000000.rds | Bin 4804 -> 5320 bytes ...rectRNA_replicate5_run1_chr9_1_1000000.rds | Bin 4700 -> 4592 bytes ...rectRNA_replicate5_run1_chr9_1_1000000.rds | Bin 4720 -> 5148 bytes ...rectRNA_replicate5_run1_chr9_1_1000000.rds | Bin 4720 -> 5220 bytes ...rectRNA_replicate5_run1_chr9_1_1000000.rds | Bin 2100 -> 2336 bytes ...rectRNA_replicate5_run1_chr9_1_1000000.rds | Bin 5544 -> 5420 bytes ...rectRNA_replicate5_run1_chr9_1_1000000.rds | Bin 7616 -> 8104 bytes ...rectRNA_replicate5_run1_chr9_1_1000000.rds | Bin 4452 -> 4336 bytes ...rectRNA_replicate5_run1_chr9_1_1000000.rds | Bin 4452 -> 4332 bytes 11 files changed, 0 insertions(+), 0 deletions(-) diff --git a/inst/extdata/extendedAnnotationGranges_txdbGrch38_91_chr9_1_1000000.rds b/inst/extdata/extendedAnnotationGranges_txdbGrch38_91_chr9_1_1000000.rds index 0b70a66f129249bcb7f36157e4146cd60a76f5ed..68b9c92a3c52bb95c49ef644da8101c5cccccc1b 100644 GIT binary patch delta 2027 zcmV_xSQai5Vi<3&DwbZpq5qnK#Y zoYGcE%P4n3G10p7#}Y`XXw{6A@3uTxSkan9hX`oq@;OUat&3E8OQrL3np%IjB{Mr` z`o!3BW#I~1u@%B$wi|WS-CuY(j0*}FFc5U7ZLl)j=3&Iz0bosdrkW4lf{Fg9{ZULZ zHX>1Xp@S9BuM#4y4wfU}-zB*-s;jP#` z+qfatEG!T5u%K$M$%rn5)}em`QA|f&YkS}ir#W@_!4Z33OVCeK!mLW?3kK;|J?DopLO!L|_pJm_%dW)wNFVu1}+vgmyHcY^ud2ZR==^Ckr@!< zzK3C!>DTS89znV)N7^C&IuwPu)-%x9@6gh0$bxA&sfp$P(lwfYGijT#h)9y5l-+5@ zwjdufgfYIkrwwN|oQL1$U5pfbd^eARzTJrx-dqda#?l0S;OT$(>uvM9TA?4^hF8 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zD`U)H34R+hVJSHUeq@NppX)KuSY|-&fPinN+Oj#g(3L032=<(KUvo&veib5?h^808Qm5L0 zgfRk!?UYkyfDb8+o&a`ez1rLxOdAR>+)8DoZy?zQZ)(?dtD|9N5s_#E1eAz7MOl`?HLU%7MdxS^Yhjl@?bb)aTMfZ%Gg`1$VI*Y;A!TPw^CMMM z;)$s)3T>Nayu4TsZ0@nOm;1uk!8=&7U1jl#FQ*bNvy9p>wu=U4@hvKBj2b0z8Q;+F@8c3@23)OyQl8Q8Y_LyHjN7^rq24L`#g}Do&Xb++03Lg%i z)C|tU^Ou_|*MaR$uMx@KpT0V-(2&4%;jFL`8XZ3s4dYa}6>SN|&gO$f=>VjA6Z8(N zyl4mj@O&64r|DEYL>Uc!3JsL4HUDBuBSCPpMVkD&!FKlNX0@Kuf5|^&hB979VLAN5 zJwC9}ggpzwC!Yl$n;O*=j3bjpFL zKtwhQTCL4Bkv1&XS!%LDH_hBjm4*al^OLKv;uKGW{+k@SLxzgeSnQwH=~=su`={u- qPu8{do2VF_0001w=-`I{0lp%?{Q&^7Rf4%bFb#_W000000a;q{X^1@l From d0b3b7d6753ae3639a9b972293b409ddf778ab1b Mon Sep 17 00:00:00 2001 From: Andre Date: Fri, 28 Apr 2023 15:25:30 +0800 Subject: [PATCH 021/189] Assign names to transcripts earler so subset and lowConf are given names --- R/bambu-extendAnnotations-utilityExtend.R | 17 ++++++++++------- 1 file changed, 10 insertions(+), 7 deletions(-) diff --git a/R/bambu-extendAnnotations-utilityExtend.R b/R/bambu-extendAnnotations-utilityExtend.R index 316cbe1b..bc67281b 100644 --- a/R/bambu-extendAnnotations-utilityExtend.R +++ b/R/bambu-extendAnnotations-utilityExtend.R @@ -81,6 +81,10 @@ filterTranscriptsByAnnotation <- function(rowDataCombined, annotationGrangesList #calculate relative read count before any filtering rowDataCombined <- group_by(rowDataCombined, GENEID) %>% mutate(relReadCount = readCount/sum(readCount)) + rowDataCombined$TXNAME[is.na(rowDataCombined$TXNAME)] <- paste0( + prefix, "Tx", seq_len(sum(is.na(rowDataCombined$TXNAME)))) + names(exonRangesCombined) <- rowDataCombined$TXNAME + #filter out subset reads if (remove.subsetTx) { # (1) based on compatibility with annotations notCompatibleIds <- (!grepl("compatible", rowDataCombined$readClassType) | @@ -651,11 +655,11 @@ combindRowDataWithRanges <- function(rowDataCombinedFiltered, exonRangesCombined extendedAnnotationRanges <- exonRangesCombinedFiltered if("NDR" %in% colnames(rowDataCombinedFiltered)){ mcols(extendedAnnotationRanges) <- - rowDataCombinedFiltered[, c("GENEID", "novelGene", "novelTranscript", "txClassDescription","readCount", "NDR", + rowDataCombinedFiltered[, c("TXNAME", "GENEID", "novelGene", "novelTranscript", "txClassDescription","readCount", "NDR", "maxTxScore", "maxTxScore.noFit", "relReadCount")] } else{ mcols(extendedAnnotationRanges) <- - rowDataCombinedFiltered[, c("GENEID", "novelGene", "novelTranscript", "txClassDescription","readCount", + rowDataCombinedFiltered[, c("TXNAME", "GENEID", "novelGene", "novelTranscript", "txClassDescription","readCount", "maxTxScore", "maxTxScore.noFit", "relReadCount")] } return(extendedAnnotationRanges) @@ -665,9 +669,9 @@ combindRowDataWithRanges <- function(rowDataCombinedFiltered, exonRangesCombined #' @noRd combineWithAnnotations <- function(rowDataCombinedFiltered, extendedAnnotationRanges,annotationGrangesList, prefix){ - equalRanges = rowDataCombinedFiltered[!is.na(rowDataCombinedFiltered$TXNAME),] + equalRanges = rowDataCombinedFiltered[!(rowDataCombinedFiltered$novelTranscript),] #remove extended ranges that are already present in annotation - extendedAnnotationRanges <- extendedAnnotationRanges[is.na(rowDataCombinedFiltered$TXNAME)] + extendedAnnotationRanges <- extendedAnnotationRanges[rowDataCombinedFiltered$novelTranscript] annotationRangesToMerge <- annotationGrangesList if(length(annotationGrangesList)){ mcols(annotationRangesToMerge)$readCount <- NA @@ -687,8 +691,7 @@ combineWithAnnotations <- function(rowDataCombinedFiltered, #mcols(annotationRangesToMerge[equalRanges$TXNAME])$relSubsetCount = equalRanges$relSubsetCount } if (length(extendedAnnotationRanges)) { - mcols(extendedAnnotationRanges)$TXNAME <- paste0( - prefix, "Tx", seq_along(extendedAnnotationRanges)) + mcols(extendedAnnotationRanges)$TXNAME <- rowDataCombinedFiltered[rowDataCombinedFiltered$novelTranscript,]$TXNAME names(extendedAnnotationRanges) <- mcols(extendedAnnotationRanges)$TXNAME extendedAnnotationRanges <- c(extendedAnnotationRanges, annotationRangesToMerge) # this will throw error in line 648-649 when extendedAnnotationRanges is empty @@ -837,7 +840,7 @@ setNDR = function(extendedAnnotations, NDR = NULL, includeRef = FALSE, prefix = toRemove = (mcols(extendedAnnotations)$NDR > NDR & grepl(prefix, mcols(extendedAnnotations)$TXNAME)) toAdd = (mcols(metadata(extendedAnnotations)$lowConfidenceTranscripts)$NDR <= NDR & - grepl(prefix, mcols(extendedAnnotations)$TXNAME)) + grepl(prefix, mcols(metadata(extendedAnnotations)$lowConfidenceTranscripts)$TXNAME)) } temp = c(metadata(extendedAnnotations)$lowConfidenceTranscripts[!toAdd], extendedAnnotations[toRemove]) From afc9e039fb7162d3a8b479ada9603b1f57fdc121 Mon Sep 17 00:00:00 2001 From: Andre Date: Fri, 28 Apr 2023 15:55:55 +0800 Subject: [PATCH 022/189] Remove unneeded argument --- R/bambu-extendAnnotations-utilityExtend.R | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/R/bambu-extendAnnotations-utilityExtend.R b/R/bambu-extendAnnotations-utilityExtend.R index bc67281b..164dfc54 100644 --- a/R/bambu-extendAnnotations-utilityExtend.R +++ b/R/bambu-extendAnnotations-utilityExtend.R @@ -181,7 +181,7 @@ recommendNDR <- function(combinedTranscripts, baselineFDR = 0.1, NDR = NULL, def return(NDR) } -recommendNDR.onAnnotations = function(annotations, prefix = "Bambu", baselineFDR = 0.1, NDR = NULL, defaultModels2 = defaultModels2){ +recommendNDR.onAnnotations = function(annotations, prefix = "Bambu", baselineFDR = 0.1, defaultModels2 = defaultModels2){ mcols = mcols(annotations)[!is.na(mcols(annotations)$maxTxScore),] equal = !grepl(prefix, mcols$TXNAME) #add envirnment so poly() works @@ -828,7 +828,7 @@ setNDR = function(extendedAnnotations, NDR = NULL, includeRef = FALSE, prefix = #recommend an NDR (needed when users read in Bambu GTF) if(is.null(NDR)){ tempAnno = c(metadata(extendedAnnotations)$lowConfidenceTranscripts, extendedAnnotations) - NDR = recommendNDR.onAnnotations(tempAnno, prefix = prefix, baselineFDR = baselineFDR, NDR = NDR, defaultModels2 = defaultModels2) + NDR = recommendNDR.onAnnotations(tempAnno, prefix = prefix, baselineFDR = baselineFDR, defaultModels2 = defaultModels2) message("Recommending a novel discovery rate (NDR) of: ", NDR) } From 735a22e4ab0ed5344823909c0a50cb7e12424775 Mon Sep 17 00:00:00 2001 From: Andre Date: Fri, 28 Apr 2023 15:56:14 +0800 Subject: [PATCH 023/189] Fix includeRef bug --- R/bambu-extendAnnotations-utilityExtend.R | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/R/bambu-extendAnnotations-utilityExtend.R b/R/bambu-extendAnnotations-utilityExtend.R index 164dfc54..f90a1b90 100644 --- a/R/bambu-extendAnnotations-utilityExtend.R +++ b/R/bambu-extendAnnotations-utilityExtend.R @@ -827,15 +827,16 @@ setNDR = function(extendedAnnotations, NDR = NULL, includeRef = FALSE, prefix = #recommend an NDR (needed when users read in Bambu GTF) if(is.null(NDR)){ - tempAnno = c(metadata(extendedAnnotations)$lowConfidenceTranscripts, extendedAnnotations) + tempAnno = c(extendedAnnotations, metadata(extendedAnnotations)$lowConfidenceTranscripts) NDR = recommendNDR.onAnnotations(tempAnno, prefix = prefix, baselineFDR = baselineFDR, defaultModels2 = defaultModels2) message("Recommending a novel discovery rate (NDR) of: ", NDR) } #If reference annotations should be filtered too (note that reference annotations with no read support arn't filtered) if(includeRef){ - toRemove = (mcols(extendedAnnotations)$NDR > NDR) - toAdd = mcols(metadata(extendedAnnotations)$lowConfidenceTranscripts)$NDR <= NDR + toRemove = (!is.na(mcols(extendedAnnotations)$NDR) & mcols(extendedAnnotations)$NDR > NDR) + toAdd = !is.na(mcols(metadata(extendedAnnotations)$lowConfidenceTranscripts)$NDR) & + mcols(metadata(extendedAnnotations)$lowConfidenceTranscripts)$NDR <= NDR } else { toRemove = (mcols(extendedAnnotations)$NDR > NDR & grepl(prefix, mcols(extendedAnnotations)$TXNAME)) From d2427963ac6ad3f96567bf2a95857abdbba9c733 Mon Sep 17 00:00:00 2001 From: Andre Date: Fri, 28 Apr 2023 16:01:03 +0800 Subject: [PATCH 024/189] Unit tests for setNDR --- tests/testthat/test_setNDR.R | 94 ++++++++++++++++++++++++++++++++++++ 1 file changed, 94 insertions(+) create mode 100644 tests/testthat/test_setNDR.R diff --git a/tests/testthat/test_setNDR.R b/tests/testthat/test_setNDR.R new file mode 100644 index 00000000..7d4bca53 --- /dev/null +++ b/tests/testthat/test_setNDR.R @@ -0,0 +1,94 @@ +context("setNDR") + +test_that("txRange generates a gene and transcript score",{ + readClasses <- readRDS(system.file("extdata","readClassesUnstranded_SGNex_A549_directRNA_replicate5_run1_chr9_1_1000000.rds",package = "bambu")) + annotations <- readRDS(system.file("extdata","annotationGranges_txdbGrch38_91_chr9_1_1000000.rds",package = "bambu")) + genomeSequence <- system.file("extdata","Homo_sapiens.GRCh38.dna_sm.primary_assembly_chr9_1_1000000.fa",package = "bambu") + genomeSequence <- checkInputSequence(genomeSequence) + + se = scoreReadClasses(readClasses, genomeSequence, annotations, defaultModels) + + seExpected = readRDS(system.file("extdata", "seReadClassUnstranded_SGNex_A549_directRNA_replicate5_run1_chr9_1_1000000.rds", package = "bambu")) + + expect_is(rowData(se)$txScore, class = 'numeric') + expect_equal(rowData(se)$txScore, rowData(seExpected)$txScore) +}) + +test_that("Correctly moves transcripts with NDR above the threshold into lowCofidenceTranscripts",{ + extendedAnnotationsExpected <- readRDS(system.file("extdata", "extendedAnnotationGranges_txdbGrch38_91_chr9_1_1000000.rds",package = "bambu")) + + expect_equal(length(extendedAnnotationsExpected), 106) + expect_equal(length(metadata(extendedAnnotationsExpected)$lowConfidenceTranscripts),1) + + extendedAnnotationsExpected_0.1 = setNDR(extendedAnnotationsExpected, 0.1) + expect_equal(length(extendedAnnotationsExpected_0.1), 105) + expect_equal(length(metadata(extendedAnnotationsExpected_0.1)$lowConfidenceTranscripts),2) +}) + +test_that("Correctly moves transcripts with NDR below the threshold into the extendedAnnotations",{ + extendedAnnotationsExpected <- readRDS(system.file("extdata", "extendedAnnotationGranges_txdbGrch38_91_chr9_1_1000000.rds",package = "bambu")) + + expect_equal(length(extendedAnnotationsExpected), 106) + expect_equal(length(metadata(extendedAnnotationsExpected)$lowConfidenceTranscripts),1) + + extendedAnnotationsExpected_1 = setNDR(extendedAnnotationsExpected, 1) + expect_equal(length(extendedAnnotationsExpected_1), 107) + expect_equal(length(metadata(extendedAnnotationsExpected_1)$lowConfidenceTranscripts),0) +}) + +test_that("Reference annotations are not moved unless includeRef is used", { + extendedAnnotationsExpected <- readRDS(system.file("extdata", "extendedAnnotationGranges_txdbGrch38_91_chr9_1_1000000.rds",package = "bambu")) + + expect_equal(length(extendedAnnotationsExpected), 106) + expect_equal(length(metadata(extendedAnnotationsExpected)$lowConfidenceTranscripts),1) + + extendedAnnotationsExpected_0.5 = setNDR(extendedAnnotationsExpected, 0.5, includeRef = TRUE) + expect_equal(length(extendedAnnotationsExpected_0.5), 104) + expect_equal(length(metadata(extendedAnnotationsExpected_0.5)$lowConfidenceTranscripts),3) +}) + +test_that("setNDR only effects transcripts with the prefix", { + extendedAnnotationsExpected <- readRDS(system.file("extdata", "extendedAnnotationGranges_txdbGrch38_91_chr9_1_1000000.rds",package = "bambu")) + + expect_equal(length(extendedAnnotationsExpected), 106) + expect_equal(length(metadata(extendedAnnotationsExpected)$lowConfidenceTranscripts),1) + + extendedAnnotationsExpected_1 = setNDR(extendedAnnotationsExpected, 1, prefix = "Stringtie2") + expect_equal(length(extendedAnnotationsExpected_1), 106) + expect_equal(length(metadata(extendedAnnotationsExpected_1)$lowConfidenceTranscripts),1) +}) + +test_that("setNDR saves the used NDR threshold correctly", { + extendedAnnotationsExpected <- readRDS(system.file("extdata", "extendedAnnotationGranges_txdbGrch38_91_chr9_1_1000000.rds",package = "bambu")) + metadata(extendedAnnotationsExpected)$NDR = 0.7 + extendedAnnotationsExpected_1 = setNDR(extendedAnnotationsExpected, 1) + metadata(extendedAnnotationsExpected_1)$NDR = 1 +}) + +test_that("setNDR works when no lowConfidenceTranscripts are present", { + seIsoReCombined <- readRDS(system.file("extdata", "seIsoReCombined_SGNex_A549_directRNA_replicate5_run1_chr9_1_1000000.rds", package = "bambu")) + gr <- readRDS(system.file("extdata", "annotationGranges_txdbGrch38_91_chr9_1_1000000.rds", package = "bambu")) + + extendedAnnotations <- isore.extendAnnotations(combinedTranscripts=seIsoReCombined, + annotationGrangesList=gr, + remove.subsetTx = TRUE, min.sampleNumber = 1, NDR = 1, + min.exonDistance = 35, min.exonOverlap = 10, + min.primarySecondaryDist = 5, min.primarySecondaryDistStartEnd = 5, + prefix='Bambu', verbose=FALSE, defaultModels = defaultModels) + + extendedAnnotationsExpected_0.7 = setNDR(extendedAnnotationsExpected, 0.7) + expect_equal(length(extendedAnnotationsExpected), 106) + expect_equal(length(metadata(extendedAnnotationsExpected)$lowConfidenceTranscripts),1) +}) + +test_that("setNDR recommends the correct NDR", { + extendedAnnotationsExpected <- readRDS(system.file("extdata", "extendedAnnotationGranges_txdbGrch38_91_chr9_1_1000000.rds",package = "bambu")) + + extendedAnnotationsExpected_rec = setNDR(extendedAnnotationsExpected) + expect_equal(unname(metadata(extendedAnnotationsExpected_rec)$NDR), -0.013) +}) + +test_that("setNDR handles annotations with no NDR", { + annotations <- readRDS(system.file("extdata","annotationGranges_txdbGrch38_91_chr9_1_1000000.rds",package = "bambu")) + expect_warning(setNDR(annotations, 0.5), "Annotations were not extended by Bambu") +}) \ No newline at end of file From 75458de6023d5c0c621ea141e1e1794de8768c1e Mon Sep 17 00:00:00 2001 From: Andre Date: Fri, 28 Apr 2023 16:26:23 +0800 Subject: [PATCH 025/189] Unit tests for reading and writing NDR and txScore --- data-raw/DATASET.R | 6 +- ...onGranges_txdbGrch38_91_chr9_1_1000000.gtf | 947 ++++++++++++++++++ ...onGranges_txdbGrch38_91_chr9_1_1000000.rds | Bin 4512 -> 4608 bytes tests/testthat/test_prepareAnnotations.R | 8 + tests/testthat/test_readWrite.R | 14 + 5 files changed, 972 insertions(+), 3 deletions(-) create mode 100644 inst/extdata/extendedAnnotationGranges_txdbGrch38_91_chr9_1_1000000.gtf diff --git a/data-raw/DATASET.R b/data-raw/DATASET.R index 95aae23b..df6b4616 100755 --- a/data-raw/DATASET.R +++ b/data-raw/DATASET.R @@ -300,12 +300,12 @@ gr <- readRDS(system.file("extdata", "annotationGranges_txdbGrch38_91_chr9_1_100 extendedAnnotations <- isore.extendAnnotations(combinedTranscripts=seIsoReCombined, annotationGrangesList=gr, - remove.subsetTx = TRUE, min.sampleNumber = 1, NDR = 0.1, + remove.subsetTx = TRUE, min.sampleNumber = 1, NDR = 0.7, min.exonDistance = 35, min.exonOverlap = 10, min.primarySecondaryDist = 5, min.primarySecondaryDistStartEnd = 5, - prefix='', verbose=FALSE, defaultModels = defaultModels) + prefix='Bambu', verbose=FALSE, defaultModels = defaultModels) saveRDS(extendedAnnotations, file = "./inst/extdata/extendedAnnotationGranges_txdbGrch38_91_chr9_1_1000000.rds", compress = "xz") - +writeToGTF(extendedAnnotations, "./inst/extdata/extendedAnnotationGranges_txdbGrch38_91_chr9_1_1000000.gtf") ## expected output for test isore seReadClass1 <- readRDS(system.file("extdata", "seReadClassUnstranded_SGNex_A549_directRNA_replicate5_run1_chr9_1_1000000.rds", package = "bambu")) diff --git a/inst/extdata/extendedAnnotationGranges_txdbGrch38_91_chr9_1_1000000.gtf b/inst/extdata/extendedAnnotationGranges_txdbGrch38_91_chr9_1_1000000.gtf new file mode 100644 index 00000000..a58dfa8b --- /dev/null +++ b/inst/extdata/extendedAnnotationGranges_txdbGrch38_91_chr9_1_1000000.gtf @@ -0,0 +1,947 @@ +9 Bambu transcript 12134 13783 . + . gene_id "ENSG00000236875"; transcript_id "ENST00000421620"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 12134 12190 . + . gene_id "ENSG00000236875"; transcript_id "ENST00000421620"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 12291 12340 . + . gene_id "ENSG00000236875"; transcript_id "ENST00000421620"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 12726 12834 . + . gene_id "ENSG00000236875"; transcript_id "ENST00000421620"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 13088 13157 . + . gene_id "ENSG00000236875"; transcript_id "ENST00000421620"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 13338 13487 . + . gene_id "ENSG00000236875"; transcript_id "ENST00000421620"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 13566 13783 . + . gene_id "ENSG00000236875"; transcript_id "ENST00000421620"; exon_number "6"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 14513 19197 . - . gene_id "ENSG00000181404"; transcript_id "BambuTx1"; NDR "0.636065870523453"; txScore ""; txScore.noFit ""; +9 Bambu exon 14513 14940 . - . gene_id "ENSG00000181404"; transcript_id "BambuTx1"; exon_number "10"; NDR "0.636065870523453"; maxTxScore "0.363934129476547"; maxTxScore.noFit "0.363934129476547"; +9 Bambu transcript 14521 29739 . - . gene_id "ENSG00000181404"; transcript_id "ENST00000442898"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 14521 14940 . - . gene_id "ENSG00000181404"; transcript_id "ENST00000442898"; exon_number "11"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 15081 15149 . - . gene_id "ENSG00000181404"; transcript_id "BambuTx1"; exon_number "9"; NDR "0.636065870523453"; maxTxScore "0.363934129476547"; maxTxScore.noFit "0.363934129476547"; +9 Bambu exon 15081 15149 . - . gene_id "ENSG00000181404"; transcript_id "ENST00000442898"; exon_number "10"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 15909 16421 . - . gene_id "ENSG00000181404"; transcript_id "BambuTx1"; exon_number "8"; NDR "0.636065870523453"; maxTxScore "0.363934129476547"; maxTxScore.noFit "0.363934129476547"; +9 Bambu exon 15909 16061 . - . gene_id "ENSG00000181404"; transcript_id "ENST00000442898"; exon_number "9"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 16718 16876 . - . gene_id "ENSG00000181404"; transcript_id "BambuTx1"; exon_number "7"; NDR "0.636065870523453"; maxTxScore "0.363934129476547"; maxTxScore.noFit "0.363934129476547"; +9 Bambu exon 16718 16876 . - . gene_id "ENSG00000181404"; transcript_id "ENST00000442898"; exon_number "8"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 16965 17166 . - . gene_id "ENSG00000181404"; transcript_id "ENST00000442898"; exon_number "7"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 16969 17166 . - . gene_id "ENSG00000181404"; transcript_id "BambuTx1"; exon_number "6"; NDR "0.636065870523453"; maxTxScore "0.363934129476547"; maxTxScore.noFit "0.363934129476547"; +9 Bambu exon 17344 17479 . - . gene_id "ENSG00000181404"; transcript_id "BambuTx1"; exon_number "5"; NDR "0.636065870523453"; maxTxScore "0.363934129476547"; maxTxScore.noFit "0.363934129476547"; +9 Bambu exon 17344 17479 . - . gene_id "ENSG00000181404"; transcript_id "ENST00000442898"; exon_number "6"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 17719 17855 . - . gene_id "ENSG00000181404"; transcript_id "BambuTx1"; exon_number "4"; NDR "0.636065870523453"; maxTxScore "0.363934129476547"; maxTxScore.noFit "0.363934129476547"; +9 Bambu exon 17719 17855 . - . gene_id "ENSG00000181404"; transcript_id "ENST00000442898"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 18028 18174 . - . gene_id "ENSG00000181404"; transcript_id "BambuTx1"; exon_number "3"; NDR "0.636065870523453"; maxTxScore "0.363934129476547"; maxTxScore.noFit "0.363934129476547"; +9 Bambu exon 18028 18174 . - . gene_id "ENSG00000181404"; transcript_id "ENST00000442898"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 18381 18482 . - . gene_id "ENSG00000181404"; transcript_id "BambuTx1"; exon_number "2"; NDR "0.636065870523453"; maxTxScore "0.363934129476547"; maxTxScore.noFit "0.363934129476547"; +9 Bambu exon 18381 18492 . - . gene_id "ENSG00000181404"; transcript_id "ENST00000442898"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 19026 19197 . - . gene_id "ENSG00000181404"; transcript_id "BambuTx1"; exon_number "1"; NDR "0.636065870523453"; maxTxScore "0.363934129476547"; maxTxScore.noFit "0.363934129476547"; +9 Bambu exon 24851 25004 . - . gene_id "ENSG00000181404"; transcript_id "ENST00000442898"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 27657 30891 . + . gene_id "ENSG00000227518"; transcript_id "ENST00000422679"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 27657 30445 . + . gene_id "ENSG00000227518"; transcript_id "ENST00000422679"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 29602 29739 . - . gene_id "ENSG00000181404"; transcript_id "ENST00000442898"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 30144 30281 . + . gene_id "ENSG00000283921"; transcript_id "ENST00000408365"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 30144 30281 . + . gene_id "ENSG00000283921"; transcript_id "ENST00000408365"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 30758 30891 . + . gene_id "ENSG00000227518"; transcript_id "ENST00000422679"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 34394 35860 . - . gene_id "ENSG00000218839"; transcript_id "ENST00000449442"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 34394 34957 . - . gene_id "ENSG00000218839"; transcript_id "ENST00000449442"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 34965 35871 . - . gene_id "ENSG00000218839"; transcript_id "ENST00000305248"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 34965 35264 . - . gene_id "ENSG00000218839"; transcript_id "ENST00000305248"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 35060 35264 . - . gene_id "ENSG00000218839"; transcript_id "ENST00000449442"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 35504 35871 . - . gene_id "ENSG00000218839"; transcript_id "ENST00000305248"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 35504 35860 . - . gene_id "ENSG00000218839"; transcript_id "ENST00000449442"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 72674 87667 . + . gene_id "ENSG00000277631"; transcript_id "ENST00000621255"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 72674 72816 . + . gene_id "ENSG00000277631"; transcript_id "ENST00000621255"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 72675 75293 . + . gene_id "ENSG00000277631"; transcript_id "ENST00000620326"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 72675 72816 . + . gene_id "ENSG00000277631"; transcript_id "ENST00000620326"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 72691 88826 . + . gene_id "ENSG00000277631"; transcript_id "ENST00000429980"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 72691 72816 . + . gene_id "ENSG00000277631"; transcript_id "ENST00000429980"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 72705 75327 . + . gene_id "ENSG00000277631"; transcript_id "ENST00000442069"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 72705 72816 . + . gene_id "ENSG00000277631"; transcript_id "ENST00000442069"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 72727 87739 . + . gene_id "ENSG00000277631"; transcript_id "ENST00000613372"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 72727 72816 . + . gene_id "ENSG00000277631"; transcript_id "ENST00000613372"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 74139 87590 . + . gene_id "ENSG00000277631"; transcript_id "ENST00000622412"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 74139 74205 . + . gene_id "ENSG00000277631"; transcript_id "ENST00000622412"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 74149 74205 . + . gene_id "ENSG00000277631"; transcript_id "ENST00000442069"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 74882 75327 . + . gene_id "ENSG00000277631"; transcript_id "ENST00000442069"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 74882 75293 . + . gene_id "ENSG00000277631"; transcript_id "ENST00000620326"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 79345 79537 . + . gene_id "ENSG00000277631"; transcript_id "ENST00000429980"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 79345 79537 . + . gene_id "ENSG00000277631"; transcript_id "ENST00000613372"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 79345 79537 . + . gene_id "ENSG00000277631"; transcript_id "ENST00000621255"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 79345 79537 . + . gene_id "ENSG00000277631"; transcript_id "ENST00000622412"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 80651 80807 . + . gene_id "ENSG00000277631"; transcript_id "ENST00000621255"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 87284 87739 . + . gene_id "ENSG00000277631"; transcript_id "ENST00000613372"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 87284 87667 . + . gene_id "ENSG00000277631"; transcript_id "ENST00000621255"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 87284 87590 . + . gene_id "ENSG00000277631"; transcript_id "ENST00000622412"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 87661 88775 . + . gene_id "ENSG00000277631"; transcript_id "ENST00000614900"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 87661 88195 . + . gene_id "ENSG00000277631"; transcript_id "ENST00000614900"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 88742 88826 . + . gene_id "ENSG00000277631"; transcript_id "ENST00000429980"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 88742 88775 . + . gene_id "ENSG00000277631"; transcript_id "ENST00000614900"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 100804 102850 . - . gene_id "ENSG00000227917"; transcript_id "ENST00000435421"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 100804 101304 . - . gene_id "ENSG00000227917"; transcript_id "ENST00000435421"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 100994 102941 . - . gene_id "ENSG00000227917"; transcript_id "ENST00000427318"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 100994 101304 . - . gene_id "ENSG00000227917"; transcript_id "ENST00000427318"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 102473 102541 . - . gene_id "ENSG00000227917"; transcript_id "ENST00000427318"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 102740 102941 . - . gene_id "ENSG00000227917"; transcript_id "ENST00000427318"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 102740 102850 . - . gene_id "ENSG00000227917"; transcript_id "ENST00000435421"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 112713 113754 . - . gene_id "ENSG00000231808"; transcript_id "ENST00000416242"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 112713 113067 . - . gene_id "ENSG00000231808"; transcript_id "ENST00000416242"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 113694 113754 . - . gene_id "ENSG00000231808"; transcript_id "ENST00000416242"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 116231 118204 . - . gene_id "ENSG00000170122"; transcript_id "ENST00000382500"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 116231 118204 . - . gene_id "ENSG00000170122"; transcript_id "ENST00000382500"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 121038 179058 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000356521"; NDR "0.191389977931976"; txScore ""; txScore.noFit ""; +9 Bambu exon 121038 121573 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000356521"; exon_number "15"; NDR "0.191389977931976"; maxTxScore "0.808610022068024"; maxTxScore.noFit "0.808610022068024"; +9 Bambu transcript 121041 179147 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000377400"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 121041 121573 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000377400"; exon_number "15"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 121052 146140 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000475990"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 121052 123282 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000475990"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 121058 164009 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000619157"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 121058 121573 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000619157"; exon_number "12"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 121060 179047 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000314367"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 121060 121573 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000314367"; exon_number "16"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 121089 149446 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000475411"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu transcript 121089 179012 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000612045"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 121089 122090 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000475411"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 121089 121573 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000612045"; exon_number "16"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 121091 148625 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000611457"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 121091 121573 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000611457"; exon_number "6"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 121224 179042 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000465014"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 121224 121573 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000465014"; exon_number "15"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 121407 179008 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000613508"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 121407 121573 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000613508"; exon_number "13"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 121409 179021 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000382447"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 121409 121573 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000382447"; exon_number "14"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 121410 166599 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000487575"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 121410 121573 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000487575"; exon_number "15"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 121411 123747 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000464198"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 121411 121573 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000464198"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 121418 167605 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000495302"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 121418 121573 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000495302"; exon_number "13"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 121503 146154 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000462513"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 121503 121573 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000462513"; exon_number "6"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 121961 122090 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000314367"; exon_number "15"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 121961 122090 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000356521"; exon_number "14"; NDR "0.191389977931976"; maxTxScore "0.808610022068024"; maxTxScore.noFit "0.808610022068024"; +9 Bambu exon 121961 122090 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000377400"; exon_number "14"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 121961 122090 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000382447"; exon_number "13"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 121961 122136 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000462513"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 121961 122090 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000464198"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 121961 122090 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000465014"; exon_number "14"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 121961 122090 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000487575"; exon_number "14"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 121961 122090 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000495302"; exon_number "12"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 121961 122090 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000611457"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 121961 122090 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000612045"; exon_number "15"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 121961 122090 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000613508"; exon_number "12"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 121961 122090 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000619157"; exon_number "11"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 122691 179052 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000616944"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 122691 123282 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000616944"; exon_number "14"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 122843 179016 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000613355"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 122843 123282 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000613355"; exon_number "13"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 123217 123282 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000314367"; exon_number "14"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 123217 123282 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000356521"; exon_number "13"; NDR "0.191389977931976"; maxTxScore "0.808610022068024"; maxTxScore.noFit "0.808610022068024"; +9 Bambu exon 123217 123282 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000377400"; exon_number "13"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 123217 123282 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000382447"; exon_number "12"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 123217 123282 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000462513"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 123217 123282 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000464198"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 123217 123282 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000465014"; exon_number "13"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 123217 123282 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000475411"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 123217 123282 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000487575"; exon_number "13"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 123217 123282 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000495302"; exon_number "11"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 123217 123282 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000611457"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 123217 123282 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000612045"; exon_number "14"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 123217 123282 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000613508"; exon_number "11"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 123217 123282 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000619157"; exon_number "10"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 123386 123454 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000314367"; exon_number "13"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 123386 123454 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000356521"; exon_number "12"; NDR "0.191389977931976"; maxTxScore "0.808610022068024"; maxTxScore.noFit "0.808610022068024"; +9 Bambu exon 123386 123454 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000377400"; exon_number "12"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 123386 123454 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000382447"; exon_number "11"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 123386 123454 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000462513"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 123386 123747 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000464198"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 123386 123454 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000465014"; exon_number "12"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 123386 123454 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000475411"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 123386 123454 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000475990"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 123386 123454 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000487575"; exon_number "12"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 123386 123454 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000495302"; exon_number "10"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 123386 123454 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000611457"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 123386 123454 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000612045"; exon_number "13"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 123386 123454 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000613355"; exon_number "12"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 123386 123454 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000613508"; exon_number "10"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 123386 123454 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000616944"; exon_number "13"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 123386 123454 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000619157"; exon_number "9"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 134979 135030 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000314367"; exon_number "12"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 134979 135030 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000356521"; exon_number "11"; NDR "0.191389977931976"; maxTxScore "0.808610022068024"; maxTxScore.noFit "0.808610022068024"; +9 Bambu exon 134979 135030 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000377400"; exon_number "11"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 134979 135030 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000382447"; exon_number "10"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 134979 135030 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000462513"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 134979 135030 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000465014"; exon_number "11"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 134979 135030 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000475411"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 134979 135030 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000475990"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 134979 135030 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000487575"; exon_number "11"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 134979 135030 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000495302"; exon_number "9"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 134979 135030 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000611457"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 134979 135030 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000612045"; exon_number "12"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 134979 135030 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000613355"; exon_number "11"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 134979 135030 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000613508"; exon_number "9"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 134979 135030 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000616944"; exon_number "12"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 134979 135030 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000619157"; exon_number "8"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 146102 146158 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000314367"; exon_number "11"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 146102 146158 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000356521"; exon_number "10"; NDR "0.191389977931976"; maxTxScore "0.808610022068024"; maxTxScore.noFit "0.808610022068024"; +9 Bambu exon 146102 146158 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000377400"; exon_number "10"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 146102 146154 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000462513"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 146102 146158 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000465014"; exon_number "10"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 146102 149446 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000475411"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 146102 146140 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000475990"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 146102 146158 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000487575"; exon_number "10"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 146102 146158 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000495302"; exon_number "8"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 146102 148625 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000611457"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 146102 146158 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000612045"; exon_number "11"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 146102 146158 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000616944"; exon_number "11"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 146102 146158 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000619157"; exon_number "7"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 146114 172172 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000498044"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 146114 146158 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000498044"; exon_number "9"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 147901 148040 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000465014"; exon_number "9"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 147950 164039 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000618361"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 147950 148044 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000618361"; exon_number "8"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 150132 164039 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000618061"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 150132 152078 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000618061"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 150509 150725 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000487575"; exon_number "9"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 150642 150725 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000498044"; exon_number "8"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 151305 151427 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000495302"; exon_number "7"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 151305 151427 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000612045"; exon_number "10"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 151305 151427 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000618361"; exon_number "7"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 151577 179088 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000613988"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 151577 152078 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000613988"; exon_number "10"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 151745 161647 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000489272"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 151745 152078 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000489272"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 152034 173325 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000616803"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 152034 152078 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000314367"; exon_number "10"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 152034 152078 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000356521"; exon_number "9"; NDR "0.191389977931976"; maxTxScore "0.808610022068024"; maxTxScore.noFit "0.808610022068024"; +9 Bambu exon 152034 152078 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000377400"; exon_number "9"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 152034 152078 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000382447"; exon_number "9"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 152034 152078 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000465014"; exon_number "8"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 152034 152078 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000487575"; exon_number "8"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 152034 152078 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000495302"; exon_number "6"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 152034 152078 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000498044"; exon_number "7"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 152034 152078 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000612045"; exon_number "9"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 152034 152078 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000613355"; exon_number "10"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 152034 152078 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000613508"; exon_number "8"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 152034 152078 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000616803"; exon_number "8"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 152034 152078 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000616944"; exon_number "10"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 152034 152078 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000618361"; exon_number "6"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 152034 152078 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000619157"; exon_number "6"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 152914 179025 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000377447"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 152914 154795 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000377447"; exon_number "8"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 154709 154795 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000314367"; exon_number "9"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 154709 154795 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000356521"; exon_number "8"; NDR "0.191389977931976"; maxTxScore "0.808610022068024"; maxTxScore.noFit "0.808610022068024"; +9 Bambu exon 154709 154795 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000377400"; exon_number "8"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 154709 154795 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000382447"; exon_number "8"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 154709 154795 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000487575"; exon_number "7"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 154709 154795 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000489272"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 154709 154795 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000495302"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 154709 154795 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000498044"; exon_number "6"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 154709 154795 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000613355"; exon_number "9"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 154709 154795 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000613988"; exon_number "9"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 154709 154795 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000616803"; exon_number "7"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 154709 154795 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000616944"; exon_number "9"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 154709 154795 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000618361"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 154709 154795 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000619157"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 154732 172179 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000620292"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 154732 154795 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000620292"; exon_number "6"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 156481 156527 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000314367"; exon_number "8"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 156481 156527 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000356521"; exon_number "7"; NDR "0.191389977931976"; maxTxScore "0.808610022068024"; maxTxScore.noFit "0.808610022068024"; +9 Bambu exon 156481 156527 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000377400"; exon_number "7"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 156481 156527 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000377447"; exon_number "7"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 156481 156527 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000382447"; exon_number "7"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 156481 156527 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000465014"; exon_number "7"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 156481 156527 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000487575"; exon_number "6"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 156481 156527 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000489272"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 156481 156527 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000495302"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 156481 156527 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000498044"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 156481 156527 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000612045"; exon_number "8"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 156481 156527 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000613355"; exon_number "8"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 156481 156527 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000613508"; exon_number "7"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 156481 156527 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000613988"; exon_number "8"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 156481 156527 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000616803"; exon_number "6"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 156481 156527 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000616944"; exon_number "8"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 156481 156527 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000618061"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 156481 156527 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000618361"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 156481 156527 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000619157"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 156481 156527 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000620292"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 160001 160140 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000487575"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 160001 160140 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000498044"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 160001 160140 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000612045"; exon_number "7"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 160001 160140 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000620292"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 160088 179018 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000431099"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 160088 160140 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000431099"; exon_number "8"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 161567 161654 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000465014"; exon_number "6"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 161567 161654 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000487575"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 161567 161647 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000489272"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 161567 161654 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000612045"; exon_number "6"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 161567 161654 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000616803"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 161567 161654 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000616944"; exon_number "7"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 161567 161654 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000618061"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 161567 161654 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000618361"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 161567 161654 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000619157"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 162432 162469 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000314367"; exon_number "7"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 162432 162469 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000356521"; exon_number "6"; NDR "0.191389977931976"; maxTxScore "0.808610022068024"; maxTxScore.noFit "0.808610022068024"; +9 Bambu exon 162432 162469 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000377400"; exon_number "6"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 162432 162469 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000377447"; exon_number "6"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 162432 162469 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000382447"; exon_number "6"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 162432 162469 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000431099"; exon_number "7"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 162432 162469 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000465014"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 162432 162469 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000487575"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 162432 162469 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000495302"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 162432 162469 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000498044"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 162432 162469 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000612045"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 162432 162469 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000613355"; exon_number "7"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 162432 162469 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000613508"; exon_number "6"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 162432 162469 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000613988"; exon_number "7"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 162432 162469 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000616803"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 162432 162469 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000616944"; exon_number "6"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 162432 162469 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000618061"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 162432 162469 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000618361"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 162432 162469 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000619157"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 162432 162469 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000620292"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 163978 164037 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000314367"; exon_number "6"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 163978 164037 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000356521"; exon_number "5"; NDR "0.191389977931976"; maxTxScore "0.808610022068024"; maxTxScore.noFit "0.808610022068024"; +9 Bambu exon 163978 164037 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000377400"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 163978 164037 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000377447"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 163978 164037 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000382447"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 163978 164037 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000431099"; exon_number "6"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 163978 164037 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000487575"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 163978 164037 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000495302"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 163978 164037 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000498044"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 163978 164037 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000613355"; exon_number "6"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 163978 164037 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000613508"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 163978 164037 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000613988"; exon_number "6"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 163978 164037 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000616944"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 163978 164039 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000618061"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 163978 164039 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000618361"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 163978 164009 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000619157"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 163978 164037 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000620292"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 164403 164448 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000616803"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 165983 166599 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000487575"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 165983 167605 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000495302"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 171596 173371 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000483817"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 171596 172172 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000483817"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 171953 179023 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000382389"; NDR "0.521544337272644"; txScore ""; txScore.noFit ""; +9 Bambu transcript 171953 179045 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000382393"; NDR "0.330390512943268"; txScore ""; txScore.noFit ""; +9 Bambu exon 171953 173366 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000382389"; exon_number "4"; NDR "0.521544337272644"; maxTxScore "0.478455662727356"; maxTxScore.noFit "0.478455662727356"; +9 Bambu exon 171953 173366 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000382393"; exon_number "3"; NDR "0.330390512943268"; maxTxScore "0.669609487056732"; maxTxScore.noFit "0.669609487056732"; +9 Bambu exon 172081 172172 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000314367"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 172081 172172 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000356521"; exon_number "4"; NDR "0.191389977931976"; maxTxScore "0.808610022068024"; maxTxScore.noFit "0.808610022068024"; +9 Bambu exon 172081 172172 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000377400"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 172081 172172 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000377447"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 172081 172172 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000382447"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 172081 172172 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000431099"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 172081 172172 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000465014"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 172081 172172 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000498044"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 172081 172172 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000612045"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 172081 172172 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000613355"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 172081 172172 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000613508"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 172081 172172 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000613988"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 172081 172172 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000616803"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 172081 172172 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000616944"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 172081 172179 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000620292"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 173270 173366 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000314367"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 173270 173366 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000356521"; exon_number "3"; NDR "0.191389977931976"; maxTxScore "0.808610022068024"; maxTxScore.noFit "0.808610022068024"; +9 Bambu exon 173270 173366 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000377400"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 173270 173366 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000377447"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 173270 173366 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000382447"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 173270 173366 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000431099"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 173270 173366 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000465014"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 173270 173371 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000483817"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 173270 173366 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000612045"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 173270 173366 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000613355"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 173270 173366 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000613508"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 173270 173366 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000613988"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 173270 173325 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000616803"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 173270 173366 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000616944"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 175698 175784 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000314367"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 175698 175784 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000356521"; exon_number "2"; NDR "0.191389977931976"; maxTxScore "0.808610022068024"; maxTxScore.noFit "0.808610022068024"; +9 Bambu exon 175698 175784 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000377400"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 175698 175784 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000377447"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 175698 175784 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000382389"; exon_number "3"; NDR "0.521544337272644"; maxTxScore "0.478455662727356"; maxTxScore.noFit "0.478455662727356"; +9 Bambu exon 175698 175784 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000382393"; exon_number "2"; NDR "0.330390512943268"; maxTxScore "0.669609487056732"; maxTxScore.noFit "0.669609487056732"; +9 Bambu exon 175698 175784 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000382447"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 175698 175784 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000431099"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 175698 175784 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000465014"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 175698 175784 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000612045"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 175698 175784 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000613355"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 175698 175784 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000613508"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 175698 175784 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000613988"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 175698 175784 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000616944"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 177723 177820 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000314367"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 177723 177820 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000382389"; exon_number "2"; NDR "0.521544337272644"; maxTxScore "0.478455662727356"; maxTxScore.noFit "0.478455662727356"; +9 Bambu exon 177723 177820 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000431099"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 177723 177820 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000613355"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 177723 177820 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000613988"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 178816 179047 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000314367"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 178816 179058 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000356521"; exon_number "1"; NDR "0.191389977931976"; maxTxScore "0.808610022068024"; maxTxScore.noFit "0.808610022068024"; +9 Bambu exon 178816 179147 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000377400"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 178816 179025 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000377447"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 178816 179023 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000382389"; exon_number "1"; NDR "0.521544337272644"; maxTxScore "0.478455662727356"; maxTxScore.noFit "0.478455662727356"; +9 Bambu exon 178816 179045 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000382393"; exon_number "1"; NDR "0.330390512943268"; maxTxScore "0.669609487056732"; maxTxScore.noFit "0.669609487056732"; +9 Bambu exon 178816 179021 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000382447"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 178816 179018 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000431099"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 178816 179042 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000465014"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 178816 179012 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000612045"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 178816 179016 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000613355"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 178816 179008 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000613508"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 178816 179088 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000613988"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 178816 179052 . - . gene_id "ENSG00000172785"; transcript_id "ENST00000616944"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 212824 215741 . - . gene_id "ENSG00000183784"; transcript_id "ENST00000382387"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 212824 215741 . - . gene_id "ENSG00000183784"; transcript_id "ENST00000382387"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 214854 286636 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469197"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 214854 215029 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469197"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 214865 465259 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu transcript 214865 340620 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000524396"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 214865 215029 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 214865 215029 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000524396"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 214868 340620 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000454469"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 214868 215029 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000454469"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 215171 289579 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000479404"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 215171 215416 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000479404"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 220748 220863 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000524396"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 267966 273002 . - . gene_id "ENSG00000235880"; transcript_id "ENST00000429661"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 267966 268273 . - . gene_id "ENSG00000235880"; transcript_id "ENST00000429661"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 271627 271729 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 271627 271729 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000454469"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 271627 271729 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469197"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 271627 271729 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000479404"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 271627 271729 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000524396"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 272905 273002 . - . gene_id "ENSG00000235880"; transcript_id "ENST00000429661"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 273048 465259 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 273048 273100 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 273050 340620 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382341"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu transcript 273050 304703 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000487230"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 273050 273100 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382341"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 273050 273100 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000487230"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 273059 381387 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000483757"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 273059 273100 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000483757"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 273066 312941 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000478380"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 273066 273100 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000478380"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 273070 464526 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 273070 273100 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 273084 465241 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 273084 273100 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 276994 277086 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469197"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 280791 280905 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000487230"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 284375 284567 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469197"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 286461 286636 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382341"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 286461 286636 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 286461 286636 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 286461 286636 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000454469"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 286461 286636 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469197"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 286461 286636 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 286461 286636 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000478380"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 286461 286636 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000479404"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 286461 286636 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000483757"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 286461 286636 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000487230"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 286461 286636 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 286461 286636 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000524396"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 289510 289581 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382341"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 289510 289581 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 289510 289581 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 289510 289581 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000454469"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 289510 289581 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 289510 289581 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000478380"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 289510 289579 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000479404"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 289510 289581 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000483757"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 289510 289581 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000487230"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 289510 289581 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 289510 289581 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000524396"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 304581 304704 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382341"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 304581 304704 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 304581 304704 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 304581 304704 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000454469"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 304581 304704 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 304581 304704 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000478380"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 304581 304704 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000483757"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 304581 304703 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000487230"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 304581 304704 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 304581 304704 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000524396"; exon_number "6"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 311954 312166 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382341"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 311954 312166 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "6"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 311954 312166 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 311954 312166 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000454469"; exon_number "6"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 311954 312166 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 311954 312941 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000478380"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 311954 312166 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000483757"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 311954 312166 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 311954 312166 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000524396"; exon_number "7"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 311958 314466 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000474772"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 311958 312166 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000474772"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 314292 314466 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000474772"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 317043 317128 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382341"; exon_number "6"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 317043 317128 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "7"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 317043 317128 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "6"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 317043 317128 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000454469"; exon_number "7"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 317043 317128 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "6"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 317043 317128 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000483757"; exon_number "6"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 317043 317128 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "6"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 317043 317128 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000524396"; exon_number "8"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 325671 325737 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382341"; exon_number "7"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 325671 325737 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "8"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 325671 325737 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "7"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 325671 325737 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000454469"; exon_number "8"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 325671 325737 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "7"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 325671 325737 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000483757"; exon_number "7"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 325671 325737 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "7"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 325671 325737 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000524396"; exon_number "9"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 328022 328171 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382341"; exon_number "8"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 328022 328171 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "9"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 328022 328171 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "8"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 328022 328171 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000454469"; exon_number "9"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 328022 328171 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "8"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 328022 328171 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000483757"; exon_number "8"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 328022 328171 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "8"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 328022 328171 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000524396"; exon_number "10"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 332398 332478 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382341"; exon_number "9"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 332398 332478 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "10"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 332398 332478 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "9"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 332398 332478 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000454469"; exon_number "10"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 332398 332478 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "9"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 332398 332478 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000483757"; exon_number "9"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 332398 332478 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "9"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 332398 332478 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000524396"; exon_number "11"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 334225 334384 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382341"; exon_number "10"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 334225 334384 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "11"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 334225 334384 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "10"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 334225 334384 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000454469"; exon_number "11"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 334225 334384 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "10"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 334225 334384 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000483757"; exon_number "10"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 334225 334384 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "10"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 334225 334384 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000524396"; exon_number "12"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 336582 336718 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382341"; exon_number "11"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 336582 336718 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "12"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 336582 336718 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "11"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 336582 336718 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000454469"; exon_number "12"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 336582 336718 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "11"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 336582 336718 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000483757"; exon_number "11"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 336582 336718 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "11"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 336582 336718 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000524396"; exon_number "13"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 339006 339099 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382341"; exon_number "12"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 339006 339099 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "13"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 339006 339099 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "12"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 339006 339099 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000454469"; exon_number "13"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 339006 339099 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "12"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 339006 339099 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000483757"; exon_number "12"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 339006 339099 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "12"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 339006 339099 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000524396"; exon_number "14"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 340159 340620 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382341"; exon_number "13"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 340159 340321 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "14"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 340159 340321 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "13"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 340159 340620 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000454469"; exon_number "14"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 340159 340321 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "13"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 340159 340321 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000483757"; exon_number "13"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 340159 340321 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "13"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 340159 340620 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000524396"; exon_number "15"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 365591 366552 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000483757"; exon_number "14"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 366229 405099 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382331"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 366229 366552 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382331"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 366251 465255 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382329"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 366251 366552 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382329"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 368018 368300 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382329"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 368018 368135 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382331"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 368018 368135 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "15"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 368018 368135 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "14"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 368018 368135 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "14"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 368018 368135 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000483757"; exon_number "15"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 368018 370300 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "14"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 369222 369447 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000483757"; exon_number "16"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 370230 370300 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382329"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 370230 370300 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382331"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 370230 370300 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "16"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 370230 370300 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "15"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 370230 370300 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "15"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 370230 370300 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000483757"; exon_number "17"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 371428 371566 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382329"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 371428 371566 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "17"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 371428 371566 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "16"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 371428 371566 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "16"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 371428 371566 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000483757"; exon_number "18"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 371428 371566 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "15"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 372185 372286 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382329"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 372185 372286 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382331"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 372185 372286 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "18"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 372185 372286 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "17"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 372185 372286 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "17"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 372185 372286 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000483757"; exon_number "19"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 372185 372286 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "16"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 376210 376305 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382329"; exon_number "6"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 376210 376305 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382331"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 376210 376305 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "19"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 376210 376305 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "18"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 376210 376305 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "18"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 376210 376305 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000483757"; exon_number "20"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 376210 376305 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "17"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 376977 377211 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382329"; exon_number "7"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 376977 377211 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382331"; exon_number "6"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 376977 377211 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "20"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 376977 377211 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "19"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 376977 377211 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "19"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 376977 377211 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000483757"; exon_number "21"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 376977 377211 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "18"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 379771 379935 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382329"; exon_number "8"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 379771 379935 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382331"; exon_number "7"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 379771 379935 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "21"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 379771 379935 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "20"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 379771 379935 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "20"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 379771 379935 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000483757"; exon_number "22"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 379771 379935 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "19"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 380279 381387 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000483757"; exon_number "23"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 382513 382685 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382329"; exon_number "9"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 382513 382685 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382331"; exon_number "8"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 382513 382685 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "22"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 382513 382685 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "21"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 382513 382685 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "21"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 382513 382685 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "20"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 386331 386426 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382329"; exon_number "10"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 386331 386426 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382331"; exon_number "9"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 386331 386426 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "23"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 386331 386426 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "22"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 386331 386426 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "21"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 390471 390566 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382329"; exon_number "11"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 390471 390566 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382331"; exon_number "10"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 390471 390566 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "24"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 390471 390566 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "23"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 390471 390566 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "22"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 390471 390566 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "22"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 396785 396934 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382329"; exon_number "12"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 396785 396934 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382331"; exon_number "11"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 396785 396934 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "25"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 396785 396934 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "24"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 396785 396934 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "23"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 396785 396934 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "23"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 399146 399259 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382329"; exon_number "13"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 399146 399259 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382331"; exon_number "12"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 399146 399259 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "26"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 399146 399259 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "25"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 399146 399259 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "24"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 399146 399259 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "24"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 404918 405073 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382329"; exon_number "14"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 404918 405099 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382331"; exon_number "13"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 404918 405073 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "27"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 404918 405073 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "26"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 404918 405073 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "25"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 404918 405073 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "25"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 406930 407069 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382329"; exon_number "15"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 406930 407069 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "28"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 406930 407069 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "27"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 406930 407069 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "26"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 406930 407069 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "26"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 414782 414951 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382329"; exon_number "16"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 414782 414951 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "29"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 414782 414951 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "28"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 414782 414951 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "27"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 414782 414951 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "27"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 418068 418207 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382329"; exon_number "17"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 418068 418207 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "30"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 418068 418207 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "29"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 418068 418207 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "28"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 418068 418207 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "28"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 420116 426953 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000493666"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 420116 420180 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000493666"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 420401 420583 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382329"; exon_number "18"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 420401 420583 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "31"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 420401 420583 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "30"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 420401 420583 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "29"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 420401 420583 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000493666"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 420401 420583 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "29"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 420949 421078 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382329"; exon_number "19"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 420949 421078 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "32"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 420949 421078 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "31"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 420949 421078 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "30"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 420949 421078 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000493666"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 420949 421078 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "30"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 422048 422135 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382329"; exon_number "20"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 422048 422135 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "33"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 422048 422135 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "32"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 422048 422135 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "31"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 422048 422135 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000493666"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 422048 422135 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "31"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 426885 426981 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382329"; exon_number "21"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 426885 426981 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "34"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 426885 426981 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "33"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 426885 426981 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "32"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 426885 426953 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000493666"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 426885 426981 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "32"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 428362 428496 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382329"; exon_number "22"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 428362 428496 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "35"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 428362 428496 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "34"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 428362 428496 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "33"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 428362 428496 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "33"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 429702 429854 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382329"; exon_number "23"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 429702 429854 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "36"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 429702 429854 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "35"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 429702 429854 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "34"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 429702 429854 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "34"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 432166 432324 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382329"; exon_number "24"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 432166 432324 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "37"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 432166 432324 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "36"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 432166 432324 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "35"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 432166 432324 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "35"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 433875 433975 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382329"; exon_number "25"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 433875 433975 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "38"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 433875 433975 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "37"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 433875 433975 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "36"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 433875 433975 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "36"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 434783 434975 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382329"; exon_number "26"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 434783 434975 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "39"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 434783 434975 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "38"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 434783 434975 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "37"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 434783 434975 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "37"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 439245 439388 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382329"; exon_number "27"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 439245 439388 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "40"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 439245 439388 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "39"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 439245 439388 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "38"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 439245 439388 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "38"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 441286 441417 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382329"; exon_number "28"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 441286 441417 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "41"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 441286 441417 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "40"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 441286 441417 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "39"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 441286 441417 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "39"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 441875 442009 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382329"; exon_number "29"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 441875 442009 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "42"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 441875 442009 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "41"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 441875 442009 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "40"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 441875 442009 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "40"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 443427 443516 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382329"; exon_number "30"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 443427 443516 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "43"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 443427 443516 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "42"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 443427 443516 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "41"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 443427 443516 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "41"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 446370 446606 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382329"; exon_number "31"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 446370 446606 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "44"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 446370 446606 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "43"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 446370 446606 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "42"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 446370 446606 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "42"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 449784 449927 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382329"; exon_number "32"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 449784 449927 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "45"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 449784 449927 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "44"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 449784 449927 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "43"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 449784 449927 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "43"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 452011 452117 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382329"; exon_number "33"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 452011 452117 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "46"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 452011 452117 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "45"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 452011 452117 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "44"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 452011 452117 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "44"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 452492 469836 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000591577"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 452492 452948 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000591577"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 452493 456207 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000628764"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 452493 452948 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000628764"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 454304 492248 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000415004"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 454304 454606 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000415004"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 454432 456988 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000585944"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 454432 454606 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000585944"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 454439 454606 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000591577"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 454447 469802 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000589287"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 454447 454606 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000589287"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 454507 454606 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000628764"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 454576 469802 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000589387"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 454576 454606 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000589387"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 454585 470961 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000586805"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 454585 454606 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000586805"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 456201 460507 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000585631"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 456201 456703 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000415004"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 456201 456703 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000585631"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 456201 456988 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000585944"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 456201 456703 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000586805"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 456201 456703 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000589287"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 456201 456703 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000589387"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 456201 456703 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000591577"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 456201 456207 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000628764"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 456204 470816 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000593137"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 456204 456703 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000593137"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 456211 460227 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000590240"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 456211 456703 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000590240"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 456518 467390 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000592805"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 456518 456703 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000592805"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 456521 470934 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000585819"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 456521 456703 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000585819"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 456530 466866 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000588474"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 456530 456703 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000588474"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 456545 467336 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000590518"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 456545 456703 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000590518"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 456915 457047 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000585819"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 456915 457047 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000588474"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 456915 457047 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000590518"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 456915 457047 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000593137"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 457004 467219 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000588989"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 457004 457047 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000588989"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 458117 458281 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000590240"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 458370 458423 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000590240"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 459716 466065 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000608617"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 459716 460507 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000585631"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 459716 459866 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000585819"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 459716 459866 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000588474"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 459716 459866 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000588989"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 459716 460227 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000590240"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 459716 459815 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000608617"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 463517 463687 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382329"; exon_number "34"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 463517 463687 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "47"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 463517 463687 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "46"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 463517 463687 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "45"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 463517 463687 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "45"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 463555 465247 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000462618"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 463555 463687 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000462618"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 464159 465255 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000382329"; exon_number "35"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 464159 465259 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000432829"; exon_number "48"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 464159 465259 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000453981"; exon_number "47"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 464159 464278 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000462618"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 464159 464526 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000469391"; exon_number "46"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 464159 465241 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000495184"; exon_number "46"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 465073 465247 . + . gene_id "ENSG00000107099"; transcript_id "ENST00000462618"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 465962 466069 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000585819"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 465962 466069 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000588474"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 465962 466069 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000588989"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 465962 466069 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000589387"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 465962 466069 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000590518"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 465962 466069 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000591577"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 465962 466069 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000593137"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 465962 466065 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000608617"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 466688 466866 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000588474"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 466688 467219 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000588989"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 466688 466853 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000589287"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 466688 467390 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000592805"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 466900 467336 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000590518"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 469722 469802 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000589287"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 469722 469802 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000589387"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 469722 469836 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000591577"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 470291 746105 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382303"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 470291 470374 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382303"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 470556 470682 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382303"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 470592 484491 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000467541"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 470592 470677 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000467541"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 470765 470934 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000585819"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 470765 470961 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000586805"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 470765 470816 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000593137"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 471449 471586 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000467541"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 471467 476769 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000475690"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 471467 471586 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000475690"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 473194 473273 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382303"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 473194 473273 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000467541"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 473194 473273 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000475690"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 476628 476769 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000475690"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 477750 478423 . + . gene_id "ENSG00000235330"; transcript_id "ENST00000598100"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 477750 478423 . + . gene_id "ENSG00000235330"; transcript_id "ENST00000598100"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 477856 478349 . + . gene_id "ENSG00000235330"; transcript_id "ENST00000455592"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 477856 478349 . + . gene_id "ENSG00000235330"; transcript_id "ENST00000455592"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 484282 484491 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000467541"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 487774 495610 . + . gene_id "ENSG00000228115"; transcript_id "ENST00000442442"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 487774 487803 . + . gene_id "ENSG00000228115"; transcript_id "ENST00000442442"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 488957 489066 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000415004"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 492084 492248 . - . gene_id "ENSG00000227155"; transcript_id "ENST00000415004"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 495238 495610 . + . gene_id "ENSG00000228115"; transcript_id "ENST00000442442"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 504695 746106 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000619269"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 504695 504754 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000619269"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 504702 746103 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000489369"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 504702 504754 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000489369"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 504703 734129 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000354485"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 504703 504754 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000354485"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 504716 746105 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382297"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 504716 504754 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382297"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 539516 539633 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382303"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 540508 540667 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382303"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 547317 549531 . + . gene_id "ENSG00000226403"; transcript_id "ENST00000441028"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 547317 547341 . + . gene_id "ENSG00000226403"; transcript_id "ENST00000441028"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 547318 549531 . + . gene_id "ENSG00000226403"; transcript_id "ENST00000444793"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 547318 547341 . + . gene_id "ENSG00000226403"; transcript_id "ENST00000444793"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 549107 549531 . + . gene_id "ENSG00000226403"; transcript_id "ENST00000444793"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 549107 549721 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000619269"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 549190 549531 . + . gene_id "ENSG00000226403"; transcript_id "ENST00000441028"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 558826 558930 . + . gene_id "ENSG00000202172"; transcript_id "ENST00000365302"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 558826 558930 . + . gene_id "ENSG00000202172"; transcript_id "ENST00000365302"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 659986 660326 . + . gene_id "ENSG00000229875"; transcript_id "ENST00000421436"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 659986 660326 . + . gene_id "ENSG00000229875"; transcript_id "ENST00000421436"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 673478 685555 . - . gene_id "ENSG00000227914"; transcript_id "ENST00000421645"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 673478 674379 . - . gene_id "ENSG00000227914"; transcript_id "ENST00000421645"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 674124 677628 . - . gene_id "ENSG00000227914"; transcript_id "ENST00000608097"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 674124 674379 . - . gene_id "ENSG00000227914"; transcript_id "ENST00000608097"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 676890 677009 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000354485"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 676890 677009 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382297"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 676890 677009 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382303"; exon_number "6"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 676890 677009 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000489369"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 676890 677009 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000619269"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 677542 677628 . - . gene_id "ENSG00000227914"; transcript_id "ENST00000608097"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 680857 681046 . - . gene_id "ENSG00000227914"; transcript_id "ENST00000421645"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 685528 685555 . - . gene_id "ENSG00000227914"; transcript_id "ENST00000421645"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 706889 746103 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382293"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 706889 707247 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382293"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 710804 713464 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000354485"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 710804 713464 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382293"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 710804 713464 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382297"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 710804 713464 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382303"; exon_number "7"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 710804 713464 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000489369"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 710804 713464 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000619269"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 730051 734129 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000354485"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 730051 730248 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382293"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 730051 730248 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382297"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 730051 730248 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382303"; exon_number "8"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 730051 730248 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000489369"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 730051 730248 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000619269"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 731158 731266 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382293"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 731158 731266 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382297"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 731158 731266 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382303"; exon_number "9"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 731158 731266 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000489369"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 731158 731266 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000619269"; exon_number "6"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 732378 732617 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382293"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 732378 732617 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382297"; exon_number "6"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 732378 732617 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382303"; exon_number "10"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 732378 734835 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000489369"; exon_number "6"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 732378 732617 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000619269"; exon_number "7"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 732442 746102 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382289"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 732442 732617 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382289"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 734748 746104 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382286"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 734748 734835 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382286"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 734748 734835 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382289"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 734748 734835 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382293"; exon_number "6"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 734748 734835 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382297"; exon_number "7"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 734748 734835 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382303"; exon_number "11"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 734748 734835 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000619269"; exon_number "8"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 735712 735780 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382289"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 738285 738504 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382286"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 738285 738504 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382289"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 738285 738504 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382293"; exon_number "7"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 738285 738504 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382297"; exon_number "8"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 738285 738504 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382303"; exon_number "12"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 738285 738504 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000489369"; exon_number "7"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 738285 738504 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000619269"; exon_number "9"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 740792 740934 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382286"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 740792 740934 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382289"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 740792 740934 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382293"; exon_number "8"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 740792 740934 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382297"; exon_number "9"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 740792 740934 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382303"; exon_number "13"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 740792 740934 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000489369"; exon_number "8"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 740792 740934 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000619269"; exon_number "10"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 742205 742405 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382286"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 742205 742405 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382289"; exon_number "6"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 742205 742405 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382293"; exon_number "9"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 742205 742405 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382297"; exon_number "10"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 742205 742405 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382303"; exon_number "14"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 742205 742405 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000489369"; exon_number "9"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 742205 742405 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000619269"; exon_number "11"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 744491 746104 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382286"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 744491 744589 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382289"; exon_number "7"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 744491 744589 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382293"; exon_number "10"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 744491 744589 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382297"; exon_number "11"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 744491 744589 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382303"; exon_number "15"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 744491 744589 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000489369"; exon_number "10"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 744491 744589 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000619269"; exon_number "12"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 745173 746102 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382289"; exon_number "8"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 745173 746103 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382293"; exon_number "11"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 745173 746105 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382297"; exon_number "12"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 745173 746105 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000382303"; exon_number "16"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 745173 746103 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000489369"; exon_number "11"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 745173 746106 . + . gene_id "ENSG00000107104"; transcript_id "ENST00000619269"; exon_number "13"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 841690 969090 . + . gene_id "ENSG00000137090"; transcript_id "ENST00000382276"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu transcript 841690 894985 . + . gene_id "ENSG00000137090"; transcript_id "ENST00000564322"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 841690 842192 . + . gene_id "ENSG00000137090"; transcript_id "ENST00000382276"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 841690 842192 . + . gene_id "ENSG00000137090"; transcript_id "ENST00000564322"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 842714 968515 . + . gene_id "ENSG00000137090"; transcript_id "ENST00000569227"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 842714 842954 . + . gene_id "ENSG00000137090"; transcript_id "ENST00000569227"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 846960 847143 . + . gene_id "ENSG00000137090"; transcript_id "ENST00000382276"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 846960 847143 . + . gene_id "ENSG00000137090"; transcript_id "ENST00000564322"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 846960 847143 . + . gene_id "ENSG00000137090"; transcript_id "ENST00000569227"; exon_number "2"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 893912 894195 . + . gene_id "ENSG00000137090"; transcript_id "ENST00000382276"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 893912 894985 . + . gene_id "ENSG00000137090"; transcript_id "ENST00000564322"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 893912 894195 . + . gene_id "ENSG00000137090"; transcript_id "ENST00000569227"; exon_number "3"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 916763 916907 . + . gene_id "ENSG00000137090"; transcript_id "ENST00000382276"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 916763 916907 . + . gene_id "ENSG00000137090"; transcript_id "ENST00000569227"; exon_number "4"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 967985 969090 . + . gene_id "ENSG00000137090"; transcript_id "ENST00000382276"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu exon 967985 968515 . + . gene_id "ENSG00000137090"; transcript_id "ENST00000569227"; exon_number "5"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 976964 991731 . + . gene_id "ENSG00000064218"; transcript_id "ENST00000190165"; NDR "NA"; txScore ""; txScore.noFit ""; +9 Bambu exon 976964 977455 . + . gene_id "ENSG00000064218"; transcript_id "ENST00000190165"; exon_number "1"; NDR "NA"; maxTxScore "NA"; maxTxScore.noFit "NA"; +9 Bambu transcript 989837 990333 . + . gene_id 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a/tests/testthat/test_prepareAnnotations.R b/tests/testthat/test_prepareAnnotations.R index f9c65007..97903eeb 100644 --- a/tests/testthat/test_prepareAnnotations.R +++ b/tests/testthat/test_prepareAnnotations.R @@ -150,6 +150,14 @@ test_that("eqClassById is correct", { expect_true(all(check$validate)) }) +test_that("prepareAnnotations reads in the NDR, txScore and txScore.noFit correctly", { + extendedAnnotationsExpected <- readRDS(system.file("extdata", "extendedAnnotationGranges_txdbGrch38_91_chr9_1_1000000.rds",package = "bambu")) + extendedAnnotations = prepareAnnotations(system.file("extdata", "extendedAnnotationGranges_txdbGrch38_91_chr9_1_1000000.gtf",package = "bambu")) + expect_equal(mcols(extendedAnnotations)$NDR, mcols(extendedAnnotationsExpected)$NDR) + expect_equal(mcols(extendedAnnotations)$txScore, mcols(extendedAnnotationsExpected)$txScore) + expect_equal(mcols(extendedAnnotations)$txScore.noFit, mcols(extendedAnnotationsExpected)$txScore.noFit) +}) + # test_that("eqClass and eqClassById matches", { # gr <- readRDS(test_path("fixtures", "grGTF.rds")) diff --git a/tests/testthat/test_readWrite.R b/tests/testthat/test_readWrite.R index 7223c1fb..84eb0219 100644 --- a/tests/testthat/test_readWrite.R +++ b/tests/testthat/test_readWrite.R @@ -94,3 +94,17 @@ test_that("readGTF can generate a GRangesList from a GTF file", { expect_s4_class(gr, class = "CompressedGRangesList") expect_named(mcols(gr), c("TXNAME", "GENEID")) }) + +test_that("writeToGTF writes the NDR, txScore and txScore.noFit correctly", { + extendedAnnotationsExpected <- readRDS(system.file("extdata", "extendedAnnotationGranges_txdbGrch38_91_chr9_1_1000000.rds",package = "bambu")) + + writeToGTF(extendedAnnotationsExpected, test_path("fixtures", "grGTF.rds")) + + extendedAnnotations = prepareAnnotations(test_path("fixtures", "grGTF.rds")) + + expect_equal(mcols(extendedAnnotations)$NDR, mcols(extendedAnnotationsExpected)$NDR) + expect_equal(mcols(extendedAnnotations)$txScore, mcols(extendedAnnotationsExpected)$txScore) + expect_equal(mcols(extendedAnnotations)$txScore.noFit, mcols(extendedAnnotationsExpected)$txScore.noFit) + + unlink(test_path("fixtures", "*")) +}) From 5be3a63f5e0f20725452280e2a2d77b053d70958 Mon Sep 17 00:00:00 2001 From: Andre Date: Wed, 3 May 2023 13:28:33 +0800 Subject: [PATCH 026/189] Update documentation --- README.md | 85 ++++++++++++++++++++++++++++++++++++++++++++----------- 1 file changed, 69 insertions(+), 16 deletions(-) diff --git a/README.md b/README.md index ae13f235..8fd3468a 100755 --- a/README.md +++ b/README.md @@ -93,11 +93,17 @@ For information on the output and how to export it to a file see [Output](#Outpu #### **Transcript discovery only (no quantification)** If you are only interested in identifying novel transcripts, the quantification module of *bambu* can be skipped by setting quant to FALSE. -Note that the output will be a GRangeslist object containing the reference and novel annotations (See rowRanges() in [Output](#Output)). We recommend running transcript discovery only mode with NDR = 1, and doing filtering in the downstream analysis to allow flexibility in the analysis. See [Modulating the sensitivity of discovery (pre and post analysis)](#Modulating-the-sensitivity-of-discovery-pre-and-post-analysis) +Note that the output will be a GRangeslist object containing the reference and novel annotations (See rowRanges() in [Output](#Output)). For more details on how to adjust the sensitivity and precision of the results see [Modulating the sensitivity of discovery (pre and post analysis)](#Modulating-the-sensitivity-of-discovery-pre-and-post-analysis) ```rscript se.discoveryOnly <- bambu(reads = test.bam, annotations = gtf.file, genome = fa.file, quant = FALSE) ``` +Transcripts that were above the NDR threshold and filtered out (low confidence transcripts) and subset transcripts can be accessed in the metadata of the GRangesList object. + +```rscript +metadata(se.discoveryOnly)$lowConfidenceTranscripts +metadata(se.discoveryOnly)$subsetTranscripts +``` **Quantification of annotated transcripts and genes only (no transcript/gene discovery)** @@ -152,13 +158,30 @@ To manually select an NDR value, use the NDR argument in *bambu*: ```rscript se.NDR_0.3 <- bambu(reads = test.bam, annotations = annotations, genome = fa.file, NDR = 0.3) ``` -Alternatively transcript discovery can be run without thresholds, producing a GRangesList annotation object with all transcripts scored with its NDR score. Note that this means turning quant = FALSE in running *bambu* (refer to [“Transcript discovery only”](#transcript-discovery-only-no-quantification) section). The annotations can be filtered by their NDR score (see example below), read count and gene read proportion between the discovery and quantification steps or used for other types of analysis. +Alternatively the NDR threshold can be adjuted after discovery or on the final output (note that this will only effect the gtf output and for quantification to reflect the adddition or removal of transcripts because of the updated NDR, quantification would need to be rerun). the setNDR function will adjust the novel transcripts included in the output by removing any which are above the new threshold and adding those which are now below the threshold. setNDR takes the annotations as its first argument and the new NDR as the second argument. These annotations must have been generated by Bambu and have stored NDR values for this to work. Additionally setNDR can be run with no NDR, if you would prefer Bambu to recommend a threshold for your dataset. Refer to [“Transcript discovery only”](#transcript-discovery-only-no-quantification) for advanced details using setNDR + +```rscript +# after the discovery step +extendedAnnotations_0.3 = setNDR(se.discoveryOnly, 0.3) +writeToGTF(extendedAnnotations, "./output.gtf") + +# after a complete run +extendedAnnotations_0.3 = setNDR(rowRanges(se), 0.3) +writeToGTF(extendedAnnotations, "./output.gtf") +``` + +To run quantification at a different NDR, simply provide bambu annotations alongside the new NDR threshold to bambu and it will automatically adjust the transcripts. + +```rscript +se.quantOnly <- bambu(reads = test.bam, annotations = extendedAnnotatons genome = fa.file, discovery = FALSE, NDR = 0.5) +``` + +You can check the NDR threshold of your annotations by looking at the stored NDR value. This value is updated upon running setNDR. annotations imported from a gtf file will not have this value until after the first running of setNDR. ```rscript -newAnnotations <- bambu(reads = test.bam, annotations = annotations, genome = fa.file, NDR = 1, quant = FALSE) -annotations.filtered <- newAnnotations[(!is.na(mcols(newAnnotations)$NDR) & mcols(newAnnotations)$NDR<0.1) | is.na(mcols(newAnnotations)$NDR)] -se.NDR_1 <- bambu(reads = test.bam, annotations = annotations.filtered, genome = fa.file, NDR = 1, discovery = FALSE) +print(metadata(extendedAnnotations_0.3)$NDRthreshold) ``` + Additionally there are other thresholds that advanced users can access through opt.discovery when running *bambu* (see arguments). ### Output @@ -167,6 +190,7 @@ Additionally there are other thresholds that advanced users can access through o - **assays(se)** returns a list of transcript abundance estimates as counts or CPM - **rowRanges(se)** returns a GRangesList with all annotated and newly discovered transcripts - **rowData(se)** returns additional information about each transcript +- **metadata(rowRanges(se))** returns a list of transcripts considered low confidience which were not included in the exnteded Annotations. Access transcript expression estimates by extracting a variable (such as counts or CPM) using assays(): @@ -282,7 +306,7 @@ We have found the pretrained model works successfully across species borders (on ### De-novo transcript discovery In cases where the organism does not yet have reference annotations, or unreliable annotations, *bambu* can be run in de-novo mode. In de-novo mode, *bambu* does not train a model, and instead uses the pretrained model to classify novel transcripts (see [Using a pretrained model](#Using-a-pretrained-model). To learn how to train a new model for a more closely related organism/sample see [Training a model on another species/dataset and applying it](#Training-a-model-on-another-speciesdataset-and-applying-it). Without annotations *bambu* is unable to calibrate the NDR output, nor be able to recommend a threshold and will instead use the TPS as the thresholded value. Therefore you should supply a manual NDR threshold ([Modulating the sensitivity of discovery (pre and post analysis)](#Modulating-the-sensitivity-of-discovery-pre-and-post-analysis)) and note that the precision of the output is unlikely to linearly match an applied threshold. -The TPS threshold used is (> 1-NDR). If an NDR is not provided, a default NDR threshold of <0.1 is used (an effective TPS threshold of > 0.9). As in [Modulating the sensitivity of discovery (pre and post analysis)](#Modulating-the-sensitivity-of-discovery-pre-and-post-analysis) an NDR of 1 can be provided to output all possible read classes with their TPS scores +The TPS threshold used is (> 1-NDR). If an NDR is not provided, a default NDR threshold of <0.1 is used (an effective TPS threshold of > 0.9). ```rscript novelAnnotations <- bambu(reads = test.bam, annotations = NULL, genome = fa.file, NDR = 0.5, quant = FALSE) @@ -445,6 +469,16 @@ se <- bambu(reads = sample1.bam, annotations = annotations, genome = fa.file, op | verbose | A logical variable indicating whether processing messages will be printed. | | lowMemory | Reads will be processed by chromosomes instead of all together when lowMemory is specified. This option provides an efficient way to process big samples. | +### setNDR() arguments +|argument|description| +|---|---| +|extendedAnnotations| A GRangesList object produced from bambu(quant = FALSE) or rowRanges(se) or loaded in from prepareAnnotations() of a Bambu dervived .gtf | +|NDR| The maximum NDR for novel transcripts to be in extendedAnnotations (0-1). If not provided a recommended NDR is calculated. | +|includeRef| A boolean which if TRUE will also filter out reference annotations based on their NDR. Note that reference annotations with no NDR (because they were not detected) are not filtered and will remain potentially impacting quantificaiton. Use with caution. Defaults to FALSE. | +|prefix| A string which determines which transcript names are considered novel by bambu and will be filtered. Defaults to 'Bambu') | +|baselineFDR| a value between 0-1. Bambu uses this FDR on the trained model to recommend an equivilent NDR threshold to be used for the sample. By default, a baseline FDR of 0.1 is used. This does not impact the analysis if an NDR is set. Defaults to NULL| +|defaultModels| a bambu trained model object used to recommend an NDR threshold if no NDR is provided. Defaults to the pretrained model in the bambu package| + ### Output Description Access annotations that are matched to the transcript expression estimates by rowRanges() ```rscript @@ -480,25 +514,44 @@ rowData(se) |NDR|The NDR score calculated for the transcript| |relReadCount|The proportion of reads this transcript has relative to all reads assigned to its gene| |relSubsetCount|The proportion of reads this transcript has relative to all reads that either fully or partially match this transcript| +|maxTxScore|The maximum model score across samples from the sample-trained model. Used internally by Bambu to calculate NDR scores| +|maxTxScore.noFit|The maximum model score across samples from the pretrained model. Used internally by Bambu to recommend NDR thresholds| + +```rscript +metadata(se)$incompatibleCounts +metadata(se)$warnings +``` +IncompatibleCounts - A table containing counts for incompatible reads that can be assigned to a gene but to none of the provided transcripts. +warnings - A list containing the warnings produced by each sample + +```rscript +metadata(rowRanges(se))$NDRthreshold +metadata(rowRanges(se))$subsetTranscripts +metadata(rowRanges(se))$lowConfidenceTranscripts +metadata(rowRanges(se))$warnings +``` +NDRthreshold - The NDR threshold currently appled to the novel transcripts. A number between 0 and 1 +subsetTranscripts - A GrangesList containing subset transcripts when remove.subsetTx = TRUE. readCount and txScore can be accessed from mcols. +lowConfidenceTranscripts - A GrangesList containing novel transcripts above the NDR threshold +warnings - A list containing the warnings produced by each sample - ### Release History **bambu version 3.0.0** Release date: 2022-10-25 Major changes: - * Updated the input parameters of Bambu to simplify the user experience - * Introduced NDR threshold recommendation - * Implemented trainBambu(), allowing users to train and use models on their own data - * Reads that cannot be assigned to any transcript are grouped as incompatible counts - * Partial estimates are removed from output as it can be directly obtained based on total count estimates and full-length count estimates - * The fusion mode is now available, which assigns read classes that align to multiple genes to a new combined fusion gene +- Updated the input parameters of Bambu to simplify the user experience +- Introduced NDR threshold recommendation +- Implemented trainBambu(), allowing users to train and use models on their own data +- Reads that cannot be assigned to any transcript are grouped as incompatible counts +- Partial estimates are removed from output as it can be directly obtained based on total count estimates and full-length count estimates +- The fusion mode is now available, which assigns read classes that align to multiple genes to a new combined fusion gene Minor changes: - * Novel transcripts and genes are now by default output with a Bambu prefix - * Updated the documentation, messages and errors output by Bambu - * Annotated transcripts (with unique exon-junctions) with at least 1 full-length read are assigned a NDR rank +- Novel transcripts and genes are now by default output with a Bambu prefix +- Updated the documentation, messages and errors output by Bambu +- Annotated transcripts (with unique exon-junctions) with at least 1 full-length read are assigned a NDR rank **bambu version 1.99.0** From 108e8b914d5f63aff9ad0f889cec46a435a5b094 Mon Sep 17 00:00:00 2001 From: Andre Date: Wed, 3 May 2023 13:41:01 +0800 Subject: [PATCH 027/189] fix setNDR test --- R/bambu-extendAnnotations-utilityExtend.R | 2 +- tests/testthat/test_setNDR.R | 4 ++-- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/R/bambu-extendAnnotations-utilityExtend.R b/R/bambu-extendAnnotations-utilityExtend.R index f90a1b90..a31854a3 100644 --- a/R/bambu-extendAnnotations-utilityExtend.R +++ b/R/bambu-extendAnnotations-utilityExtend.R @@ -848,7 +848,7 @@ setNDR = function(extendedAnnotations, NDR = NULL, includeRef = FALSE, prefix = extendedAnnotations = c(extendedAnnotations[!toRemove], metadata(extendedAnnotations)$lowConfidenceTranscripts[toAdd]) metadata(extendedAnnotations)$lowConfidenceTranscripts = temp - metadata(extendedAnnotations)$NDR = NDR + metadata(extendedAnnotations)$NDRthreshold = NDR return(extendedAnnotations) } \ No newline at end of file diff --git a/tests/testthat/test_setNDR.R b/tests/testthat/test_setNDR.R index 7d4bca53..1c59b7d1 100644 --- a/tests/testthat/test_setNDR.R +++ b/tests/testthat/test_setNDR.R @@ -60,9 +60,9 @@ test_that("setNDR only effects transcripts with the prefix", { test_that("setNDR saves the used NDR threshold correctly", { extendedAnnotationsExpected <- readRDS(system.file("extdata", "extendedAnnotationGranges_txdbGrch38_91_chr9_1_1000000.rds",package = "bambu")) - metadata(extendedAnnotationsExpected)$NDR = 0.7 + #metadata(extendedAnnotationsExpected)$NDR = 0.7 extendedAnnotationsExpected_1 = setNDR(extendedAnnotationsExpected, 1) - metadata(extendedAnnotationsExpected_1)$NDR = 1 + expect_equal(metadata(extendedAnnotationsExpected_1)$NDRthreshold,1) }) test_that("setNDR works when no lowConfidenceTranscripts are present", { From f061a8e4e07c5fc2fa47e57961d01d3da5189be6 Mon Sep 17 00:00:00 2001 From: Andre Date: Tue, 9 May 2023 10:18:42 +0800 Subject: [PATCH 028/189] Bambu now outputs 3 gtf files by default --- R/readWrite.R | 22 ++++++++++++++++++++-- R/transcriptToGeneExpression.R | 12 ++++++------ 2 files changed, 26 insertions(+), 8 deletions(-) diff --git a/R/readWrite.R b/R/readWrite.R index 4f6087d2..f7cfaec0 100644 --- a/R/readWrite.R +++ b/R/readWrite.R @@ -28,7 +28,7 @@ writeBambuOutput <- function(se, path, prefix = "") { transcript_grList <- rowRanges(se) transcript_gtffn <- paste(outdir, prefix, "extended_annotations.gtf", sep = "") - gtf <- writeToGTF(annotation = transcript_grList, + gtf <- writeAnnotatonsToGTF(annotation = transcript_grList, file = transcript_gtffn) for(d in names(assays(se))){ @@ -98,7 +98,7 @@ writeToGTF <- function(annotation, file, geneIDs = NULL) { txScore.noFit = rep(mcols(annotation)$maxTxScore.noFit, unname(elementNROWS(annotation))) df$txScore.noFit <- paste('maxTxScore.noFit "', as.character(txScore.noFit), '";', sep = "") } - if (missing(geneIDs)) { + if (is.null(geneIDs)) { if (!is.null(mcols(annotation, use.names = FALSE)$GENEID)) { geneIDs <- as_tibble(mcols(annotation, use.names = FALSE)[, c("TXNAME", "GENEID")]) @@ -139,6 +139,24 @@ writeToGTF <- function(annotation, file, geneIDs = NULL) { col.names = FALSE, sep = "\t") } +writeAnnotatonsToGTF <- function(annotation, file, geneIDs = NULL, outputExtendedAnno = TRUE, outputAll = TRUE, outputBambuModels = TRUE){ + if(outputExtendedAnno){ + writeToGTF(annotation, paste0(file, "_extendedAnnotations"), geneIDs) + } + if(outputAll){ + annotationAll = setNDR(annotation, 1) + if(length(annotationAll) == length(annotation)) + message("The current NDR threshold already outputs all transcript models. This may result in reduced precision for th extendedAnnotations and supportedTranscriptModels gtfs") + writeToGTF(annotationAll, paste0(file, "_allTranscriptModels"), geneIDs) + } + #todo - have this write bambu start and ends for annotated transcripts + if(outputBambuModels){ + annotationBambu = annotation[!is.na(mcols(annotation)$readCount)] + writeToGTF(annotationBambu, paste0(file, "_supportedTranscriptModels"), geneIDs) + + } +} + #' Outputs GRangesList object from reading a GTF file #' @title convert a GTF file into a GRangesList diff --git a/R/transcriptToGeneExpression.R b/R/transcriptToGeneExpression.R index 9cf7604b..e91efca5 100644 --- a/R/transcriptToGeneExpression.R +++ b/R/transcriptToGeneExpression.R @@ -20,12 +20,12 @@ transcriptToGeneExpression <- function(se) { rowDataSe <- as.data.table(rowData(se)) counts <- rowDataSe[, .(TXNAME, GENEID)][counts, on = "TXNAME"] - incompatibleCounts <- metadata(se)$incompatibleCounts - incompatibleCounts[, TXNAME := "incompatible"] - counts_incompatible <- melt(incompatibleCounts, id.vars = c("GENEID","TXNAME"), - measure.vars = setdiff(colnames(incompatibleCounts), c("GENEID","TXNAME"))) - # GENEID, TXNAME, variable, value - counts <- rbind(counts, counts_incompatible[variable %in% unique(counts$variable)]) + # incompatibleCounts <- metadata(se)$incompatibleCounts + # incompatibleCounts[, TXNAME := "incompatible"] + # counts_incompatible <- melt(incompatibleCounts, id.vars = c("GENEID","TXNAME"), + # measure.vars = setdiff(colnames(incompatibleCounts), c("GENEID","TXNAME"))) + # # GENEID, TXNAME, variable, value + # counts <- rbind(counts, counts_incompatible[variable %in% unique(counts$variable)]) counts[, valueGene := sum(value), by = list(variable, GENEID)] counts[, valueGeneCPM := valueGene / max(sum(value), 1) * 10^6, by = list(variable)] From 601301ab0b244ec89d1456c95294d36af43d3abb Mon Sep 17 00:00:00 2001 From: Andre Date: Tue, 9 May 2023 10:22:07 +0800 Subject: [PATCH 029/189] 4th GTF of novel transcripts only --- R/readWrite.R | 8 +++++++- 1 file changed, 7 insertions(+), 1 deletion(-) diff --git a/R/readWrite.R b/R/readWrite.R index f7cfaec0..1ce54297 100644 --- a/R/readWrite.R +++ b/R/readWrite.R @@ -139,7 +139,8 @@ writeToGTF <- function(annotation, file, geneIDs = NULL) { col.names = FALSE, sep = "\t") } -writeAnnotatonsToGTF <- function(annotation, file, geneIDs = NULL, outputExtendedAnno = TRUE, outputAll = TRUE, outputBambuModels = TRUE){ +writeAnnotatonsToGTF <- function(annotation, file, geneIDs = NULL, outputExtendedAnno = TRUE, + outputAll = TRUE, outputBambuModels = TRUE, outputNovelOnly = TRUE){ if(outputExtendedAnno){ writeToGTF(annotation, paste0(file, "_extendedAnnotations"), geneIDs) } @@ -149,11 +150,16 @@ writeAnnotatonsToGTF <- function(annotation, file, geneIDs = NULL, outputExtende message("The current NDR threshold already outputs all transcript models. This may result in reduced precision for th extendedAnnotations and supportedTranscriptModels gtfs") writeToGTF(annotationAll, paste0(file, "_allTranscriptModels"), geneIDs) } + #todo - have this write bambu start and ends for annotated transcripts if(outputBambuModels){ annotationBambu = annotation[!is.na(mcols(annotation)$readCount)] writeToGTF(annotationBambu, paste0(file, "_supportedTranscriptModels"), geneIDs) + } + if(outputNovelOnly){ + annotationNovel = annotation[mcols(annotation)novelTranscript] + writeToGTF(annotationBambu, paste0(file, "_novelTranscripts"), geneIDs) } } From 49340ba6b17c0f43aca3e19b84cc3fddb372d3c8 Mon Sep 17 00:00:00 2001 From: Andre Date: Tue, 9 May 2023 11:18:08 +0800 Subject: [PATCH 030/189] Include options to ignore GTF outputs --- R/readWrite.R | 28 ++++++++++++++++++++++++++-- 1 file changed, 26 insertions(+), 2 deletions(-) diff --git a/R/readWrite.R b/R/readWrite.R index 1ce54297..bb606ae7 100644 --- a/R/readWrite.R +++ b/R/readWrite.R @@ -16,7 +16,8 @@ #' )) #' path <- tempdir() #' writeBambuOutput(se, path) -writeBambuOutput <- function(se, path, prefix = "") { +writeBambuOutput <- function(se, path, prefix = "", outputExtendedAnno = TRUE, + outputAll = TRUE, outputBambuModels = TRUE, outputNovelOnly = TRUE) { if (missing(se) | missing(path)) { stop("Both summarizedExperiment object from bambu and the path for the output files are required.") @@ -29,7 +30,8 @@ writeBambuOutput <- function(se, path, prefix = "") { transcript_gtffn <- paste(outdir, prefix, "extended_annotations.gtf", sep = "") gtf <- writeAnnotatonsToGTF(annotation = transcript_grList, - file = transcript_gtffn) + file = transcript_gtffn, outputExtendedAnno = TRUE, + outputAll = TRUE, outputBambuModels = TRUE, outputNovelOnly = TRUE) for(d in names(assays(se))){ writeCountsOutput(se, varname=d, @@ -139,6 +141,28 @@ writeToGTF <- function(annotation, file, geneIDs = NULL) { col.names = FALSE, sep = "\t") } +#' Write annotation GRangesList into multiple filtered GTF files +#' @title write GRangeslist into multiple filtered GTF files +#' @param annotation a \code{GRangesList} object +#' @param file the output gtf file name +#' @param geneIDs an optional dataframe of geneIDs (column 2) with +#' the corresponding transcriptIDs (column 1) +#' @param outputExtendedAnno an optional boolean to write the extended annotations as a GTF +#' @param outputAll an optional boolean to write all transcripts (irrespective of confidence) as a GTF +#' @param outputBambuModels an optional boolean to write only full-length read supported models as a GTF +#' @param outputNovelOnly an optional boolean to write only novel high confidence transcripts as a GTF +#' @return gtf a GTF dataframe +#' @importFrom dplyr select as_tibble mutate %>% left_join arrange group_by +#' ungroup recode_factor +#' @importFrom methods is +#' @export +#' @examples +#' outputGtfFile <- tempfile() +#' gr <- readRDS(system.file("extdata", +#' "annotationGranges_txdbGrch38_91_chr9_1_1000000.rds", +#' package = "bambu" +#' )) +#' writeToGTF(gr, outputGtfFile) writeAnnotatonsToGTF <- function(annotation, file, geneIDs = NULL, outputExtendedAnno = TRUE, outputAll = TRUE, outputBambuModels = TRUE, outputNovelOnly = TRUE){ if(outputExtendedAnno){ From 392383751d3f632d2a57ac68f5f5a2ad25196e37 Mon Sep 17 00:00:00 2001 From: Andre Date: Tue, 9 May 2023 11:18:24 +0800 Subject: [PATCH 031/189] Update documentation with writeAnnotationsToGTF --- NAMESPACE | 1 + README.md | 36 ++++++++++++++++-------------------- 2 files changed, 17 insertions(+), 20 deletions(-) diff --git a/NAMESPACE b/NAMESPACE index c360bde7..b908b9de 100755 --- a/NAMESPACE +++ b/NAMESPACE @@ -7,6 +7,7 @@ export(readFromGTF) export(transcriptToGeneExpression) export(writeBambuOutput) export(writeToGTF) +export(writeAnnotationsToGTF) export(trainBambu) export(setNDR) export(compareTranscripts) diff --git a/README.md b/README.md index 8fd3468a..b79f0fdd 100755 --- a/README.md +++ b/README.md @@ -164,11 +164,11 @@ Alternatively the NDR threshold can be adjuted after discovery or on the final o ```rscript # after the discovery step extendedAnnotations_0.3 = setNDR(se.discoveryOnly, 0.3) -writeToGTF(extendedAnnotations, "./output.gtf") +writeAnnotationsToGTF(extendedAnnotations, "./output.gtf") # after a complete run extendedAnnotations_0.3 = setNDR(rowRanges(se), 0.3) -writeToGTF(extendedAnnotations, "./output.gtf") +writeAnnotationsToGTF(extendedAnnotations, "./output.gtf") ``` To run quantification at a different NDR, simply provide bambu annotations alongside the new NDR threshold to bambu and it will automatically adjust the transcripts. @@ -202,41 +202,37 @@ Access transcript expression estimates by extracting a variable (such as counts For a full description of the other outputs see [Output Description](#Output-Description) -The full output can be written to a file using writeBambuOutput(). Using this function will generate three files, including a .gtf file for the extended annotations, and two .txt files for the expression counts at transcript and gene levels. +The full output can be written to a file using writeBambuOutput(). Using this function will generate six files, including 4four .gtf files(detailed below), and two .txt files for the expression counts at transcript and gene levels. + +By default bambu will write four .gtf files +- **extendedAnnotations.gtf** - Contains all transcript models from the reference annotations and any novel high confidence transcript models (below NDR threshold) from Bambu +- **allTranscriptModels** - Contains all transcript models from the reference annotations and all novel transcript models, irrespective of their NDR score. This is useful for reloading into Bambu with prepareAnnotations() to redo the analysis or reoutput the annotations at different NDR thresholds. +- **supportedTranscriptModels** - Contains only transcript models that are fully supported by at least one read across the samples provided. Note that if multiple reference annotations share the same intron junctions, an abitrary one will selected to be be included in this output. +- **novelTranscripts** - Contains only novel high confidence transcript models (below NDR threshold) from Bambu. + ```rscript writeBambuOutput(se, path = "./bambu/") ``` -If you are only interested in the novel transcripts, one can filter this 'se' object first to remove reference annotations. -```rscript -se.novel = se[mcols(se)$novelTranscript,] -writeBambuOutput(se.novel, path = "./bambu/") -``` -If you are only interested in full-length transcripts that were detected by Bambu. +If you would like to avoid outputting any of the above .gtf for space concerns, each can be toggled off with the below arguments. ```rscript -se.novel = se[assays(se)$fullLengthCounts >= 1,] -writeBambuOutput(se.novel, path = "./bambu/") +writeBambuOutput(se.novel, path = "./bambu/", outputExtendedAnno = FALSE, outputAll = FALSE, outputBambuModels = FALSE, outputNovelOnly = FALSE) ``` If quant is set to FALSE i.e. only transcript discovery is performed, only the rowRanges output of the extended annotations is returned (a GRangesList object). The equivalent rowData can be accessed with mcols() -These annotations can be written to a .gtf file using writeToGTF(GRangesList_object, output_path). +These annotations can be written to a .gtf file using writeAnnotatonsToGTF(GRangesList_object, output_path). +This will output the four .gtf files mentioned above, and can be excluded using the same arguments. ```rscript se.discoveryOnly <- bambu(reads = sample, annotations = annotations, genome = fa.file, quant = FALSE) -writeToGTF(se.discoveryOnly, "./output.gtf") +writeAnnotatonsToGTF(se.discoveryOnly, "./output.gtf") ``` -As above, to output only the novel annotations, you need to filter out the reference annotations. +If you would prefer to manually filter the annotations, you can also provide the resulting annotations to writeToGTF() which will output the annotations as is. ```rscript se.discoveryOnly.novel = se.discoveryOnly[mcols(se.discoveryOnly)$novelTranscript,] writeToGTF(se.discoveryOnly.novel, "./output.gtf") ``` -If you are only interested in full-length transcripts that were detected by Bambu. If multiple transcripts share exon-junctions, only one will be displayed. To avoid this, do the filter after quantification as in the example above. -```rscript -se.novel = se[!is.na(mcols(se)$readCount) & mcols(se)$readCount >= 1,] -writeBambuOutput(se.novel, path = "./bambu/") -``` If both quant and discovery are set to FALSE, *bambu* will return an intermediate object see [Storing and using preprocessed files (rcFiles)](#Storing-and-using-preprocessed-files-rcFiles) - ### Visualization You can visualize the novel genes/transcripts using plotBambu function. (Note that the visualization was done by running *bambu* on the three replicates of HepG2 cell line in the SG-NEx project) From 584c81185bd5ee7f6d6969be40516c134d43511d Mon Sep 17 00:00:00 2001 From: Andre Date: Tue, 13 Jun 2023 16:54:46 +0800 Subject: [PATCH 032/189] Fix typo --- R/bambu_utilityFunctions.R | 2 +- R/readWrite.R | 4 ++-- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/R/bambu_utilityFunctions.R b/R/bambu_utilityFunctions.R index be588acf..c04f4781 100644 --- a/R/bambu_utilityFunctions.R +++ b/R/bambu_utilityFunctions.R @@ -187,10 +187,10 @@ handleWarnings <- function(readClassList, verbose){ if (is.character(readClassSe)) readClassSe <- readRDS(file = readClassSe) warnings[[i]] = metadata(readClassSe)$warnings + if(is.null(metadata(readClassSe)$warnings)) warnings[[i]] = NA sampleNames = c(sampleNames, colnames(readClassList[[i]])) } names(warnings) = sampleNames - if(verbose & any(lengths(warnings)>0)){ message("--- per sample warnings during read class construction ---") for(i in seq_along(warnings)){ diff --git a/R/readWrite.R b/R/readWrite.R index bb606ae7..227adeca 100644 --- a/R/readWrite.R +++ b/R/readWrite.R @@ -163,7 +163,7 @@ writeToGTF <- function(annotation, file, geneIDs = NULL) { #' package = "bambu" #' )) #' writeToGTF(gr, outputGtfFile) -writeAnnotatonsToGTF <- function(annotation, file, geneIDs = NULL, outputExtendedAnno = TRUE, +writeAnnotationsToGTF <- function(annotation, file, geneIDs = NULL, outputExtendedAnno = TRUE, outputAll = TRUE, outputBambuModels = TRUE, outputNovelOnly = TRUE){ if(outputExtendedAnno){ writeToGTF(annotation, paste0(file, "_extendedAnnotations"), geneIDs) @@ -182,7 +182,7 @@ writeAnnotatonsToGTF <- function(annotation, file, geneIDs = NULL, outputExtende } if(outputNovelOnly){ - annotationNovel = annotation[mcols(annotation)novelTranscript] + annotationNovel = annotation[mcols(annotation)$novelTranscript] writeToGTF(annotationBambu, paste0(file, "_novelTranscripts"), geneIDs) } } From 3466f7f2b58f377f6523d07281fdf35ba2bb4205 Mon Sep 17 00:00:00 2001 From: Andre Date: Mon, 26 Jun 2023 15:26:36 +0800 Subject: [PATCH 033/189] Fix typo --- R/readWrite.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/R/readWrite.R b/R/readWrite.R index 227adeca..f7c4fc9c 100644 --- a/R/readWrite.R +++ b/R/readWrite.R @@ -29,7 +29,7 @@ writeBambuOutput <- function(se, path, prefix = "", outputExtendedAnno = TRUE, transcript_grList <- rowRanges(se) transcript_gtffn <- paste(outdir, prefix, "extended_annotations.gtf", sep = "") - gtf <- writeAnnotatonsToGTF(annotation = transcript_grList, + gtf <- writeAnnotationsToGTF(annotation = transcript_grList, file = transcript_gtffn, outputExtendedAnno = TRUE, outputAll = TRUE, outputBambuModels = TRUE, outputNovelOnly = TRUE) From 754e5edde5496a5738eb749ac5d71e6c467d0198 Mon Sep 17 00:00:00 2001 From: Andre Date: Mon, 26 Jun 2023 16:03:14 +0800 Subject: [PATCH 034/189] Fix typo --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index b79f0fdd..2cc17cab 100755 --- a/README.md +++ b/README.md @@ -219,11 +219,11 @@ writeBambuOutput(se.novel, path = "./bambu/", outputExtendedAnno = FALSE, output ``` If quant is set to FALSE i.e. only transcript discovery is performed, only the rowRanges output of the extended annotations is returned (a GRangesList object). The equivalent rowData can be accessed with mcols() -These annotations can be written to a .gtf file using writeAnnotatonsToGTF(GRangesList_object, output_path). +These annotations can be written to a .gtf file using writeAnnotationsToGTF(GRangesList_object, output_path). This will output the four .gtf files mentioned above, and can be excluded using the same arguments. ```rscript se.discoveryOnly <- bambu(reads = sample, annotations = annotations, genome = fa.file, quant = FALSE) -writeAnnotatonsToGTF(se.discoveryOnly, "./output.gtf") +writeAnnotationsToGTF(se.discoveryOnly, "./output.gtf") ``` If you would prefer to manually filter the annotations, you can also provide the resulting annotations to writeToGTF() which will output the annotations as is. ```rscript From 897d7355e64b37b77ffc3acda49beefbff2a40c8 Mon Sep 17 00:00:00 2001 From: Andre Date: Mon, 26 Jun 2023 16:03:24 +0800 Subject: [PATCH 035/189] Fix bug when rcOutDir not used --- R/bambu_utilityFunctions.R | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/R/bambu_utilityFunctions.R b/R/bambu_utilityFunctions.R index c04f4781..9e3cca67 100644 --- a/R/bambu_utilityFunctions.R +++ b/R/bambu_utilityFunctions.R @@ -184,11 +184,11 @@ handleWarnings <- function(readClassList, verbose){ sampleNames = c() for(i in seq_along(readClassList)){ readClassSe = readClassList[[i]] - if (is.character(readClassSe)) - readClassSe <- readRDS(file = readClassSe) + if (is.character(readClassSe)) { + readClassSe <- readRDS(file = readClassSe)} warnings[[i]] = metadata(readClassSe)$warnings - if(is.null(metadata(readClassSe)$warnings)) warnings[[i]] = NA - sampleNames = c(sampleNames, colnames(readClassList[[i]])) + if(is.null(metadata(readClassSe)$warnings)) {warnings[[i]] = NA} + sampleNames = c(sampleNames, colnames(readClassSe)) } names(warnings) = sampleNames if(verbose & any(lengths(warnings)>0)){ From 3645daefc7dbc82e40028f78d7bf40b7139f044b Mon Sep 17 00:00:00 2001 From: Andre Date: Mon, 26 Jun 2023 16:25:26 +0800 Subject: [PATCH 036/189] Improve default outs to include counts of rcs and txs --- R/bambu-extendAnnotations-utilityExtend.R | 3 +++ R/bambu-processReads_scoreReadClasses.R | 2 ++ R/bambu.R | 1 + 3 files changed, 6 insertions(+) diff --git a/R/bambu-extendAnnotations-utilityExtend.R b/R/bambu-extendAnnotations-utilityExtend.R index a31854a3..d5bed4a9 100644 --- a/R/bambu-extendAnnotations-utilityExtend.R +++ b/R/bambu-extendAnnotations-utilityExtend.R @@ -43,6 +43,9 @@ isore.extendAnnotations <- function(combinedTranscripts, annotationGrangesList, extendedAnnotationRanges <- filterTranscriptsByAnnotation( rowDataCombined, annotationGrangesList, exonRangesCombined, prefix, remove.subsetTx, min.readFractionByEqClass, baselineFDR, NDR, defaultModels, verbose) + message(paste0("Novel transcripts detected: ", sum(mcols(extendedAnnotationRanges)$novelTranscript))) + message(paste0("Novel genes detected: ", length(unique(mcols(se)$GENEID[mcols(se)$novelGene])))) + message(paste0("Low confidence transcripts excluded: ", length(metadata(extendedAnnotationRanges)$lowConfidenceTranscripts))) return(extendedAnnotationRanges) } else { message("The current filtering criteria filters out all new read diff --git a/R/bambu-processReads_scoreReadClasses.R b/R/bambu-processReads_scoreReadClasses.R index 7a3ab276..1c328cf4 100644 --- a/R/bambu-processReads_scoreReadClasses.R +++ b/R/bambu-processReads_scoreReadClasses.R @@ -7,6 +7,7 @@ scoreReadClasses = function(se, genomeSequence, annotations, defaultModels, fit = TRUE, returnModel = FALSE, min.readCount = 2, min.exonOverlap = 10, fusionMode = FALSE, verbose = FALSE){ + message(paste0("Number of Read Classes - ", nrow(se))) start.ptm <- proc.time() options(scipen = 999) #maintain numeric basepair locations not sci.notfi. geneIds = assignGeneIds(rowRanges(se), annotations, min.exonOverlap, fusionMode) @@ -196,6 +197,7 @@ getTranscriptScore = function(rowData, model = NULL, defaultModels){ #' @return It returns a model object to use in \link{bambu} #' @export trainBambu <- function(rcFile = NULL, min.readCount = 2, nrounds = 50, NDR.threshold = 0.1, verbose = TRUE) { + if(verbose) message(paste0("Read Classes used for training", nrow(rowData))) rowData = rowData(rcFile)[which(rowData(rcFile)$readCount>=min.readCount),] txFeatures = prepareTranscriptModelFeatures(rowData) features = dplyr::select(txFeatures,!c(labels)) diff --git a/R/bambu.R b/R/bambu.R index c7c06206..b7bec995 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -140,6 +140,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, quant = TRUE, stranded = FALSE, ncore = 1, yieldSize = NULL, trackReads = FALSE, returnDistTable = FALSE, lowMemory = FALSE, fusionMode = FALSE, verbose = FALSE) { + message(paste0("Running Bambu-v", "3.2.4")) if(is.null(annotations)) { annotations = GRangesList() } else annotations <- checkInputs(annotations, reads, readClass.outputDir = rcOutDir, genomeSequence = genome) From 0dfda6d0bb16b5b55d23653b74a0e95d0835e0d2 Mon Sep 17 00:00:00 2001 From: Andre Date: Mon, 10 Jul 2023 11:44:37 +0800 Subject: [PATCH 037/189] Ensure eqClasses is recalculated when setting NDR --- R/bambu-extendAnnotations-utilityExtend.R | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/R/bambu-extendAnnotations-utilityExtend.R b/R/bambu-extendAnnotations-utilityExtend.R index d5bed4a9..2821392c 100644 --- a/R/bambu-extendAnnotations-utilityExtend.R +++ b/R/bambu-extendAnnotations-utilityExtend.R @@ -850,6 +850,10 @@ setNDR = function(extendedAnnotations, NDR = NULL, includeRef = FALSE, prefix = temp = c(metadata(extendedAnnotations)$lowConfidenceTranscripts[!toAdd], extendedAnnotations[toRemove]) extendedAnnotations = c(extendedAnnotations[!toRemove], metadata(extendedAnnotations)$lowConfidenceTranscripts[toAdd]) metadata(extendedAnnotations)$lowConfidenceTranscripts = temp + + mcols(extendedAnnotations)$txid <- seq_along(extendedAnnotations) + minEqClasses <- getMinimumEqClassByTx(extendedAnnotations) + mcols(extendedAnnotations)$eqClassById <- minEqClasses$eqClassById metadata(extendedAnnotations)$NDRthreshold = NDR From d062a5b0627b12c081ddbf2ffefbfa6737c7e17f Mon Sep 17 00:00:00 2001 From: Andre Date: Tue, 26 Sep 2023 15:50:42 +0800 Subject: [PATCH 038/189] Use one read class file for multiple samples --- R/bambu-extendAnnotations-utilityExtend.R | 9 +- R/bambu-processReads.R | 95 +++++++++++++++---- ...processReads_utilityConstructReadClasses.R | 25 +++-- R/bambu-quantify.R | 32 ++----- R/bambu.R | 31 +++++- 5 files changed, 134 insertions(+), 58 deletions(-) diff --git a/R/bambu-extendAnnotations-utilityExtend.R b/R/bambu-extendAnnotations-utilityExtend.R index 01310fa9..b675f2c4 100644 --- a/R/bambu-extendAnnotations-utilityExtend.R +++ b/R/bambu-extendAnnotations-utilityExtend.R @@ -686,10 +686,11 @@ isore.estimateDistanceToAnnotations <- function(seReadClass, primarySecondaryDistStartEnd = min.primarySecondaryDistStartEnd, ignore.strand = FALSE) distTable$readCount <- assays(seReadClass)$counts[distTable$readClassId, ] - if (additionalFiltering) - distTable <- left_join(distTable, select(readClassTable, - readClassId, confidenceType), by = "readClassId") %>% - mutate(relativeReadCount = readCount / txNumberFiltered) +# if (additionalFiltering) +# distTable <- left_join(distTable, select(readClassTable, +# readClassId, confidenceType), by = "readClassId") %>% +# mutate(relativeReadCount = readCount / txNumberFiltered) + distTable <- dplyr::select(distTable, annotationTxId, txid, readClassId, readCount, compatible, equal,dist) distTable <- left_join(distTable, as_tibble(mcols(annotationGrangesList)[, c("txid", "GENEID")]), diff --git a/R/bambu-processReads.R b/R/bambu-processReads.R index 31246d35..b6b4dda7 100644 --- a/R/bambu-processReads.R +++ b/R/bambu-processReads.R @@ -44,15 +44,58 @@ bambu.processReads <- function(reads, annotations, genomeSequence, defaultModels = isoreParameters[["defaultModels"]] returnModel = isoreParameters[["returnModel"]] min.exonOverlap = isoreParameters[["min.exonOverlap"]] - readClassList <- bplapply(names(reads), function(bamFileName) { - bambu.processReadsByFile(bam.file = reads[bamFileName], + + readGrgList <- bplapply(seq_along(reads), function(i) { + bambu.processReadsByFile(bam.file = reads[names(reads)[i]], genomeSequence = genomeSequence,annotations = annotations, readClass.outputDir = readClass.outputDir, stranded = stranded, min.readCount = min.readCount, fitReadClassModel = fitReadClassModel, min.exonOverlap = min.exonOverlap, defaultModels = defaultModels, returnModel = returnModel, verbose = verbose, - lowMemory = lowMemory, trackReads = trackReads, fusionMode = fusionMode)}, + lowMemory = lowMemory, trackReads = trackReads, fusionMode = fusionMode, index = i)}, BPPARAM = bpParameters) + readGrgList = do.call(c, readGrgList) + mcols(readGrgList)$id <- seq_along(readGrgList) + + readClassList <- constructReadClasses(readGrgList, genomeSequence = genomeSequence,annotations = annotations, + readClass.outputDir = readClass.outputDir, + stranded = stranded, min.readCount = min.readCount, + fitReadClassModel = fitReadClassModel, min.exonOverlap = min.exonOverlap, + defaultModels = defaultModels, returnModel = returnModel, verbose = verbose, + lowMemory = lowMemory, trackReads = trackReads, fusionMode = fusionMode) + + metadata(readClassList)$samples = names(reads) + countMatrix = splitReadClassFiles(readClassList) + colnames(countMatrix) = metadata(readClassList)$samples + rownames(countMatrix) = rownames(readClassList) + metadata(readClassList)$countMatrix = countMatrix + + # TODO return output + # if (!is.null(readClass.outputDir)) { + # readClassFile <- paste0(readClass.outputDir,names(bam.file), + # "_readClassSe.rds") + # if (file.exists(readClassFile)) { + # show(paste(readClassFile, "exists, will be overwritten")) + # warning(readClassFile, "exists, will be overwritten") + # } else { + # readClassFile <- BiocFileCache::bfcnew(BiocFileCache::BiocFileCache( + # readClass.outputDir, ask = FALSE), + # paste0(names(bam.file),"_readClassSe"), ext = ".rds") + # } + # saveRDS(se, file = readClassFile) + # se <- readClassFile + # } + + + # readClassList <- bplapply(names(reads), function(bamFileName) { + # bambu.processReadsByFile(bam.file = reads[bamFileName], + # genomeSequence = genomeSequence,annotations = annotations, + # readClass.outputDir = readClass.outputDir, + # stranded = stranded, min.readCount = min.readCount, + # fitReadClassModel = fitReadClassModel, min.exonOverlap = min.exonOverlap, + # defaultModels = defaultModels, returnModel = returnModel, verbose = verbose, + # lowMemory = lowMemory, trackReads = trackReads, fusionMode = fusionMode)}, + # BPPARAM = bpParameters) return(readClassList) } @@ -63,7 +106,7 @@ bambu.processReads <- function(reads, annotations, genomeSequence, bambu.processReadsByFile <- function(bam.file, genomeSequence, annotations, readClass.outputDir = NULL, stranded = FALSE, min.readCount = 2, fitReadClassModel = TRUE, min.exonOverlap = 10, defaultModels = NULL, returnModel = FALSE, - verbose = FALSE, lowMemory = FALSE, trackReads = FALSE, fusionMode = FALSE) { + verbose = FALSE, lowMemory = FALSE, trackReads = FALSE, fusionMode = FALSE, index = 0) { if(verbose) message(names(bam.file)[1]) readGrgList <- prepareDataFromBam(bam.file[[1]], verbose = verbose, use.names = trackReads) warnings = c() @@ -92,6 +135,7 @@ bambu.processReadsByFile <- function(bam.file, genomeSequence, annotations, # reassign Ids after seqlevels are dropped mcols(readGrgList)$id <- seq_along(readGrgList) } + mcols(readGrgList)$sampleID = index #removes reads that are outside genome coordinates badReads = which(max(end(ranges(readGrgList)))>= seqlengths(genomeSequence)[as.character(getChrFromGrList(readGrgList))]) @@ -106,6 +150,15 @@ bambu.processReadsByFile <- function(bam.file, genomeSequence, annotations, if(length(readGrgList) == 0) { stop("No reads left after filtering.") } + + return(readGrgList) +} + +constructReadClasses <- function(readGrgList, genomeSequence, annotations, + readClass.outputDir = NULL, stranded = FALSE, min.readCount = 2, + fitReadClassModel = TRUE, min.exonOverlap = 10, defaultModels = NULL, returnModel = FALSE, + verbose = FALSE, lowMemory = FALSE, trackReads = FALSE, fusionMode = FALSE){ + warnings = c() ###TODO # construct read classes for each chromosome seperately if(lowMemory) se <- lowMemoryConstructReadClasses(readGrgList, genomeSequence, annotations, stranded, verbose,bam.file) @@ -123,15 +176,17 @@ bambu.processReadsByFile <- function(bam.file, genomeSequence, annotations, annotations,genomeSequence, stranded = stranded, verbose = verbose) # create SE object with reconstructed readClasses se <- isore.constructReadClasses(readGrgList, unlisted_junctions, - uniqueJunctions, runName = names(bam.file)[1], + uniqueJunctions, runName = "TODO", annotations, stranded, verbose) } + metadata(se)$warnings = warnings if(trackReads){ metadata(se)$readNames = names(readGrgList) metadata(se)$readId = mcols(readGrgList)$id } rm(readGrgList) + refSeqLevels <- seqlevels(genomeSequence) GenomeInfoDb::seqlevels(se) <- refSeqLevels # create SE object with reconstructed readClasses se <- scoreReadClasses(se,genomeSequence, annotations, @@ -142,20 +197,6 @@ bambu.processReadsByFile <- function(bam.file, genomeSequence, annotations, min.exonOverlap = min.exonOverlap, fusionMode = fusionMode, verbose = verbose) - if (!is.null(readClass.outputDir)) { - readClassFile <- paste0(readClass.outputDir,names(bam.file), - "_readClassSe.rds") - if (file.exists(readClassFile)) { - show(paste(readClassFile, "exists, will be overwritten")) - warning(readClassFile, "exists, will be overwritten") - } else { - readClassFile <- BiocFileCache::bfcnew(BiocFileCache::BiocFileCache( - readClass.outputDir, ask = FALSE), - paste0(names(bam.file),"_readClassSe"), ext = ".rds") - } - saveRDS(se, file = readClassFile) - se <- readClassFile - } return(se) } @@ -194,4 +235,20 @@ seqlevelCheckReadsAnnotation <- function(reads, annotations){ "annotations might be incomplete. Please compare objects ", "on the same reference")) return(warnings) +} + +splitReadClassFiles = function(readClassFile){ + rowIndex = c() + sampleCount = c() + counts = c() + for(i in seq_along(metadata(readClassFile)$samples)){ + counts.sample = sapply(rowData(readClassFile)$sampleIDs, FUN = function(x){sum(x==i)}) + counts = c(counts, counts.sample[counts.sample != 0]) + rowIndex = c(rowIndex, which(counts.sample != 0)) + sampleCount = c(sampleCount, sum(counts.sample !=0)) + } + counts = sparseMatrix(i = rowIndex, + j = rep(seq_along(metadata(readClassFile)$samples), sampleCount), + x = counts) + return(counts) } \ No newline at end of file diff --git a/R/bambu-processReads_utilityConstructReadClasses.R b/R/bambu-processReads_utilityConstructReadClasses.R index 4858798b..0d3e0b07 100644 --- a/R/bambu-processReads_utilityConstructReadClasses.R +++ b/R/bambu-processReads_utilityConstructReadClasses.R @@ -16,6 +16,8 @@ isore.constructReadClasses <- function(readGrgList, unlisted_junctions, use.names = FALSE) mcols(reads.singleExon)$id <- mcols(readGrgList[ elementNROWS(readGrgList) == 1])$id + mcols(reads.singleExon)$sampleID <- mcols(readGrgList[ + elementNROWS(readGrgList) == 1])$sampleID #only keep multi exons reads in readGrgList readGrgList <- readGrgList[elementNROWS(readGrgList) > 1] if (!identical(mcols(readGrgList)$id,unique(mcols(unlisted_junctions)$id))) @@ -94,7 +96,7 @@ constructSplicedReadClasses <- function(uniqueJunctions, unlisted_junctions, readTable <- readTable %>% dplyr::select(chr.rc = chr, strand.rc = strand, startSD = startSD, endSD = endSD, readCount.posStrand = readCount.posStrand, intronStarts, intronEnds, - confidenceType, readCount, readIds) + confidenceType, readCount, readIds, sampleIDs) mcols(exonsByReadClass) <- readTable options(scipen = 0) return(exonsByReadClass) @@ -176,7 +178,8 @@ createReadTable <- function(unlisted_junctions_start, unlisted_junctions_end, end = pmax(end(readRanges), intronEndCoordinatesInt), strand = readStrand, confidenceType = readConfidence, alignmentStrand = as.character(getStrandFromGrList(readGrgList))=='+', - readId = mcols(readGrgList)$id) + readId = mcols(readGrgList)$id, + sampleID = mcols(readGrgList)$sampleID) rm(readRanges, readStrand, unlisted_junctions_start, unlisted_junctions_end, unlisted_junctions_id, readConfidence, intronStartCoordinatesInt, intronEndCoordinatesInt) @@ -186,7 +189,8 @@ createReadTable <- function(unlisted_junctions_start, unlisted_junctions_end, summarise(readCount = n(), startSD = sd(start), endSD = sd(end), start = nth(x = start, n = ceiling(readCount / 5), order_by = start), end = nth(x = end, n = ceiling(readCount / 1.25), order_by = end), - readCount.posStrand = sum(alignmentStrand, na.rm = TRUE), readIds = list(readId), + readCount.posStrand = sum(alignmentStrand, na.rm = TRUE), + readIds = list(readId), sampleIDs = list(sampleID), .groups = 'drop') %>% arrange(chr, start, end) %>% mutate(readClassId = paste("rc", row_number(), sep = ".")) @@ -244,13 +248,15 @@ constructUnsplicedReadClasses <- function(reads.singleExon, annotations, # by their minimum read class coordinates #remove duplicate ranges counts = as.data.frame(reads.singleExon) %>% - mutate(id = mcols(reads.singleExon)$id) %>% + mutate(id = mcols(reads.singleExon)$id, + sampleID = mcols(reads.singleExon)$sampleID) %>% group_by(seqnames,start,end,strand) %>% - summarise(n=n(), id = list(id)) %>% + summarise(n=n(), id = list(id), sampleID = list(sampleID)) %>% as.data.frame() reads.singleExon = unique(reads.singleExon) mcols(reads.singleExon)$counts <- counts$n mcols(reads.singleExon)$id <- counts$id + mcols(reads.singleExon)$sampleID <- counts$sampleID rcUnsplicedAnnotation <- getUnsplicedReadClassByReference( granges = reads.singleExon, grangesReference = referenceExons, @@ -309,17 +315,18 @@ getUnsplicedReadClassByReference <- function(granges, grangesReference, readStart = start(granges)[queryHits], readEnd = end(granges)[queryHits], counts = mcols(granges)$counts[queryHits], - readId = mcols(granges[queryHits])$id) + readId = mcols(granges[queryHits])$id, + sampleID = mcols(granges[queryHits])$sampleID) hitsDF <- hitsDF %>% dplyr::select(chr, start, end, readStart, readEnd, strand, readClassId, alignmentStrand, - counts, readId) %>% + counts, readId, sampleID) %>% group_by(readClassId) %>% summarise(start = start[1], end = end[1], strand = strand[1], chr = chr[1], readCount = sum(counts), startSD = sd(rep(readStart,counts)), endSD = sd(rep(readEnd,counts)), readCount.posStrand = sum(rep(alignmentStrand,counts)), - readIds = list(unlist(readId))) %>% + readIds = list(unlist(readId)), sampleIDs = list(unlist(sampleID))) %>% mutate(confidenceType = confidenceType, intronStarts = NA, intronEnds = NA) if(nrow(hitsDF)==0){ @@ -338,7 +345,7 @@ getUnsplicedReadClassByReference <- function(granges, grangesReference, hitsDF <- dplyr::select(hitsDF, chr.rc = chr, strand.rc = strand, intronStarts, intronEnds, confidenceType, readCount, startSD, endSD, - readCount.posStrand, readIds) + readCount.posStrand, readIds, sampleIDs) mcols(exByReadClassUnspliced) <- hitsDF return(exByReadClassUnspliced) } diff --git a/R/bambu-quantify.R b/R/bambu-quantify.R index fa5a079d..3b10eabf 100644 --- a/R/bambu-quantify.R +++ b/R/bambu-quantify.R @@ -2,31 +2,22 @@ #' @inheritParams bambu #' @import data.table #' @noRd -bambu.quantify <- function(readClass, annotations, emParameters, +bambu.quantify <- function(i, readClassDist, countMatrix, annotations, emParameters, trackReads = FALSE, returnDistTable = FALSE, verbose = FALSE, isoreParameters = setIsoreParameters(NULL)) { - min.exonDistance = isoreParameters[["min.exonDistance"]] - min.primarySecondaryDist = - isoreParameters[['min.primarySecondaryDist']] - min.primarySecondaryDistStartEnd = - isoreParameters[['min.primarySecondaryDistStartEnd2']] - if (is.character(readClass)) readClass <- readRDS(file = readClass) - readClassDist <- isore.estimateDistanceToAnnotations(readClass, annotations, - min.exonDistance = min.exonDistance, - min.primarySecondaryDist = min.primarySecondaryDist, - min.primarySecondaryDistStartEnd = min.primarySecondaryDistStartEnd, - verbose = verbose) - metadata(readClassDist)$distTable <- modifyIncompatibleAssignment(metadata(readClassDist)$distTable) - incompatibleCounts <- processIncompatibleCounts(readClassDist) + + metadata(readClassDist)$distTable$readCount <- countMatrix[,i] + #distTable$readCount <- assays(seReadClass)$counts readClassDt <- genEquiRCs(readClassDist, annotations, verbose) + incompatibleCounts <- processIncompatibleCounts(readClassDist) compatibleCounts <- bambu.quantDT(readClassDt, emParameters = emParameters,verbose = verbose) incompatibleCounts <- incompatibleCounts[data.table(GENEID = unique(mcols(annotations)$GENEID)), on = "GENEID"] incompatibleCounts[is.na(counts), counts := 0] compatibleCounts <- calculateCPM(compatibleCounts, incompatibleCounts) - setnames(incompatibleCounts, "counts", colnames(readClass)) + setnames(incompatibleCounts, "counts", colnames(countMatrix)[i]) counts <- compatibleCounts[match(mcols(annotations)$txid, txid)] - colNameRC <- colnames(readClass) - colDataRC <- colData(readClass) + colNameRC <- colnames(countMatrix)[i] + colDataRC <- NULL # TODO carry over coldata??!! sig.digit <- emParameters[["sig.digit"]] seOutput <- SummarizedExperiment( assays = SimpleList(counts = matrix(round(counts$counts,sig.digit), ncol = 1, @@ -35,12 +26,9 @@ bambu.quantify <- function(readClass, annotations, emParameters, fullLengthCounts = matrix(round(counts$fullLengthCounts,sig.digit), ncol = 1, dimnames = list(NULL, colNameRC)), uniqueCounts = matrix(counts$uniqueCounts, - ncol = 1, dimnames = list(NULL, colNameRC))), colData = colDataRC) + ncol = 1, dimnames = list(NULL, colNameRC)))) metadata(seOutput)$incompatibleCounts = incompatibleCounts - if (returnDistTable) metadata(seOutput)$distTable = metadata(readClassDist)$distTable - if (trackReads) metadata(seOutput)$readToTranscriptMap = - generateReadToTranscriptMap(readClass, metadata(readClassDist)$distTable, - annotations) + return(seOutput) } diff --git a/R/bambu.R b/R/bambu.R index e61d0bfa..12b4a2e6 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -171,11 +171,11 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, isoreParameters, trackReads = trackReads, fusionMode = fusionMode, lowMemory = lowMemory) } - warnings = handleWarnings(readClassList, verbose) + #warnings = handleWarnings(readClassList, verbose) if (!discovery & !quant) return(readClassList) if (discovery) { message("--- Start extending annotations ---") - annotations <- bambu.extendAnnotations(readClassList, annotations, NDR, + annotations <- bambu.extendAnnotations(list(readClassList), annotations, NDR, isoreParameters, stranded, bpParameters, fusionMode, verbose) metadata(annotations)$warnings = warnings if (!quant) return(annotations) @@ -184,7 +184,30 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, message("--- Start isoform quantification ---") if(length(annotations)==0) stop("No valid annotations, if running de novo please try less stringent parameters") - countsSe <- bplapply(readClassList, bambu.quantify, + + #Do distTable calculation once on all read classes + min.exonDistance = isoreParameters[["min.exonDistance"]] + min.primarySecondaryDist = + isoreParameters[['min.primarySecondaryDist']] + min.primarySecondaryDistStartEnd = + isoreParameters[['min.primarySecondaryDistStartEnd2']] + if (is.character(readClassList)) readClassList <- readRDS(file = readClassList) + readClassDist <- isore.estimateDistanceToAnnotations(readClassList, annotations, + min.exonDistance = min.exonDistance, + min.primarySecondaryDist = min.primarySecondaryDist, + min.primarySecondaryDistStartEnd = min.primarySecondaryDistStartEnd, + verbose = verbose) + metadata(readClassDist)$distTable <- modifyIncompatibleAssignment(metadata(readClassDist)$distTable) + #metadata(readClassDist)$distTable <- genEquiRCsBasedOnObservedReads(readClassDist) + # if (trackReads) metadata(seOutput)$readToTranscriptMap = + # generateReadToTranscriptMap(readClass, metadata(readClassDist)$distTable, + # annotations) + # if (returnDistTable) metadata(seOutput)$distTable = metadata(readClassDist)$distTable + + #### + countMatrix2 = metadata(readClassList)$countMatrix[metadata(readClassDist)$distTable$readClassId,] + countsSe <- bplapply(seq_len(ncol(countMatrix2)), bambu.quantify, + readClassDist = readClassDist, countMatrix = countMatrix2, annotations = annotations, isoreParameters = isoreParameters, emParameters = emParameters, trackReads = trackReads, returnDistTable = returnDistTable, verbose = verbose, @@ -196,4 +219,4 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, message("--- Finished running Bambu ---") return(countsSe) } -} \ No newline at end of file +} From b54693eabb024ed8b73126e23f5cd0e157143255 Mon Sep 17 00:00:00 2001 From: Andre Date: Tue, 26 Sep 2023 17:00:35 +0800 Subject: [PATCH 039/189] quick fix hack to enable readGrgList as input --- R/bambu-processReads.R | 60 ++++++++++++++++++++++++------------------ R/bambu.R | 7 ++--- 2 files changed, 38 insertions(+), 29 deletions(-) diff --git a/R/bambu-processReads.R b/R/bambu-processReads.R index b6b4dda7..736f7dd4 100644 --- a/R/bambu-processReads.R +++ b/R/bambu-processReads.R @@ -15,44 +15,46 @@ bambu.processReads <- function(reads, annotations, genomeSequence, readClass.outputDir=NULL, yieldSize=1000000, bpParameters, stranded=FALSE, verbose=FALSE, isoreParameters = setIsoreParameters(NULL), - lowMemory=FALSE, trackReads = trackReads, fusionMode = fusionMode) { + lowMemory=FALSE, trackReads = trackReads, fusionMode = fusionMode, rgrLists = FALSE) { genomeSequence <- checkInputSequence(genomeSequence) + if(rgrLists == FALSE){ # ===# create BamFileList object from character #===# - if (is(reads, "BamFile")) { - if (!is.null(yieldSize)) { - yieldSize(reads) <- yieldSize + if (is(reads, "BamFile")) { + if (!is.null(yieldSize)) { + yieldSize(reads) <- yieldSize + } else { + yieldSize <- yieldSize(reads) + } + reads <- BamFileList(reads) + names(reads) <- tools::file_path_sans_ext(BiocGenerics::basename(reads)) + } else if (is(reads, "BamFileList")) { + if (!is.null(yieldSize)) { + yieldSize(reads) <- yieldSize + } else { + yieldSize <- min(yieldSize(reads)) + } + } else if (any(!grepl("\\.bam$", reads))) { + stop("Bam file is missing from arguments.") } else { - yieldSize <- yieldSize(reads) + if (is.null(yieldSize)) yieldSize <- NA + reads <- BamFileList(reads, yieldSize = yieldSize) + names(reads) <- tools::file_path_sans_ext(BiocGenerics::basename(reads)) } - reads <- BamFileList(reads) - names(reads) <- tools::file_path_sans_ext(BiocGenerics::basename(reads)) - } else if (is(reads, "BamFileList")) { - if (!is.null(yieldSize)) { - yieldSize(reads) <- yieldSize - } else { - yieldSize <- min(yieldSize(reads)) - } - } else if (any(!grepl("\\.bam$", reads))) { - stop("Bam file is missing from arguments.") - } else { - if (is.null(yieldSize)) yieldSize <- NA - reads <- BamFileList(reads, yieldSize = yieldSize) - names(reads) <- tools::file_path_sans_ext(BiocGenerics::basename(reads)) } min.readCount = isoreParameters[["min.readCount"]] fitReadClassModel = isoreParameters[["fitReadClassModel"]] defaultModels = isoreParameters[["defaultModels"]] returnModel = isoreParameters[["returnModel"]] min.exonOverlap = isoreParameters[["min.exonOverlap"]] - + readGrgList <- bplapply(seq_along(reads), function(i) { - bambu.processReadsByFile(bam.file = reads[names(reads)[i]], + bambu.processReadsByFile(bam.file = reads[i], genomeSequence = genomeSequence,annotations = annotations, readClass.outputDir = readClass.outputDir, stranded = stranded, min.readCount = min.readCount, fitReadClassModel = fitReadClassModel, min.exonOverlap = min.exonOverlap, defaultModels = defaultModels, returnModel = returnModel, verbose = verbose, - lowMemory = lowMemory, trackReads = trackReads, fusionMode = fusionMode, index = i)}, + lowMemory = lowMemory, trackReads = trackReads, fusionMode = fusionMode, index = i, rgrLists = rgrLists)}, BPPARAM = bpParameters) readGrgList = do.call(c, readGrgList) mcols(readGrgList)$id <- seq_along(readGrgList) @@ -64,7 +66,7 @@ bambu.processReads <- function(reads, annotations, genomeSequence, defaultModels = defaultModels, returnModel = returnModel, verbose = verbose, lowMemory = lowMemory, trackReads = trackReads, fusionMode = fusionMode) - metadata(readClassList)$samples = names(reads) + metadata(readClassList)$samples = reads countMatrix = splitReadClassFiles(readClassList) colnames(countMatrix) = metadata(readClassList)$samples rownames(countMatrix) = rownames(readClassList) @@ -106,9 +108,15 @@ bambu.processReads <- function(reads, annotations, genomeSequence, bambu.processReadsByFile <- function(bam.file, genomeSequence, annotations, readClass.outputDir = NULL, stranded = FALSE, min.readCount = 2, fitReadClassModel = TRUE, min.exonOverlap = 10, defaultModels = NULL, returnModel = FALSE, - verbose = FALSE, lowMemory = FALSE, trackReads = FALSE, fusionMode = FALSE, index = 0) { - if(verbose) message(names(bam.file)[1]) - readGrgList <- prepareDataFromBam(bam.file[[1]], verbose = verbose, use.names = trackReads) + verbose = FALSE, lowMemory = FALSE, trackReads = FALSE, fusionMode = FALSE, index = 0, rgrLists = FALSE) { + #if(verbose) message(names(bam.file)[1]) + if(rgrLists){ + print(bam.file) + readGrgList <- readRDS(bam.file) + } else{ + readGrgList <- prepareDataFromBam(bam.file[[1]], verbose = verbose, use.names = trackReads) + } + warnings = c() warnings = seqlevelCheckReadsAnnotation(readGrgList, annotations) if(verbose & length(warnings) > 0) warning(paste(warnings,collapse = "\n")) diff --git a/R/bambu.R b/R/bambu.R index 12b4a2e6..3b8a9cde 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -139,7 +139,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, opt.discovery = NULL, opt.em = NULL, rcOutDir = NULL, discovery = TRUE, quant = TRUE, stranded = FALSE, ncore = 1, yieldSize = NULL, trackReads = FALSE, returnDistTable = FALSE, lowMemory = FALSE, - fusionMode = FALSE, verbose = FALSE) { + fusionMode = FALSE, verbose = FALSE, rgrLists = FALSE) { if(is.null(annotations)) { annotations = GRangesList() } else annotations <- checkInputs(annotations, reads, readClass.outputDir = rcOutDir, genomeSequence = genome) @@ -155,7 +155,8 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, isRDSs = all(sapply(reads, class)=="RangedSummarizedExperiment") isBamFiles = !isRDSs if(!isRDSs) isBamFiles = ifelse(!is(reads, "BamFileList"), all(grepl(".bam$", reads)), FALSE) - if (isBamFiles | is(reads, "BamFileList")) { + if(TRUE){ + #if (isBamFiles | is(reads, "BamFileList")) { if (length(reads) > 10 & (is.null(rcOutDir))) { rcOutDir <- tempdir() #>=10 samples, save to temp folder message("There are more than 10 samples, read class files @@ -169,7 +170,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, readClass.outputDir = rcOutDir, yieldSize, bpParameters, stranded, verbose, isoreParameters, trackReads = trackReads, fusionMode = fusionMode, - lowMemory = lowMemory) + lowMemory = lowMemory, rgrLists = rgrLists) } #warnings = handleWarnings(readClassList, verbose) if (!discovery & !quant) return(readClassList) From 699034a39c8174b6369de7765a020606beff2570 Mon Sep 17 00:00:00 2001 From: Andre Date: Thu, 28 Sep 2023 09:54:00 +0800 Subject: [PATCH 040/189] small temp hack to allow readClassInput for now --- R/bambu.R | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/R/bambu.R b/R/bambu.R index 3b8a9cde..d0757628 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -155,7 +155,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, isRDSs = all(sapply(reads, class)=="RangedSummarizedExperiment") isBamFiles = !isRDSs if(!isRDSs) isBamFiles = ifelse(!is(reads, "BamFileList"), all(grepl(".bam$", reads)), FALSE) - if(TRUE){ + if(rgrLists){ #if (isBamFiles | is(reads, "BamFileList")) { if (length(reads) > 10 & (is.null(rcOutDir))) { rcOutDir <- tempdir() #>=10 samples, save to temp folder @@ -193,6 +193,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, min.primarySecondaryDistStartEnd = isoreParameters[['min.primarySecondaryDistStartEnd2']] if (is.character(readClassList)) readClassList <- readRDS(file = readClassList) + if(is.list(readClassList)) readClassList = readClassList[[1]] readClassDist <- isore.estimateDistanceToAnnotations(readClassList, annotations, min.exonDistance = min.exonDistance, min.primarySecondaryDist = min.primarySecondaryDist, From 5fae869df82fb16f8f9f73a572544a5dca8126c4 Mon Sep 17 00:00:00 2001 From: Andre Date: Thu, 28 Sep 2023 11:13:42 +0800 Subject: [PATCH 041/189] Move getUniCountPerEquiRC outside bplapply --- R/bambu-quantify_utilityFunctions.R | 7 +++---- R/bambu.R | 2 +- 2 files changed, 4 insertions(+), 5 deletions(-) diff --git a/R/bambu-quantify_utilityFunctions.R b/R/bambu-quantify_utilityFunctions.R index 39a48c9a..1db1a6f9 100644 --- a/R/bambu-quantify_utilityFunctions.R +++ b/R/bambu-quantify_utilityFunctions.R @@ -44,19 +44,18 @@ processIncompatibleCounts <- function(readClassDist){ #' @import data.table #' @noRd genEquiRCs <- function(readClassDist, annotations, verbose){ - distTable <- genEquiRCsBasedOnObservedReads(readClassDist) - eqClassCount <- getUniCountPerEquiRC(distTable) + eqClassCount <- getUniCountPerEquiRC(metadata(readClassDist)$distTable) eqClassTable <- addEmptyRC(eqClassCount, annotations) # create equiRC id eqClassTable <- eqClassTable %>% group_by(eqClassById) %>% mutate(eqClassId = cur_group_id()) %>% data.table() - + tx_len <- rbind(data.table(txid = mcols(annotations)$txid, txlen = sum(width(annotations)))) eqClassTable <- tx_len[eqClassTable, on = "txid"] %>% distinct() - + # remove unused columns eqClassTable[, eqClassById := NULL] return(eqClassTable) diff --git a/R/bambu.R b/R/bambu.R index d0757628..481047ad 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -200,7 +200,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, min.primarySecondaryDistStartEnd = min.primarySecondaryDistStartEnd, verbose = verbose) metadata(readClassDist)$distTable <- modifyIncompatibleAssignment(metadata(readClassDist)$distTable) - #metadata(readClassDist)$distTable <- genEquiRCsBasedOnObservedReads(readClassDist) + metadata(readClassDist)$distTable <- genEquiRCsBasedOnObservedReads(readClassDist) # if (trackReads) metadata(seOutput)$readToTranscriptMap = # generateReadToTranscriptMap(readClass, metadata(readClassDist)$distTable, # annotations) From 22a8aaf791a8c4d64b7fda0e6f534f4acaae3464 Mon Sep 17 00:00:00 2001 From: Andre Date: Thu, 28 Sep 2023 18:10:38 +0800 Subject: [PATCH 042/189] Speed up bambu.quant --- DESCRIPTION | 3 ++- NAMESPACE | 1 + R/bambu-quantify.R | 27 +++++++++++++++++++++++---- R/bambu-quantify_utilityFunctions.R | 3 ++- R/bambu.R | 3 ++- 5 files changed, 30 insertions(+), 7 deletions(-) diff --git a/DESCRIPTION b/DESCRIPTION index d6a36949..c5a34856 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -86,7 +86,8 @@ Imports: Rsamtools, methods, Rcpp, - xgboost + xgboost, + Matrix VignetteBuilder: knitr LazyData: true diff --git a/NAMESPACE b/NAMESPACE index b4c51d05..7fa99dc8 100755 --- a/NAMESPACE +++ b/NAMESPACE @@ -76,4 +76,5 @@ import(SummarizedExperiment) import(S4Vectors, except=c(rename, setequal, setdiff, intersect,cor)) useDynLib(bambu, .registration = TRUE) import(xgboost) +import(Matrix) import(BSgenome) diff --git a/R/bambu-quantify.R b/R/bambu-quantify.R index 3b10eabf..ad2c5344 100644 --- a/R/bambu-quantify.R +++ b/R/bambu-quantify.R @@ -2,13 +2,33 @@ #' @inheritParams bambu #' @import data.table #' @noRd -bambu.quantify <- function(i, readClassDist, countMatrix, annotations, emParameters, +bambu.quantify <- function(i, readClassDist, readClassDt, countMatrix, annotations, emParameters, trackReads = FALSE, returnDistTable = FALSE, verbose = FALSE, isoreParameters = setIsoreParameters(NULL)) { - metadata(readClassDist)$distTable$readCount <- countMatrix[,i] + metadata(readClassDist)$distTable = metadata(readClassDist)$distTable[metadata(readClassDist)$distTable$readCount != 0,] #distTable$readCount <- assays(seReadClass)$counts - readClassDt <- genEquiRCs(readClassDist, annotations, verbose) + + + #calculate equivilent class counts + start.ptm <- proc.time() + y = metadata(readClassDist)$distTable %>% group_by(eqClassById) %>% + mutate(anyEqual = any(equal)) %>% + select(eqClassById, firstExonWidth,totalWidth, readCount,GENEID,anyEqual) %>% #eqClassByIdTemp, + distinct() %>% + mutate(nobs = sum(readCount), + rcWidth = ifelse(anyEqual, max(totalWidth), + max(firstExonWidth))) %>% + select(eqClassById,GENEID,nobs,rcWidth) %>% + ungroup() %>% + distinct() + readClassDt$nobs = y$nobs[match(readClassDt$eqClassById,y$eqClassById)] + readClassDt$nobs[is.na(readClassDt$nobs)] = 0 + end.ptm <- proc.time() + if (verbose) message("Finished eqv.class counts in ", + round((end.ptm - start.ptm)[3] / 60, 1), " mins.") + #### + incompatibleCounts <- processIncompatibleCounts(readClassDist) compatibleCounts <- bambu.quantDT(readClassDt, emParameters = emParameters,verbose = verbose) incompatibleCounts <- incompatibleCounts[data.table(GENEID = unique(mcols(annotations)$GENEID)), on = "GENEID"] @@ -28,7 +48,6 @@ bambu.quantify <- function(i, readClassDist, countMatrix, annotations, emParamet uniqueCounts = matrix(counts$uniqueCounts, ncol = 1, dimnames = list(NULL, colNameRC)))) metadata(seOutput)$incompatibleCounts = incompatibleCounts - return(seOutput) } diff --git a/R/bambu-quantify_utilityFunctions.R b/R/bambu-quantify_utilityFunctions.R index 1db1a6f9..a1c30fdc 100644 --- a/R/bambu-quantify_utilityFunctions.R +++ b/R/bambu-quantify_utilityFunctions.R @@ -57,7 +57,8 @@ genEquiRCs <- function(readClassDist, annotations, verbose){ eqClassTable <- tx_len[eqClassTable, on = "txid"] %>% distinct() # remove unused columns - eqClassTable[, eqClassById := NULL] + #eqClassTable[, eqClassById := NULL] + return(eqClassTable) } diff --git a/R/bambu.R b/R/bambu.R index 481047ad..32e42e1f 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -208,8 +208,9 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, #### countMatrix2 = metadata(readClassList)$countMatrix[metadata(readClassDist)$distTable$readClassId,] + readClassDt <- genEquiRCs(readClassDist, annotations, verbose) countsSe <- bplapply(seq_len(ncol(countMatrix2)), bambu.quantify, - readClassDist = readClassDist, countMatrix = countMatrix2, + readClassDist = readClassDist, readClassDt = readClassDt, countMatrix = countMatrix2, annotations = annotations, isoreParameters = isoreParameters, emParameters = emParameters, trackReads = trackReads, returnDistTable = returnDistTable, verbose = verbose, From e7d3c7b08ead127d23cf9509cfcba8ce7bc99c25 Mon Sep 17 00:00:00 2001 From: Andre Date: Thu, 28 Sep 2023 18:16:58 +0800 Subject: [PATCH 043/189] Clean up bambu.quantify and add calculateEqClassCounts --- R/bambu-quantify.R | 23 +---------------------- R/bambu-quantify_utilityFunctions.R | 17 +++++++++++++++++ 2 files changed, 18 insertions(+), 22 deletions(-) diff --git a/R/bambu-quantify.R b/R/bambu-quantify.R index ad2c5344..ed4d09a8 100644 --- a/R/bambu-quantify.R +++ b/R/bambu-quantify.R @@ -7,28 +7,7 @@ bambu.quantify <- function(i, readClassDist, readClassDt, countMatrix, annotatio verbose = FALSE, isoreParameters = setIsoreParameters(NULL)) { metadata(readClassDist)$distTable$readCount <- countMatrix[,i] metadata(readClassDist)$distTable = metadata(readClassDist)$distTable[metadata(readClassDist)$distTable$readCount != 0,] - #distTable$readCount <- assays(seReadClass)$counts - - - #calculate equivilent class counts - start.ptm <- proc.time() - y = metadata(readClassDist)$distTable %>% group_by(eqClassById) %>% - mutate(anyEqual = any(equal)) %>% - select(eqClassById, firstExonWidth,totalWidth, readCount,GENEID,anyEqual) %>% #eqClassByIdTemp, - distinct() %>% - mutate(nobs = sum(readCount), - rcWidth = ifelse(anyEqual, max(totalWidth), - max(firstExonWidth))) %>% - select(eqClassById,GENEID,nobs,rcWidth) %>% - ungroup() %>% - distinct() - readClassDt$nobs = y$nobs[match(readClassDt$eqClassById,y$eqClassById)] - readClassDt$nobs[is.na(readClassDt$nobs)] = 0 - end.ptm <- proc.time() - if (verbose) message("Finished eqv.class counts in ", - round((end.ptm - start.ptm)[3] / 60, 1), " mins.") - #### - + readClassDt$nobs = calculateEqClassCounts(metadata(readClassDist)$distTable, readClassDt) incompatibleCounts <- processIncompatibleCounts(readClassDist) compatibleCounts <- bambu.quantDT(readClassDt, emParameters = emParameters,verbose = verbose) incompatibleCounts <- incompatibleCounts[data.table(GENEID = unique(mcols(annotations)$GENEID)), on = "GENEID"] diff --git a/R/bambu-quantify_utilityFunctions.R b/R/bambu-quantify_utilityFunctions.R index a1c30fdc..bebcb0e2 100644 --- a/R/bambu-quantify_utilityFunctions.R +++ b/R/bambu-quantify_utilityFunctions.R @@ -487,6 +487,23 @@ generateReadToTranscriptMap <- function(readClass, distTable, annotations){ return(readToTranscriptMap) } +#' Get counts of equivilent classes from a distTable and match to a readClassDt +#' @noRd +calculateEqClassCounts = function(distTable, readClassDt){ + eqClasses = distTable %>% group_by(eqClassById) %>% + mutate(anyEqual = any(equal)) %>% + select(eqClassById, firstExonWidth,totalWidth, readCount,GENEID,anyEqual) %>% #eqClassByIdTemp, + distinct() %>% + mutate(nobs = sum(readCount), + rcWidth = ifelse(anyEqual, max(totalWidth), + max(firstExonWidth))) %>% + select(eqClassById,GENEID,nobs,rcWidth) %>% + ungroup() %>% + distinct() + eqCounts = y$nobs[match(readClassDt$eqClassById,eqClasses$eqClassById)] + eqCounts[is.na(eqCounts)] = 0 + return(eqCounts) + } #' calculate CPM post estimation #' @noRd From 136f9a61257db18c15a7c51cc6f1eec7c29d8fc1 Mon Sep 17 00:00:00 2001 From: Andre Date: Thu, 28 Sep 2023 18:23:50 +0800 Subject: [PATCH 044/189] Tidy up code --- R/bambu.R | 24 +++++++++--------------- R/bambu_utilityFunctions.R | 16 ---------------- 2 files changed, 9 insertions(+), 31 deletions(-) diff --git a/R/bambu.R b/R/bambu.R index 32e42e1f..9daa3f14 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -186,25 +186,15 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, if(length(annotations)==0) stop("No valid annotations, if running de novo please try less stringent parameters") - #Do distTable calculation once on all read classes - min.exonDistance = isoreParameters[["min.exonDistance"]] - min.primarySecondaryDist = - isoreParameters[['min.primarySecondaryDist']] - min.primarySecondaryDistStartEnd = - isoreParameters[['min.primarySecondaryDistStartEnd2']] if (is.character(readClassList)) readClassList <- readRDS(file = readClassList) if(is.list(readClassList)) readClassList = readClassList[[1]] readClassDist <- isore.estimateDistanceToAnnotations(readClassList, annotations, - min.exonDistance = min.exonDistance, - min.primarySecondaryDist = min.primarySecondaryDist, - min.primarySecondaryDistStartEnd = min.primarySecondaryDistStartEnd, + min.exonDistance = isoreParameters[["min.exonDistance"]], + min.primarySecondaryDist = isoreParameters[['min.primarySecondaryDist']] + min.primarySecondaryDistStartEnd = isoreParameters[['min.primarySecondaryDistStartEnd2']], verbose = verbose) metadata(readClassDist)$distTable <- modifyIncompatibleAssignment(metadata(readClassDist)$distTable) - metadata(readClassDist)$distTable <- genEquiRCsBasedOnObservedReads(readClassDist) - # if (trackReads) metadata(seOutput)$readToTranscriptMap = - # generateReadToTranscriptMap(readClass, metadata(readClassDist)$distTable, - # annotations) - # if (returnDistTable) metadata(seOutput)$distTable = metadata(readClassDist)$distTable + metadata(readClassDist)$distTable <- genEquiRCsBasedOnObservedReads(readClassDist) #### countMatrix2 = metadata(readClassList)$countMatrix[metadata(readClassDist)$distTable$readClassId,] @@ -215,9 +205,13 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, emParameters = emParameters, trackReads = trackReads, returnDistTable = returnDistTable, verbose = verbose, BPPARAM = bpParameters) - countsSe <- combineCountSes(countsSe, trackReads, returnDistTable) + countsSe <- combineCountSes(countsSe, trackReads) rowRanges(countsSe) <- annotations metadata(countsSe)$warnings = warnings + if (trackReads) metadata(seOutput)$readToTranscriptMap = + generateReadToTranscriptMap(readClass, metadata(readClassDist)$distTable, + annotations) + if (returnDistTable) metadata(seOutput)$distTable = metadata(readClassDist)$distTable if (rm.readClassSe) file.remove(unlist(readClassList)) message("--- Finished running Bambu ---") return(countsSe) diff --git a/R/bambu_utilityFunctions.R b/R/bambu_utilityFunctions.R index 8d8b98d1..d22db18e 100644 --- a/R/bambu_utilityFunctions.R +++ b/R/bambu_utilityFunctions.R @@ -214,28 +214,12 @@ handleWarnings <- function(readClassList, verbose){ #' @noRd combineCountSes <- function(countsSe, trackReads = FALSE, returnDistTable = FALSE){ sampleNames = sapply(countsSe, FUN = function(x){colnames(x)}) - if(trackReads){ - readToTranscriptMaps = lapply(countsSe, FUN = function(se){metadata(se)$readToTranscriptMap}) - names(readToTranscriptMaps) = sampleNames - countsSe = lapply(countsSe, FUN = function(se){ - metadata(se)$readToTranscriptMap=NULL - return(se)}) - } - if(returnDistTable){ - distTables = lapply(countsSe, FUN = function(se){metadata(se)$distTable}) - names(distTables) = sampleNames - countsSe = lapply(countsSe, FUN = function(se){ - metadata(se)$distTable=NULL - return(se)}) - } # combine incompatible counts incompatibleCounts = Reduce(merge_wrapper, lapply(countsSe, FUN = function(se){metadata(se)$incompatibleCounts})) countsSe = lapply(countsSe, FUN = function(se){ metadata(se)$incompatibleCounts=NULL return(se)}) countsSe <- do.call(SummarizedExperiment::cbind, countsSe) - if(trackReads) metadata(countsSe)$readToTranscriptMaps = readToTranscriptMaps - if(returnDistTable) metadata(countsSe)$distTables = distTables metadata(countsSe)$incompatibleCounts = incompatibleCounts return(countsSe) } From df4476bc4f1e21fcfb6c2e890ec3629d8da2dc8d Mon Sep 17 00:00:00 2001 From: Andre Date: Thu, 28 Sep 2023 18:24:15 +0800 Subject: [PATCH 045/189] Also tidy up --- R/bambu.R | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/R/bambu.R b/R/bambu.R index 9daa3f14..4371b7bf 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -195,8 +195,6 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, verbose = verbose) metadata(readClassDist)$distTable <- modifyIncompatibleAssignment(metadata(readClassDist)$distTable) metadata(readClassDist)$distTable <- genEquiRCsBasedOnObservedReads(readClassDist) - - #### countMatrix2 = metadata(readClassList)$countMatrix[metadata(readClassDist)$distTable$readClassId,] readClassDt <- genEquiRCs(readClassDist, annotations, verbose) countsSe <- bplapply(seq_len(ncol(countMatrix2)), bambu.quantify, @@ -205,7 +203,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, emParameters = emParameters, trackReads = trackReads, returnDistTable = returnDistTable, verbose = verbose, BPPARAM = bpParameters) - countsSe <- combineCountSes(countsSe, trackReads) + countsSe <- combineCountSes(countsSe) rowRanges(countsSe) <- annotations metadata(countsSe)$warnings = warnings if (trackReads) metadata(seOutput)$readToTranscriptMap = From ea452f00750068dbd4a7c4c5aab975def6115d85 Mon Sep 17 00:00:00 2001 From: Andre Date: Mon, 2 Oct 2023 16:03:56 +0800 Subject: [PATCH 046/189] Fix issue where old memory was used --- R/bambu-processReads.R | 16 +++++++++++++--- R/bambu-quantify_utilityFunctions.R | 2 +- R/bambu.R | 12 ++++++------ 3 files changed, 20 insertions(+), 10 deletions(-) diff --git a/R/bambu-processReads.R b/R/bambu-processReads.R index 736f7dd4..18520287 100644 --- a/R/bambu-processReads.R +++ b/R/bambu-processReads.R @@ -65,9 +65,9 @@ bambu.processReads <- function(reads, annotations, genomeSequence, fitReadClassModel = fitReadClassModel, min.exonOverlap = min.exonOverlap, defaultModels = defaultModels, returnModel = returnModel, verbose = verbose, lowMemory = lowMemory, trackReads = trackReads, fusionMode = fusionMode) - - metadata(readClassList)$samples = reads + metadata(readClassList)$samples = names(reads) countMatrix = splitReadClassFiles(readClassList) + colnames(countMatrix) = metadata(readClassList)$samples rownames(countMatrix) = rownames(readClassList) metadata(readClassList)$countMatrix = countMatrix @@ -158,7 +158,6 @@ bambu.processReadsByFile <- function(bam.file, genomeSequence, annotations, if(length(readGrgList) == 0) { stop("No reads left after filtering.") } - return(readGrgList) } @@ -258,5 +257,16 @@ splitReadClassFiles = function(readClassFile){ counts = sparseMatrix(i = rowIndex, j = rep(seq_along(metadata(readClassFile)$samples), sampleCount), x = counts) + +# countMat = sapply(seq_along(metadata(readClassFile)$samples), FUN = function(i){ +# counts.sample = sapply(rowData(readClassFile)$sampleIDs, FUN = function(x){sum(x==i)}) +# return(c(counts.sample[counts.sample != 0], #counts +# which(counts.sample != 0)), #rowindex +# sum(counts.sample !=0)) #sampleCount +# }) +# counts = sparseMatrix(i = countMat[2,], +# j = rep(seq_along(metadata(readClassFile)$samples), countMat[3,]), +# x = countMat[1,]) + return(counts) } \ No newline at end of file diff --git a/R/bambu-quantify_utilityFunctions.R b/R/bambu-quantify_utilityFunctions.R index bebcb0e2..bf07d9dd 100644 --- a/R/bambu-quantify_utilityFunctions.R +++ b/R/bambu-quantify_utilityFunctions.R @@ -500,7 +500,7 @@ calculateEqClassCounts = function(distTable, readClassDt){ select(eqClassById,GENEID,nobs,rcWidth) %>% ungroup() %>% distinct() - eqCounts = y$nobs[match(readClassDt$eqClassById,eqClasses$eqClassById)] + eqCounts = eqClasses$nobs[match(readClassDt$eqClassById,eqClasses$eqClassById)] eqCounts[is.na(eqCounts)] = 0 return(eqCounts) } diff --git a/R/bambu.R b/R/bambu.R index 4371b7bf..90714e38 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -155,8 +155,8 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, isRDSs = all(sapply(reads, class)=="RangedSummarizedExperiment") isBamFiles = !isRDSs if(!isRDSs) isBamFiles = ifelse(!is(reads, "BamFileList"), all(grepl(".bam$", reads)), FALSE) - if(rgrLists){ - #if (isBamFiles | is(reads, "BamFileList")) { + #if(rgrLists){ + if (isBamFiles | is(reads, "BamFileList")) { if (length(reads) > 10 & (is.null(rcOutDir))) { rcOutDir <- tempdir() #>=10 samples, save to temp folder message("There are more than 10 samples, read class files @@ -176,7 +176,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, if (!discovery & !quant) return(readClassList) if (discovery) { message("--- Start extending annotations ---") - annotations <- bambu.extendAnnotations(list(readClassList), annotations, NDR, + annotations <- bambu.extendAnnotations(readClassList, annotations, NDR, isoreParameters, stranded, bpParameters, fusionMode, verbose) metadata(annotations)$warnings = warnings if (!quant) return(annotations) @@ -190,11 +190,11 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, if(is.list(readClassList)) readClassList = readClassList[[1]] readClassDist <- isore.estimateDistanceToAnnotations(readClassList, annotations, min.exonDistance = isoreParameters[["min.exonDistance"]], - min.primarySecondaryDist = isoreParameters[['min.primarySecondaryDist']] + min.primarySecondaryDist = isoreParameters[['min.primarySecondaryDist']], min.primarySecondaryDistStartEnd = isoreParameters[['min.primarySecondaryDistStartEnd2']], verbose = verbose) metadata(readClassDist)$distTable <- modifyIncompatibleAssignment(metadata(readClassDist)$distTable) - metadata(readClassDist)$distTable <- genEquiRCsBasedOnObservedReads(readClassDist) + metadata(readClassDist)$distTable <- genEquiRCsBasedOnObservedReads(readClassDist) countMatrix2 = metadata(readClassList)$countMatrix[metadata(readClassDist)$distTable$readClassId,] readClassDt <- genEquiRCs(readClassDist, annotations, verbose) countsSe <- bplapply(seq_len(ncol(countMatrix2)), bambu.quantify, @@ -205,7 +205,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, BPPARAM = bpParameters) countsSe <- combineCountSes(countsSe) rowRanges(countsSe) <- annotations - metadata(countsSe)$warnings = warnings + #metadata(countsSe)$warnings = warnings if (trackReads) metadata(seOutput)$readToTranscriptMap = generateReadToTranscriptMap(readClass, metadata(readClassDist)$distTable, annotations) From d739035d4e763196f7f43d30673af32e5df6c97a Mon Sep 17 00:00:00 2001 From: Andre Date: Mon, 2 Oct 2023 16:08:41 +0800 Subject: [PATCH 047/189] MessyForest --- R/bambu-processReads.R | 133 ++++++++---- ...processReads_utilityConstructReadClasses.R | 61 +++--- R/bambu-quantify.R | 151 ++++++++------ R/bambu.R | 191 +++++++++++++----- R/bambu_utilityFunctions.R | 25 +-- R/prepareDataFromBam.R | 23 ++- R/readWrite.R | 50 ++++- R/transcriptToGeneExpression.R | 8 +- 8 files changed, 430 insertions(+), 212 deletions(-) diff --git a/R/bambu-processReads.R b/R/bambu-processReads.R index 31246d35..d4dad79e 100644 --- a/R/bambu-processReads.R +++ b/R/bambu-processReads.R @@ -15,7 +15,8 @@ bambu.processReads <- function(reads, annotations, genomeSequence, readClass.outputDir=NULL, yieldSize=1000000, bpParameters, stranded=FALSE, verbose=FALSE, isoreParameters = setIsoreParameters(NULL), - lowMemory=FALSE, trackReads = trackReads, fusionMode = fusionMode) { + lowMemory=FALSE, trackReads = trackReads, fusionMode = fusionMode, + demultiplexed = demultiplexed, readGrgListFile = readGrgListFile) { genomeSequence <- checkInputSequence(genomeSequence) # ===# create BamFileList object from character #===# if (is(reads, "BamFile")) { @@ -44,15 +45,24 @@ bambu.processReads <- function(reads, annotations, genomeSequence, defaultModels = isoreParameters[["defaultModels"]] returnModel = isoreParameters[["returnModel"]] min.exonOverlap = isoreParameters[["min.exonOverlap"]] - readClassList <- bplapply(names(reads), function(bamFileName) { + + ### add ### + if (!is.null(readGrgListFile)){ + reads <- as.list(readGrgListFile) + names(reads) <- tools::file_path_sans_ext(BiocGenerics::basename(readGrgListFile)) + } + ### add ### + readClassList <- bplapply(names(reads), function(bamFileName){ bambu.processReadsByFile(bam.file = reads[bamFileName], - genomeSequence = genomeSequence,annotations = annotations, - readClass.outputDir = readClass.outputDir, + genomeSequence = genomeSequence, annotations = annotations, + readClass.outputDir = readClass.outputDir, yieldSize = yieldSize, stranded = stranded, min.readCount = min.readCount, fitReadClassModel = fitReadClassModel, min.exonOverlap = min.exonOverlap, defaultModels = defaultModels, returnModel = returnModel, verbose = verbose, - lowMemory = lowMemory, trackReads = trackReads, fusionMode = fusionMode)}, + lowMemory = lowMemory, trackReads = trackReads, fusionMode = fusionMode, + demultiplexed = demultiplexed, readGrgListFile = readGrgListFile)}, BPPARAM = bpParameters) + return(readClassList) } @@ -61,55 +71,88 @@ bambu.processReads <- function(reads, annotations, genomeSequence, #' @importFrom GenomeInfoDb seqlevels seqlevels<- keepSeqlevels #' @noRd bambu.processReadsByFile <- function(bam.file, genomeSequence, annotations, - readClass.outputDir = NULL, stranded = FALSE, min.readCount = 2, + readClass.outputDir = NULL, yieldSize = NULL, stranded = FALSE, min.readCount = 2, fitReadClassModel = TRUE, min.exonOverlap = 10, defaultModels = NULL, returnModel = FALSE, - verbose = FALSE, lowMemory = FALSE, trackReads = FALSE, fusionMode = FALSE) { - if(verbose) message(names(bam.file)[1]) - readGrgList <- prepareDataFromBam(bam.file[[1]], verbose = verbose, use.names = trackReads) - warnings = c() - warnings = seqlevelCheckReadsAnnotation(readGrgList, annotations) - if(verbose & length(warnings) > 0) warning(paste(warnings,collapse = "\n")) - #check seqlevels for consistency, drop ranges not present in genomeSequence - refSeqLevels <- seqlevels(genomeSequence) - if (!all(seqlevels(readGrgList) %in% refSeqLevels)) { + verbose = FALSE, lowMemory = FALSE, trackReads = FALSE, fusionMode = FALSE, + demultiplexed = FALSE, readGrgListFile = NULL) { + ### add ### + if (is.null(readGrgListFile)){ + ### add ### + if(verbose) message(names(bam.file)[1]) + readGrgList <- prepareDataFromBam(bam.file[[1]], yieldSize = yieldSize, verbose = verbose, use.names = trackReads, + demultiplexed = demultiplexed) + warnings = c() + warnings = seqlevelCheckReadsAnnotation(readGrgList, annotations) + if(verbose & length(warnings) > 0) warning(paste(warnings,collapse = "\n")) + #check seqlevels for consistency, drop ranges not present in genomeSequence + refSeqLevels <- seqlevels(genomeSequence) + if (!all(seqlevels(readGrgList) %in% refSeqLevels)) { refSeqLevels <- intersect(refSeqLevels, seqlevels(readGrgList)) if (!all(seqlevels(annotations) %in% refSeqLevels)&(!(length(annotations)==0))) { - refSeqLevels <- intersect(refSeqLevels, seqlevels(annotations)) - warningText = paste0("not all chromosomes from annotations present in ", - "reference genome sequence, annotations without reference genomic sequence ", - "are dropped") - warnings = c(warnings, warningText) - if(verbose) warning(warningText) - annotations <- keepSeqlevels(annotations, value = refSeqLevels, - pruning.mode = "coarse") + refSeqLevels <- intersect(refSeqLevels, seqlevels(annotations)) + warningText = paste0("not all chromosomes from annotations present in ", + "reference genome sequence, annotations without reference genomic sequence ", + "are dropped") + warnings = c(warnings, warningText) + if(verbose) warning(warningText) + annotations <- keepSeqlevels(annotations, value = refSeqLevels, + pruning.mode = "coarse") } warningText = paste0("not all chromosomes from reads present in reference ", - "genome sequence, reads without reference chromosome sequence are dropped") + "genome sequence, reads without reference chromosome sequence are dropped") warnings = c(warnings, warningText) if(verbose) warning(warningText) readGrgList <- keepSeqlevels(readGrgList, value = refSeqLevels, pruning.mode = "coarse") - # reassign Ids after seqlevels are dropped - mcols(readGrgList)$id <- seq_along(readGrgList) - } - #removes reads that are outside genome coordinates - badReads = which(max(end(ranges(readGrgList)))>= + } + #removes reads that are outside genome coordinates + badReads = which(max(end(ranges(readGrgList)))>= seqlengths(genomeSequence)[as.character(getChrFromGrList(readGrgList))]) - if(length(badReads) > 0 ){ + if(length(badReads) > 0 ){ readGrgList = readGrgList[-badReads] warningText = paste0(length(badReads), " reads are mapped outside the provided ", - "genomic regions. These reads will be dropped. Check you are using the ", - "same genome used for the alignment") + "genomic regions. These reads will be dropped. Check you are using the ", + "same genome used for the alignment") warnings = c(warnings, warningText) if(verbose) warning(warningText) - } - if(length(readGrgList) == 0) { + } + + ### add ### + # reassign Ids after seqlevels are dropped + mcols(readGrgList)$id <- seq_along(readGrgList) + ### add ### + + if(length(readGrgList) == 0) { stop("No reads left after filtering.") + } + + ## add ### + if (isTRUE(demultiplexed)){ + cellBarcodeAssign <- tibble(index = mcols(readGrgList)$id, CB = mcols(readGrgList)$CB) %>% nest(.by = "CB") + + if (!dir.exists("CB")){ + dir.create("CB") + } else{ + unlink(paste("CB", "*", sep = "/")) + } + + invisible(lapply(seq(nrow(cellBarcodeAssign)), + function(x){saveRDS(readGrgList[pull(cellBarcodeAssign$data[[x]])], paste0("CB/", cellBarcodeAssign$CB[[x]],".rds"))})) + } + ## add ### + + ### add ### + } else { + + readGrgList <- readRDS(bam.file[[1]]) + } + ### add ### + # construct read classes for each chromosome seperately - if(lowMemory) se <- lowMemoryConstructReadClasses(readGrgList, genomeSequence, + if(lowMemory) {se <- lowMemoryConstructReadClasses(readGrgList, genomeSequence, annotations, stranded, verbose,bam.file) - else { + } else { unlisted_junctions <- unlistIntrons(readGrgList, use.ids = TRUE) if(length(unlisted_junctions)==0){ warningText = paste0("No aligned spliced reads detected!", @@ -132,9 +175,15 @@ bambu.processReadsByFile <- function(bam.file, genomeSequence, annotations, metadata(se)$readId = mcols(readGrgList)$id } rm(readGrgList) - GenomeInfoDb::seqlevels(se) <- refSeqLevels + + ### add ### + if (is.null(readGrgListFile)){ + GenomeInfoDb::seqlevels(se) <- refSeqLevels + } + ### add ### + # create SE object with reconstructed readClasses - se <- scoreReadClasses(se,genomeSequence, annotations, + se <- scoreReadClasses(se, genomeSequence, annotations, defaultModels = defaultModels, fit = fitReadClassModel, returnModel = returnModel, @@ -142,6 +191,7 @@ bambu.processReadsByFile <- function(bam.file, genomeSequence, annotations, min.exonOverlap = min.exonOverlap, fusionMode = fusionMode, verbose = verbose) + if (!is.null(readClass.outputDir)) { readClassFile <- paste0(readClass.outputDir,names(bam.file), "_readClassSe.rds") @@ -156,6 +206,11 @@ bambu.processReadsByFile <- function(bam.file, genomeSequence, annotations, saveRDS(se, file = readClassFile) se <- readClassFile } + + if (!is.null(readGrgListFile)){ + se <- names(se) + } + return(se) } @@ -194,4 +249,4 @@ seqlevelCheckReadsAnnotation <- function(reads, annotations){ "annotations might be incomplete. Please compare objects ", "on the same reference")) return(warnings) -} \ No newline at end of file +} diff --git a/R/bambu-processReads_utilityConstructReadClasses.R b/R/bambu-processReads_utilityConstructReadClasses.R index 4858798b..999e53b0 100644 --- a/R/bambu-processReads_utilityConstructReadClasses.R +++ b/R/bambu-processReads_utilityConstructReadClasses.R @@ -385,12 +385,10 @@ assignGeneIds <- function(grl, annotations, min.exonOverlap = 10, fusionMode = fusionMode = fusionMode) #iteratively assign gene ids for stranded granges newGeneSet <- is.na(mcols(grl)$GENEID) & strandedRanges - if(sum(newGeneSet != 0)){ - referenceGeneSet <- !is.na(mcols(grl)$GENEID) & strandedRanges - mcols(grl)$GENEID[newGeneSet] <- assignGeneIdsByReference(grl[newGeneSet], grl[referenceGeneSet], - min.exonOverlap = min.exonOverlap, - fusionMode = FALSE) # fusion assignment is only done based on original annotations - } + referenceGeneSet <- !is.na(mcols(grl)$GENEID) & strandedRanges + mcols(grl)$GENEID[newGeneSet] <- assignGeneIdsByReference(grl[newGeneSet], grl[referenceGeneSet], + min.exonOverlap = min.exonOverlap, + fusionMode = FALSE) # fusion assignment is only done based on original annotations chainCount <- 1 # first iteration is outside of while loop while(any(!is.na(mcols(grl)$GENEID[newGeneSet])) & chainCount < maxChainIteration) { referenceGeneSet <- newGeneSet & !is.na(mcols(grl)$GENEID) & strandedRanges @@ -442,31 +440,32 @@ assignGeneIdsByReference <- function(grl, annotations, min.exonOverlap = 10, uniqueHits <- which(queryHits(ov) %in% which(countQueryHits(ov)==1)) geneIds[queryHits(ov)[uniqueHits]] <- names(geneRanges)[subjectHits(ov)[uniqueHits]] - if(length(ov)>0){ - ## next for non unique hits select one gene (maximum overlap) - multiHits <- which(queryHits(ov) %in% which(countQueryHits(ov)>1)) - rangeIntersect= intersect(ranges(grl[queryHits(ov)[multiHits]]), - ranges(geneRanges[subjectHits(ov)[multiHits]])) - filteredMultiHits = data.frame(queryHits = queryHits(ov)[multiHits], - intersectWidth = sum(width(rangeIntersect)), - subjectHits = subjectHits(ov)[multiHits]) %>% - group_by(queryHits) %>% summarise(subjectHits = subjectHits[which.max(intersectWidth)], - intersectWidth = max(intersectWidth)) - if(fusionMode) { - filteredMultiHits <- filteredMultiHits %>% - filter(intersectWidth>min.exonOverlap) %>% - mutate(geneid = names(geneRanges)[subjectHits]) %>% distinct() %>% - group_by(queryHits) %>% summarise(geneid = paste(geneid, collapse=':')) - geneIds[filteredMultiHits$queryHits] <- filteredMultiHits$geneid - - } else { - filteredMultiHits <- filteredMultiHits %>% - group_by(queryHits) %>% arrange(desc(intersectWidth)) %>% - dplyr::slice(1) - geneIds[filteredMultiHits$queryHits] <- - names(geneRanges)[filteredMultiHits$subjectHits] - } - } + + ## next for non unique hits select one gene (maximum overlap) + multiHits <- which(queryHits(ov) %in% which(countQueryHits(ov)>1)) + expandedRanges <- expandRangesList(ranges(grl[queryHits(ov)[multiHits]]), + ranges(geneRanges[subjectHits(ov)[multiHits]])) + rangeIntersect <- pintersect(expandedRanges, + mcols(expandedRanges)$matchRng, resolve.empty = 'start.x') + intersectById <- tapply(width(rangeIntersect), + mcols(expandedRanges)$IdMap, sum) + + filteredMultiHits <- as_tibble(ov[multiHits]) %>% + mutate(intersectWidth = intersectById) + if(fusionMode) { + filteredMultiHits <- filteredMultiHits %>% + filter(intersectWidth>min.exonOverlap) %>% + mutate(geneid = names(geneRanges)[subjectHits]) %>% distinct() %>% + group_by(queryHits) %>% summarise(geneid = paste(geneid, collapse=':')) + geneIds[filteredMultiHits$queryHits] <- filteredMultiHits$geneid + + } else { + filteredMultiHits <- filteredMultiHits %>% + group_by(queryHits) %>% arrange(desc(intersectWidth)) %>% + dplyr::slice(1) + geneIds[filteredMultiHits$queryHits] <- + names(geneRanges)[filteredMultiHits$subjectHits] + } return(geneIds) } diff --git a/R/bambu-quantify.R b/R/bambu-quantify.R index fa5a079d..6f0f9583 100644 --- a/R/bambu-quantify.R +++ b/R/bambu-quantify.R @@ -4,47 +4,82 @@ #' @noRd bambu.quantify <- function(readClass, annotations, emParameters, trackReads = FALSE, returnDistTable = FALSE, - verbose = FALSE, isoreParameters = setIsoreParameters(NULL)) { - min.exonDistance = isoreParameters[["min.exonDistance"]] - min.primarySecondaryDist = - isoreParameters[['min.primarySecondaryDist']] - min.primarySecondaryDistStartEnd = - isoreParameters[['min.primarySecondaryDistStartEnd2']] - if (is.character(readClass)) readClass <- readRDS(file = readClass) - readClassDist <- isore.estimateDistanceToAnnotations(readClass, annotations, - min.exonDistance = min.exonDistance, - min.primarySecondaryDist = min.primarySecondaryDist, - min.primarySecondaryDistStartEnd = min.primarySecondaryDistStartEnd, - verbose = verbose) - metadata(readClassDist)$distTable <- modifyIncompatibleAssignment(metadata(readClassDist)$distTable) - incompatibleCounts <- processIncompatibleCounts(readClassDist) - readClassDt <- genEquiRCs(readClassDist, annotations, verbose) - compatibleCounts <- bambu.quantDT(readClassDt, emParameters = emParameters,verbose = verbose) - incompatibleCounts <- incompatibleCounts[data.table(GENEID = unique(mcols(annotations)$GENEID)), on = "GENEID"] - incompatibleCounts[is.na(counts), counts := 0] - compatibleCounts <- calculateCPM(compatibleCounts, incompatibleCounts) - setnames(incompatibleCounts, "counts", colnames(readClass)) - counts <- compatibleCounts[match(mcols(annotations)$txid, txid)] - colNameRC <- colnames(readClass) - colDataRC <- colData(readClass) - sig.digit <- emParameters[["sig.digit"]] - seOutput <- SummarizedExperiment( - assays = SimpleList(counts = matrix(round(counts$counts,sig.digit), ncol = 1, - dimnames = list(NULL, colNameRC)), CPM = matrix(round(counts$CPM,sig.digit), - ncol = 1, dimnames = list(NULL, colNameRC)), - fullLengthCounts = matrix(round(counts$fullLengthCounts,sig.digit), ncol = 1, - dimnames = list(NULL, colNameRC)), - uniqueCounts = matrix(counts$uniqueCounts, - ncol = 1, dimnames = list(NULL, colNameRC))), colData = colDataRC) - metadata(seOutput)$incompatibleCounts = incompatibleCounts - if (returnDistTable) metadata(seOutput)$distTable = metadata(readClassDist)$distTable - if (trackReads) metadata(seOutput)$readToTranscriptMap = - generateReadToTranscriptMap(readClass, metadata(readClassDist)$distTable, - annotations) - return(seOutput) -} - + verbose = FALSE, readGrgListFile = NULL, + isoreParameters = setIsoreParameters(NULL)) { + min.exonDistance = isoreParameters[["min.exonDistance"]] + min.primarySecondaryDist = + isoreParameters[['min.primarySecondaryDist']] + min.primarySecondaryDistStartEnd = + isoreParameters[['min.primarySecondaryDistStartEnd2']] + if (is.character(readClass)) readClass <- readRDS(file = readClass) + readClassDist <- isore.estimateDistanceToAnnotations(readClass, annotations, + min.exonDistance = min.exonDistance, + min.primarySecondaryDist = min.primarySecondaryDist, + min.primarySecondaryDistStartEnd = min.primarySecondaryDistStartEnd, + verbose = verbose) + metadata(readClassDist)$distTable <- modifyIncompatibleAssignment(metadata(readClassDist)$distTable) + incompatibleCounts <- processIncompatibleCounts(readClassDist) + readClassDt <- genEquiRCs(readClassDist, annotations, verbose) + compatibleCounts <- bambu.quantDT(readClassDt, emParameters = emParameters,verbose = verbose) + + ### add ### + rm(readClassDt) + ### add ### + + incompatibleCounts <- incompatibleCounts[data.table(GENEID = unique(mcols(annotations)$GENEID)), on = "GENEID"] + incompatibleCounts[is.na(counts), counts := 0] + compatibleCounts <- calculateCPM(compatibleCounts, incompatibleCounts) + setnames(incompatibleCounts, "counts", colnames(readClass)) + counts <- compatibleCounts[match(mcols(annotations)$txid, txid)] + + ### add ### + rm(compatibleCounts) + ### add ### + + colNameRC <- colnames(readClass) + colDataRC <- colData(readClass) + sig.digit <- emParameters[["sig.digit"]] + seOutput <- SummarizedExperiment( + assays = SimpleList(counts = matrix(round(counts$counts,sig.digit), ncol = 1, + dimnames = list(NULL, colNameRC)), + CPM = matrix(round(counts$CPM,sig.digit), ncol = 1, dimnames = list(NULL, colNameRC)), + fullLengthCounts = matrix(round(counts$fullLengthCounts,sig.digit), ncol = 1, + dimnames = list(NULL, colNameRC)), + uniqueCounts = matrix(counts$uniqueCounts, + ncol = 1, dimnames = list(NULL, colNameRC))), colData = colDataRC) + + ### add ### + rm(counts) + ### add ### + + metadata(seOutput)$incompatibleCounts = incompatibleCounts + + ### add ### + rm(incompatibleCounts) + ### add ### + + if (returnDistTable) metadata(seOutput)$distTable = metadata(readClassDist)$distTable + if (trackReads) metadata(seOutput)$readToTranscriptMap = + generateReadToTranscriptMap(readClass, metadata(readClassDist)$distTable, + annotations) + + ### add ### + rm(readClassDist) + ### add ### + + ### add ### + if (!is.null(readGrgListFile)){ + seOutput <- list(incompatibleCounts = as(metadata(seOutput)$incompatibleCounts[[colnames(seOutput)]], "sparseVector"), + counts = as(assays(seOutput)$counts, "sparseVector"), + CPM = as(assays(seOutput)$CPM, "sparseVector"), + fullLengthCounts = as(assays(seOutput)$fullLengthCounts, "sparseVector"), + uniqueCounts = as(assays(seOutput)$uniqueCounts, "sparseVector"), + colnames = colnames(seOutput), colData = colData(seOutput)) + } + ### add ### + return(seOutput) +} #' Process data.table object #' @param readClassDt A data.table object @@ -53,24 +88,24 @@ bambu.quantify <- function(readClass, annotations, emParameters, bambu.quantDT <- function(readClassDt = readClassDt, emParameters = list(degradationBias = TRUE, maxiter = 10000, conv = 10^(-2), minvalue = 10^(-8)), ncore = 1, verbose = FALSE) { - rcPreOut <- addAval(readClassDt, emParameters, verbose) - readClassDt <- rcPreOut[[1]] - outIni <- initialiseOutput(readClassDt) - readClassDt <- filterTxRc(readClassDt) - readClassDt <- assignGroups(readClassDt) - inputRcDt <- getInputList(readClassDt) - readClassDt <- split(readClassDt, by = "gene_grp_id") - start.ptm <- proc.time() - outEst <- abundance_quantification(inputRcDt, readClassDt, - maxiter = emParameters[["maxiter"]], - conv = emParameters[["conv"]], minvalue = emParameters[["minvalue"]]) - end.ptm <- proc.time() - if (verbose) message("Finished EM estimation in ", - round((end.ptm - start.ptm)[3] / 60, 1), " mins.") - outEst <- modifyQuantOut(outEst,outIni) - theta_est <- rbind(rcPreOut[[2]],outEst) - theta_est <- removeDuplicates(theta_est) - return(theta_est) + rcPreOut <- addAval(readClassDt, emParameters, verbose) + readClassDt <- rcPreOut[[1]] + outIni <- initialiseOutput(readClassDt) + readClassDt <- filterTxRc(readClassDt) + readClassDt <- assignGroups(readClassDt) + inputRcDt <- getInputList(readClassDt) + readClassDt <- split(readClassDt, by = "gene_grp_id") + start.ptm <- proc.time() + outEst <- abundance_quantification(inputRcDt, readClassDt, + maxiter = emParameters[["maxiter"]], + conv = emParameters[["conv"]], minvalue = emParameters[["minvalue"]]) + end.ptm <- proc.time() + if (verbose) message("Finished EM estimation in ", + round((end.ptm - start.ptm)[3] / 60, 1), " mins.") + outEst <- modifyQuantOut(outEst,outIni) + theta_est <- rbind(rcPreOut[[2]],outEst) + theta_est <- removeDuplicates(theta_est) + return(theta_est) } diff --git a/R/bambu.R b/R/bambu.R index e61d0bfa..dcc12228 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -136,64 +136,143 @@ #' genome = fa.file, discovery = TRUE, quant = TRUE) #' @export bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, - opt.discovery = NULL, opt.em = NULL, rcOutDir = NULL, discovery = TRUE, - quant = TRUE, stranded = FALSE, ncore = 1, yieldSize = NULL, - trackReads = FALSE, returnDistTable = FALSE, lowMemory = FALSE, - fusionMode = FALSE, verbose = FALSE) { - if(is.null(annotations)) { annotations = GRangesList() - } else annotations <- checkInputs(annotations, reads, - readClass.outputDir = rcOutDir, genomeSequence = genome) - isoreParameters <- setIsoreParameters(isoreParameters = opt.discovery) - #below line is to be compatible with earlier version of running bambu - if(!is.null(isoreParameters$max.txNDR)) NDR = isoreParameters$max.txNDR + opt.discovery = NULL, opt.em = NULL, rcOutDir = NULL, discovery = TRUE, + quant = TRUE, stranded = FALSE, ncore = 1, yieldSize = NULL, + trackReads = FALSE, returnDistTable = FALSE, lowMemory = FALSE, + fusionMode = FALSE, verbose = FALSE, demultiplexed = FALSE, readGrgListFile = NULL) { + + ### add ### + library(Matrix) + + if(demultiplexed == TRUE) {trackReads = TRUE; lowMemory = TRUE} + ### add ### + + if(is.null(annotations)) { annotations = GRangesList() + } else annotations <- checkInputs(annotations, reads, + readClass.outputDir = rcOutDir, genomeSequence = genome) + isoreParameters <- setIsoreParameters(isoreParameters = opt.discovery) + #below line is to be compatible with earlier version of running bambu + if(!is.null(isoreParameters$max.txNDR)) NDR = isoreParameters$max.txNDR + + emParameters <- setEmParameters(emParameters = opt.em) + + ### add ### + if (is.null(readGrgListFile)){ + bpParameters <- setBiocParallelParameters(reads, ncore, verbose) - emParameters <- setEmParameters(emParameters = opt.em) - bpParameters <- setBiocParallelParameters(reads, ncore, verbose) - - rm.readClassSe <- FALSE - readClassList = reads - isRDSs = all(sapply(reads, class)=="RangedSummarizedExperiment") - isBamFiles = !isRDSs - if(!isRDSs) isBamFiles = ifelse(!is(reads, "BamFileList"), all(grepl(".bam$", reads)), FALSE) - if (isBamFiles | is(reads, "BamFileList")) { - if (length(reads) > 10 & (is.null(rcOutDir))) { - rcOutDir <- tempdir() #>=10 samples, save to temp folder - message("There are more than 10 samples, read class files + } else{ + bpParameters <- setBiocParallelParameters(readGrgListFile, ncore, verbose) + } + ### add ### + + rm.readClassSe <- FALSE + readClassList = reads + isRDSs = all(sapply(reads, class)=="RangedSummarizedExperiment") + isBamFiles = !isRDSs + if(!isRDSs) isBamFiles = ifelse(!is(reads, "BamFileList"), all(grepl(".bam$", reads)), FALSE) + if (isBamFiles | is(reads, "BamFileList")) { + if (length(reads) > 10 & (is.null(rcOutDir))) { + rcOutDir <- tempdir() #>=10 samples, save to temp folder + message("There are more than 10 samples, read class files will be temporarily saved to ", rcOutDir, - " for more efficient processing") - rm.readClassSe <- TRUE # remove temporary read class files - } - message("--- Start generating read class files ---") - readClassList <- bambu.processReads(reads, annotations, - genomeSequence = genome, - readClass.outputDir = rcOutDir, yieldSize, - bpParameters, stranded, verbose, - isoreParameters, trackReads = trackReads, fusionMode = fusionMode, - lowMemory = lowMemory) - } - warnings = handleWarnings(readClassList, verbose) - if (!discovery & !quant) return(readClassList) - if (discovery) { - message("--- Start extending annotations ---") - annotations <- bambu.extendAnnotations(readClassList, annotations, NDR, - isoreParameters, stranded, bpParameters, fusionMode, verbose) - metadata(annotations)$warnings = warnings - if (!quant) return(annotations) + " for more efficient processing") + rm.readClassSe <- TRUE # remove temporary read class files } - if (quant) { - message("--- Start isoform quantification ---") - if(length(annotations)==0) stop("No valid annotations, if running + message("--- Start generating read class files ---") + + readClassList <- bambu.processReads(reads, annotations, + genomeSequence = genome, + readClass.outputDir = rcOutDir, yieldSize = yieldSize, + bpParameters, stranded, verbose, + isoreParameters, trackReads = trackReads, fusionMode = fusionMode, + lowMemory = lowMemory, demultiplexed = demultiplexed, readGrgListFile = readGrgListFile) + } + if (is.null(readGrgListFile)) warnings = handleWarnings(readClassList, verbose) + if (!discovery & !quant) return(readClassList) + if (discovery) { + message("--- Start extending annotations ---") + annotations <- bambu.extendAnnotations(readClassList, annotations, NDR, + isoreParameters, stranded, bpParameters, fusionMode, verbose) + metadata(annotations)$warnings = warnings + + if (!quant) return(annotations) + } + + if (quant) { + + message("--- Start isoform quantification ---") + if(length(annotations)==0) stop("No valid annotations, if running de novo please try less stringent parameters") - countsSe <- bplapply(readClassList, bambu.quantify, - annotations = annotations, isoreParameters = isoreParameters, - emParameters = emParameters, trackReads = trackReads, - returnDistTable = returnDistTable, verbose = verbose, - BPPARAM = bpParameters) - countsSe <- combineCountSes(countsSe, trackReads, returnDistTable) - rowRanges(countsSe) <- annotations - metadata(countsSe)$warnings = warnings - if (rm.readClassSe) file.remove(unlist(readClassList)) - message("--- Finished running Bambu ---") - return(countsSe) + + ### add ### + if (!is.null(readGrgListFile)){ + + library(BiocFileCache) # temporary + bfc <- BiocFileCache(rcOutDir, ask = FALSE) + info <- bfcinfo(bfc) + + countsSeCompressed <- bplapply(info$rpath, bambu.quantify, + annotations = annotations, isoreParameters = isoreParameters, + emParameters = emParameters, trackReads = trackReads, + returnDistTable = returnDistTable, verbose = verbose, + readGrgListFile = readGrgListFile, + BPPARAM = bpParameters) + + ### countsData + countsData <- c("incompatibleCounts", "counts", "CPM", "fullLengthCounts", "uniqueCounts") + countsDataMat <- list() + + for (k in seq_along(countsData)){ + countsVecList <- lapply(seq_along(countsSeCompressed), function(j){countsSeCompressed[[j]][[countsData[k]]]}) + + countsMat <- sparseMatrix(i = unlist(lapply(seq_along(countsVecList), function(j){countsVecList[[j]]@i})), + j = unlist(lapply(seq_along(countsVecList), function(j){rep(j, length(countsVecList[[j]]@i))})), + x = unlist(lapply(seq_along(countsVecList), function(j){countsVecList[[j]]@x})), + dims = c(length(countsVecList[[1]]), length(countsVecList))) + + colnames(countsMat) <- unlist(lapply(seq_along(countsSeCompressed), function(j){countsSeCompressed[[j]]$colnames})) + + if (countsData[k] == "incompatibleCounts"){ + countsMat <- data.table(as.data.frame(as.matrix(countsMat)) %>% + mutate(GENEID = unique(mcols(annotations)$GENEID)) %>% + select(GENEID, everything())) + } + + countsDataMat[[countsData[k]]] <- countsMat + } + + countsSe <- SummarizedExperiment(assays = SimpleList(counts = countsDataMat$counts, + CPM = countsDataMat$CPM, + fullLengthCounts = countsDataMat$fullLengthCounts, + uniqueCounts = countsDataMat$uniqueCounts), + colData = as(bind_rows(lapply(lapply(seq_along(countsSeCompressed), + function(j){countsSeCompressed[[j]]$colData}), as.data.frame)), "DataFrame")) + + metadata(countsSe)$incompatibleCounts <- countsDataMat$incompatibleCounts + rowRanges(countsSe) <- annotations + metadata(countsSe)$warnings = warnings + + } else { + ### add ### + countsSe <- bplapply(readClassList, bambu.quantify, + annotations = annotations, isoreParameters = isoreParameters, + emParameters = emParameters, trackReads = trackReads, + returnDistTable = returnDistTable, verbose = verbose, + readGrgListFile = readGrgListFile, + BPPARAM = bpParameters) + + countsSe <- combineCountSes(countsSe, trackReads, returnDistTable) + rowRanges(countsSe) <- annotations + metadata(countsSe)$warnings = warnings } -} \ No newline at end of file + + ### add ### + #if (!is.null(readGrgListFile)) unlink(unique(dirname(readGrgListFile)), recursive = TRUE) + ### add ### + + #if (rm.readClassSe) file.remove(unlist(readClassList)) + message("--- Finished running Bambu ---") + + return(countsSe) + } +} diff --git a/R/bambu_utilityFunctions.R b/R/bambu_utilityFunctions.R index 8d8b98d1..be588acf 100644 --- a/R/bambu_utilityFunctions.R +++ b/R/bambu_utilityFunctions.R @@ -184,27 +184,24 @@ handleWarnings <- function(readClassList, verbose){ sampleNames = c() for(i in seq_along(readClassList)){ readClassSe = readClassList[[i]] - if (is.character(readClassSe)){ - readClassSe <- readRDS(file = readClassSe)} - warnings[[i]] = NA - if(!is.null(metadata(readClassSe)$warnings)){ - warnings[[i]] = metadata(readClassSe)$warnings} + if (is.character(readClassSe)) + readClassSe <- readRDS(file = readClassSe) + warnings[[i]] = metadata(readClassSe)$warnings sampleNames = c(sampleNames, colnames(readClassList[[i]])) } names(warnings) = sampleNames - if(verbose & any(!is.na(warnings))){ + if(verbose & any(lengths(warnings)>0)){ message("--- per sample warnings during read class construction ---") - warnings.tmp = warnings[!is.na(warnings)] - for(i in seq_along(warnings.tmp)){ - message("Warnings for: ", names(warnings.tmp)[i]) - sapply(warnings.tmp[[i]], message) + for(i in seq_along(warnings)){ + if(lengths(warnings)[i]>0){ + message("Warnings for: ", sampleNames[i]) + sapply(warnings[[i]], message) + } } } else { - warningCount = sum(lengths(warnings[!is.na(warnings)])) - if(warningCount > 0){ - message("Detected ", warningCount, " warnings across the samples during ", - "read class construction. Access warnings with metadata(bambuOutput)$warnings")} + message("Detected ", sum(lengths(warnings)), " warnings across the samples during ", + "read class construction. Access warnings with metadata(bambuOutput)$warnings") } return(warnings) } diff --git a/R/prepareDataFromBam.R b/R/prepareDataFromBam.R index 09cf5ae7..d595d6f1 100755 --- a/R/prepareDataFromBam.R +++ b/R/prepareDataFromBam.R @@ -7,7 +7,7 @@ #' @importFrom GenomicAlignments grglist readGAlignments #' @importFrom GenomicRanges width #' @noRd -prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE, use.names = FALSE) { +prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE, use.names = FALSE, demultiplexed = NULL) { if (is(bamFile, "BamFile")) { if (!is.null(yieldSize)) { yieldSize(bamFile) <- yieldSize @@ -25,15 +25,34 @@ prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE, use.n bf <- open(bamFile) readGrgList <- list() counter <- 1 + cells <- c() + umi <- c() + while (isIncomplete(bf)) { readGrgList[[counter]] <- grglist(readGAlignments(bf, param = ScanBamParam(flag = scanBamFlag(isSecondaryAlignment = FALSE)), use.names = use.names)) + + ### add ### + if (isTRUE(demultiplexed)){ + mcols(readGrgList[[counter]])$CB <- substr(names(readGrgList[[counter]]), 1, 16) + mcols(readGrgList[[counter]])$UMI <- substr(names(readGrgList[[counter]]), 18, 29) + names(readGrgList[[counter]]) <- NULL + cells <- unique(c(cells, mcols(readGrgList[[counter]])$CB)) + mcols(readGrgList[[counter]])$CB <- factor(mcols(readGrgList[[counter]])$CB, levels = cells) + + umi <- unique(c(umi, mcols(readGrgList[[counter]])$UMI)) + mcols(readGrgList[[counter]])$UMI <- factor(mcols(readGrgList[[counter]])$UMI, levels = umi) + } + ### add ### + counter <- counter + 1 } on.exit(close(bf)) + rm(cells) + rm(umi) if (length(readGrgList) > 1) { readGrgList <- do.call(c, readGrgList) } else { @@ -41,7 +60,7 @@ prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE, use.n } # remove microexons of width 1bp from list readGrgList <- readGrgList[width(readGrgList) > 1] - mcols(readGrgList)$id <- seq_along(readGrgList) + return(readGrgList) } diff --git a/R/readWrite.R b/R/readWrite.R index 44e98de9..b317267d 100644 --- a/R/readWrite.R +++ b/R/readWrite.R @@ -35,9 +35,20 @@ writeBambuOutput <- function(se, path, prefix = "") { writeCountsOutput(se, varname=d, feature='transcript',outdir, prefix) } - seGene <- transcriptToGeneExpression(se) - writeCountsOutput(seGene, varname='counts', - feature='gene',outdir, prefix) + + seGene <- transcriptToGeneExpression(se[,1]) + + for (i in seq(ceiling(length(colnames(se)) / 100))){ + if (i == ceiling(length(colnames(se)) / 100)){ + seGene <- cbind(seGene, transcriptToGeneExpression(se[,(100*i-99):length(colnames(se))])) + } else{ + seGene <- cbind(seGene, transcriptToGeneExpression(se[,(100*i-99):(100*i)])) + } + } + + seGene <- seGene[,-1] + + writeCountsOutput(seGene, varname='counts', feature='gene',outdir, prefix) } } @@ -46,19 +57,36 @@ writeBambuOutput <- function(se, path, prefix = "") { #' @noRd writeCountsOutput <- function(se, varname = "counts", feature = "transcript", outdir, prefix){ - estimates <- data.table(as.data.frame(assays(se)[[varname]]), - keep.rownames = TRUE) - if(feature == "transcript"){ + + estimatesfn <- paste(outdir, prefix, varname,"_",feature,".txt", sep = "") + if(!is(assays(se)[[varname]], "sparseMatrix")){ + estimates <- data.table(as.data.frame(assays(se)[[varname]]), + keep.rownames = TRUE) + if(feature == "transcript"){ setnames(estimates, "rn", "TXNAME") geneIDs <- data.table(as.data.frame(rowData(se))[,c("TXNAME","GENEID")]) estimates <- geneIDs[estimates, on = "TXNAME"] - }else{ + }else{ setnames(estimates, "rn","GENEID") + } + + utils::write.table(estimates, file = estimatesfn, sep = "\t", quote = FALSE, row.names = FALSE) + + } else{ + estimates <- assays(se)[[varname]] + if (feature == "transcript"){ + Matrix::writeMM(estimates, estimatesfn) + geneIDs <- data.table(as.data.frame(rowData(se))[,c("TXNAME","GENEID")]) + utils::write.table(geneIDs, file = paste0(outdir, "txANDgenes.txt"), + sep = "\t", quote = FALSE, row.names = FALSE, col.names = FALSE) + utils::write.table(colnames(se), file = paste0(outdir, "barcodes.txt"), quote = FALSE, row.names = FALSE, col.names = FALSE) + + } else{ + Matrix::writeMM(estimates, estimatesfn) + utils::write.table(names(se), file = paste0(outdir, "genes.txt"), + sep = "\t", quote = FALSE, row.names = FALSE, col.names = FALSE) + } } - estimatesfn <- paste(outdir, prefix, - varname,"_",feature,".txt", sep = "") - utils::write.table(estimates, file = estimatesfn, - sep = "\t", quote = FALSE, row.names = FALSE) } #' Write annotation GRangesList into a GTF file diff --git a/R/transcriptToGeneExpression.R b/R/transcriptToGeneExpression.R index 9cf7604b..b145a2ac 100644 --- a/R/transcriptToGeneExpression.R +++ b/R/transcriptToGeneExpression.R @@ -11,7 +11,7 @@ #' )) #' transcriptToGeneExpression(se) transcriptToGeneExpression <- function(se) { - counts <- as.data.table(assays(se)$counts, keep.rownames = TRUE) + counts <- as.data.table(as.matrix(assays(se)$counts), keep.rownames = TRUE) runnames <- colnames(counts)[-1] colnames(counts)[-1] <- rename_duplicatedNames(runnames) colData(se)@rownames <- rename_duplicatedNames(colData(se)@rownames) @@ -63,5 +63,11 @@ transcriptToGeneExpression <- function(se) { dimnames = list(RowNames, ColNames))), rowRanges = exByGene[RowNames], colData = ColData) + + if(is(assays(se)$counts, "sparseMatrix")) { + assays(seOutput)$counts <- as(assays(seOutput)$counts, "sparseMatrix") + assays(seOutput)$CPM <- as(assays(seOutput)$CPM, "sparseMatrix") + } + return(seOutput) } \ No newline at end of file From 245661774189b14dfd4b61b9ee2a610ac12e1738 Mon Sep 17 00:00:00 2001 From: Andre Date: Tue, 3 Oct 2023 13:24:14 +0800 Subject: [PATCH 048/189] bug fix the merge --- R/bambu-processReads.R | 38 +++++++--------------- R/bambu.R | 72 +++++++++++++++++------------------------- 2 files changed, 41 insertions(+), 69 deletions(-) diff --git a/R/bambu-processReads.R b/R/bambu-processReads.R index be2244ce..17a46dad 100644 --- a/R/bambu-processReads.R +++ b/R/bambu-processReads.R @@ -52,7 +52,7 @@ bambu.processReads <- function(reads, annotations, genomeSequence, stranded = stranded, min.readCount = min.readCount, fitReadClassModel = fitReadClassModel, min.exonOverlap = min.exonOverlap, defaultModels = defaultModels, returnModel = returnModel, verbose = verbose, - lowMemory = lowMemory, trackReads = trackReads, fusionMode = fusionMode, index = i, rgrLists = rgrLists)}, + lowMemory = lowMemory, trackReads = trackReads, fusionMode = fusionMode, demultiplexed = FALSE, index = i)}, BPPARAM = bpParameters) readGrgList = do.call(c, readGrgList) mcols(readGrgList)$id <- seq_along(readGrgList) @@ -65,7 +65,6 @@ bambu.processReads <- function(reads, annotations, genomeSequence, lowMemory = lowMemory, trackReads = trackReads, fusionMode = fusionMode) metadata(readClassList)$samples = names(reads) countMatrix = splitReadClassFiles(readClassList) - colnames(countMatrix) = metadata(readClassList)$samples rownames(countMatrix) = rownames(readClassList) metadata(readClassList)$countMatrix = countMatrix @@ -106,14 +105,9 @@ bambu.processReads <- function(reads, annotations, genomeSequence, bambu.processReadsByFile <- function(bam.file, genomeSequence, annotations, readClass.outputDir = NULL, yieldSize = NULL, stranded = FALSE, min.readCount = 2, fitReadClassModel = TRUE, min.exonOverlap = 10, defaultModels = NULL, returnModel = FALSE, - verbose = FALSE, lowMemory = FALSE, trackReads = FALSE, fusionMode = FALSE, index = 0, rgrLists = FALSE) { - #if(verbose) message(names(bam.file)[1]) - if(rgrLists){ - print(bam.file) - readGrgList <- readRDS(bam.file) - } else{ - readGrgList <- prepareDataFromBam(bam.file[[1]], verbose = verbose, use.names = trackReads) - } + verbose = FALSE, lowMemory = FALSE, trackReads = FALSE, fusionMode = FALSE, demultiplexed = FALSE, index = 0) { + + readGrgList <- prepareDataFromBam(bam.file[[1]], verbose = verbose, use.names = trackReads, demultiplexed) warnings = c() warnings = seqlevelCheckReadsAnnotation(readGrgList, annotations) @@ -167,23 +161,15 @@ bambu.processReadsByFile <- function(bam.file, genomeSequence, annotations, if (isTRUE(demultiplexed)){ cellBarcodeAssign <- tibble(index = mcols(readGrgList)$id, CB = mcols(readGrgList)$CB) %>% nest(.by = "CB") - if (!dir.exists("CB")){ - dir.create("CB") - } else{ - unlink(paste("CB", "*", sep = "/")) - } + # if (!dir.exists("CB")){ + # dir.create("CB") + # } else{ + # unlink(paste("CB", "*", sep = "/")) + # } - invisible(lapply(seq(nrow(cellBarcodeAssign)), - function(x){saveRDS(readGrgList[pull(cellBarcodeAssign$data[[x]])], paste0("CB/", cellBarcodeAssign$CB[[x]],".rds"))})) - } - ## add ### - - ### add ### - } else { - - readGrgList <- readRDS(bam.file[[1]]) - - } + # invisible(lapply(seq(nrow(cellBarcodeAssign)), + # function(x){saveRDS(readGrgList[pull(cellBarcodeAssign$data[[x]])], paste0("CB/", cellBarcodeAssign$CB[[x]],".rds"))})) + } return(readGrgList) } diff --git a/R/bambu.R b/R/bambu.R index c2a02376..ca11c399 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -139,7 +139,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, opt.discovery = NULL, opt.em = NULL, rcOutDir = NULL, discovery = TRUE, quant = TRUE, stranded = FALSE, ncore = 1, yieldSize = NULL, trackReads = FALSE, returnDistTable = FALSE, lowMemory = FALSE, - fusionMode = FALSE, verbose = FALSE, rgrLists = FALSE) { + fusionMode = FALSE, verbose = FALSE, demultiplexed = FALSE) { if(is.null(annotations)) { annotations = GRangesList() } else annotations <- checkInputs(annotations, reads, readClass.outputDir = rcOutDir, genomeSequence = genome) @@ -155,7 +155,6 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, isRDSs = all(sapply(reads, class)=="RangedSummarizedExperiment") isBamFiles = !isRDSs if(!isRDSs) isBamFiles = ifelse(!is(reads, "BamFileList"), all(grepl(".bam$", reads)), FALSE) - #if(rgrLists){ if (isBamFiles | is(reads, "BamFileList")) { if (length(reads) > 10 & (is.null(rcOutDir))) { rcOutDir <- tempdir() #>=10 samples, save to temp folder @@ -170,31 +169,14 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, readClass.outputDir = rcOutDir, yieldSize, bpParameters, stranded, verbose, isoreParameters, trackReads = trackReads, fusionMode = fusionMode, - lowMemory = lowMemory, rgrLists = rgrLists) + lowMemory = lowMemory, demultiplexed = FALSE) } - #warnings = handleWarnings(readClassList, verbose) - if (!discovery & !quant) return(readClassList) - if (discovery) { - message("--- Start extending annotations ---") - annotations <- bambu.extendAnnotations(readClassList, annotations, NDR, - isoreParameters, stranded, bpParameters, fusionMode, verbose) - metadata(annotations)$warnings = warnings - if (!quant) return(annotations) - } - message("--- Start generating read class files ---") - - readClassList <- bambu.processReads(reads, annotations, - genomeSequence = genome, - readClass.outputDir = rcOutDir, yieldSize = yieldSize, - bpParameters, stranded, verbose, - isoreParameters, trackReads = trackReads, fusionMode = fusionMode, - lowMemory = lowMemory, demultiplexed = demultiplexed, readGrgListFile = readGrgListFile) - } - if (is.null(readGrgListFile)) warnings = handleWarnings(readClassList, verbose) + + #warnings = handleWarnings(readClassList, verbose) if (!discovery & !quant) return(readClassList) if (discovery) { message("--- Start extending annotations ---") - annotations <- bambu.extendAnnotations(readClassList, annotations, NDR, + annotations <- bambu.extendAnnotations(list(readClassList), annotations, NDR, isoreParameters, stranded, bpParameters, fusionMode, verbose) metadata(annotations)$warnings = warnings @@ -216,34 +198,36 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, verbose = verbose) metadata(readClassDist)$distTable <- modifyIncompatibleAssignment(metadata(readClassDist)$distTable) metadata(readClassDist)$distTable <- genEquiRCsBasedOnObservedReads(readClassDist) - countMatrix2 = metadata(readClassList)$countMatrix[metadata(readClassDist)$distTable$readClassId,] + countMatrix2 = as.matrix(metadata(readClassList)$countMatrix[metadata(readClassDist)$distTable$readClassId,]) + colnames(countMatrix2) = colnames(metadata(readClassList)$countMatrix) readClassDt <- genEquiRCs(readClassDist, annotations, verbose) - countsSe <- bplapply(seq_len(ncol(countMatrix2)), bambu.quantify, - readClassDist = readClassDist, readClassDt = readClassDt, countMatrix = countMatrix2, - annotations = annotations, isoreParameters = isoreParameters, - emParameters = emParameters, trackReads = trackReads, - returnDistTable = returnDistTable, verbose = verbose, - BPPARAM = bpParameters) - countsSe <- combineCountSes(countsSe) - rowRanges(countsSe) <- annotations - #metadata(countsSe)$warnings = warnings - if (trackReads) metadata(seOutput)$readToTranscriptMap = - generateReadToTranscriptMap(readClass, metadata(readClassDist)$distTable, - annotations) - if (returnDistTable) metadata(seOutput)$distTable = metadata(readClassDist)$distTable - if (rm.readClassSe) file.remove(unlist(readClassList)) - message("--- Finished running Bambu ---") - return(countsSe) + # countsSe <- bplapply(seq_len(ncol(countMatrix2)), bambu.quantify, + # readClassDist = readClassDist, readClassDt = readClassDt, countMatrix = countMatrix2, + # annotations = annotations, isoreParameters = isoreParameters, + # emParameters = emParameters, trackReads = trackReads, + # returnDistTable = returnDistTable, verbose = verbose, + # BPPARAM = bpParameters) + # countsSe <- combineCountSes(countsSe) + # rowRanges(countsSe) <- annotations + # #metadata(countsSe)$warnings = warnings + # if (trackReads) metadata(seOutput)$readToTranscriptMap = + # generateReadToTranscriptMap(readClass, metadata(readClassDist)$distTable, + # annotations) + # if (returnDistTable) metadata(seOutput)$distTable = metadata(readClassDist)$distTable + # if (rm.readClassSe) file.remove(unlist(readClassList)) + # message("--- Finished running Bambu ---") + # return(countsSe) ###MESSYFOREST sparsematrix - countsSeCompressed <- bplapply(info$rpath, bambu.quantify, + countsSeCompressed <- bplapply(seq_len(ncol(countMatrix2)), bambu.quantify, + readClassDist = readClassDist, readClassDt = readClassDt, countMatrix = countMatrix2, annotations = annotations, isoreParameters = isoreParameters, emParameters = emParameters, trackReads = trackReads, returnDistTable = returnDistTable, verbose = verbose, - readGrgListFile = readGrgListFile, BPPARAM = bpParameters) + print("bambu.quantify finished") ### countsData countsData <- c("incompatibleCounts", "counts", "CPM", "fullLengthCounts", "uniqueCounts") @@ -277,6 +261,8 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, metadata(countsSe)$incompatibleCounts <- countsDataMat$incompatibleCounts rowRanges(countsSe) <- annotations - metadata(countsSe)$warnings = warnings + #metadata(countsSe)$warnings = warnings + + return(countsSe) } } From fc19125e7403b2e7255dfbca3bba77fde08fc8f2 Mon Sep 17 00:00:00 2001 From: Andre Date: Tue, 3 Oct 2023 15:01:01 +0800 Subject: [PATCH 049/189] Clean up combining SEs --- R/bambu.R | 98 ++++++++++---------------------------- R/bambu_utilityFunctions.R | 34 +++++++++---- 2 files changed, 50 insertions(+), 82 deletions(-) diff --git a/R/bambu.R b/R/bambu.R index ca11c399..ba6ac719 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -173,21 +173,21 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, } #warnings = handleWarnings(readClassList, verbose) - if (!discovery & !quant) return(readClassList) - if (discovery) { - message("--- Start extending annotations ---") - annotations <- bambu.extendAnnotations(list(readClassList), annotations, NDR, - isoreParameters, stranded, bpParameters, fusionMode, verbose) - metadata(annotations)$warnings = warnings - - if (!quant) return(annotations) - } + if (!discovery & !quant) return(readClassList) + if (discovery) { + message("--- Start extending annotations ---") + annotations <- bambu.extendAnnotations(list(readClassList), annotations, NDR, + isoreParameters, stranded, bpParameters, fusionMode, verbose) + metadata(annotations)$warnings = warnings + + if (!quant) return(annotations) + } - if (quant) { + if (quant) { - message("--- Start isoform quantification ---") - if(length(annotations)==0) stop("No valid annotations, if running - de novo please try less stringent parameters") + message("--- Start isoform quantification ---") + if(length(annotations)==0) stop("No valid annotations, if running + de novo please try less stringent parameters") if (is.character(readClassList)) readClassList <- readRDS(file = readClassList) if(is.list(readClassList)) readClassList = readClassList[[1]] @@ -201,68 +201,20 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, countMatrix2 = as.matrix(metadata(readClassList)$countMatrix[metadata(readClassDist)$distTable$readClassId,]) colnames(countMatrix2) = colnames(metadata(readClassList)$countMatrix) readClassDt <- genEquiRCs(readClassDist, annotations, verbose) - # countsSe <- bplapply(seq_len(ncol(countMatrix2)), bambu.quantify, - # readClassDist = readClassDist, readClassDt = readClassDt, countMatrix = countMatrix2, - # annotations = annotations, isoreParameters = isoreParameters, - # emParameters = emParameters, trackReads = trackReads, - # returnDistTable = returnDistTable, verbose = verbose, - # BPPARAM = bpParameters) - # countsSe <- combineCountSes(countsSe) - # rowRanges(countsSe) <- annotations - # #metadata(countsSe)$warnings = warnings - # if (trackReads) metadata(seOutput)$readToTranscriptMap = - # generateReadToTranscriptMap(readClass, metadata(readClassDist)$distTable, - # annotations) - # if (returnDistTable) metadata(seOutput)$distTable = metadata(readClassDist)$distTable - # if (rm.readClassSe) file.remove(unlist(readClassList)) - # message("--- Finished running Bambu ---") - # return(countsSe) - - - ###MESSYFOREST sparsematrix countsSeCompressed <- bplapply(seq_len(ncol(countMatrix2)), bambu.quantify, - readClassDist = readClassDist, readClassDt = readClassDt, countMatrix = countMatrix2, - annotations = annotations, isoreParameters = isoreParameters, - emParameters = emParameters, trackReads = trackReads, - returnDistTable = returnDistTable, verbose = verbose, - BPPARAM = bpParameters) - print("bambu.quantify finished") - - ### countsData - countsData <- c("incompatibleCounts", "counts", "CPM", "fullLengthCounts", "uniqueCounts") - countsDataMat <- list() - - for (k in seq_along(countsData)){ - countsVecList <- lapply(seq_along(countsSeCompressed), function(j){countsSeCompressed[[j]][[countsData[k]]]}) - - countsMat <- sparseMatrix(i = unlist(lapply(seq_along(countsVecList), function(j){countsVecList[[j]]@i})), - j = unlist(lapply(seq_along(countsVecList), function(j){rep(j, length(countsVecList[[j]]@i))})), - x = unlist(lapply(seq_along(countsVecList), function(j){countsVecList[[j]]@x})), - dims = c(length(countsVecList[[1]]), length(countsVecList))) - - colnames(countsMat) <- unlist(lapply(seq_along(countsSeCompressed), function(j){countsSeCompressed[[j]]$colnames})) - - if (countsData[k] == "incompatibleCounts"){ - countsMat <- data.table(as.data.frame(as.matrix(countsMat)) %>% - mutate(GENEID = unique(mcols(annotations)$GENEID)) %>% - select(GENEID, everything())) - } - - countsDataMat[[countsData[k]]] <- countsMat - } - - countsSe <- SummarizedExperiment(assays = SimpleList(counts = countsDataMat$counts, - CPM = countsDataMat$CPM, - fullLengthCounts = countsDataMat$fullLengthCounts, - uniqueCounts = countsDataMat$uniqueCounts), - colData = as(bind_rows(lapply(lapply(seq_along(countsSeCompressed), - function(j){countsSeCompressed[[j]]$colData}), as.data.frame)), "DataFrame")) - - metadata(countsSe)$incompatibleCounts <- countsDataMat$incompatibleCounts - rowRanges(countsSe) <- annotations - #metadata(countsSe)$warnings = warnings + readClassDist = readClassDist, readClassDt = readClassDt, countMatrix = countMatrix2, + annotations = annotations, isoreParameters = isoreParameters, + emParameters = emParameters, trackReads = trackReads, + returnDistTable = returnDistTable, verbose = verbose, + BPPARAM = bpParameters) + countsSe <- combineCountSes(countsSe, annotations) - return(countsSe) + #metadata(countsSe)$warnings = warnings + # if (trackReads) metadata(seOutput)$readToTranscriptMap = + # generateReadToTranscriptMap(readClass, metadata(readClassDist)$distTable, + # annotations) + # if (returnDistTable) metadata(seOutput)$distTable = metadata(readClassDist)$distTable + return(countsSe) } } diff --git a/R/bambu_utilityFunctions.R b/R/bambu_utilityFunctions.R index b7fcb88e..347a4268 100644 --- a/R/bambu_utilityFunctions.R +++ b/R/bambu_utilityFunctions.R @@ -209,15 +209,31 @@ handleWarnings <- function(readClassList, verbose){ #' Combine count se object while preserving the metadata objects #' @noRd -combineCountSes <- function(countsSe, trackReads = FALSE, returnDistTable = FALSE){ - sampleNames = sapply(countsSe, FUN = function(x){colnames(x)}) - # combine incompatible counts - incompatibleCounts = Reduce(merge_wrapper, lapply(countsSe, FUN = function(se){metadata(se)$incompatibleCounts})) - countsSe = lapply(countsSe, FUN = function(se){ - metadata(se)$incompatibleCounts=NULL - return(se)}) - countsSe <- do.call(SummarizedExperiment::cbind, countsSe) - metadata(countsSe)$incompatibleCounts = incompatibleCounts +combineCountSes <- function(countsSe, annotations){ + countsData <- c("counts", "CPM", "fullLengthCounts", "uniqueCounts", "incompatibleCounts") + sampleNames = sapply(countsSeCompressed, FUN = function(x){x$colnames}) + countsDataMat <- lapply(countsData, FUN = function(k){ + countsVecList <- lapply(countsSeCompressed, function(j){j[[k]]}) + countsMat <- sparseMatrix(i = unlist(lapply(countsVecList, function(j){j@i})), + j = unlist(lapply(seq_along(countsVecList), function(j){rep(j, length(countsVecList[[j]]@i))})), + x = unlist(lapply(countsVecList, function(j){j@x})), + dims = c(length(countsVecList[[1]]), length(countsVecList))) + if(all(countsMat==0)){return(NULL)} + colnames(countsMat) <- sampleNames + if (k == "incompatibleCounts"){ + countsMat <- data.table(as.data.frame(as.matrix(countsMat)) %>% + mutate(GENEID = unique(mcols(annotations)$GENEID)) %>% + select(GENEID, everything())) + } + return(countsMat) + }) + names(countsDataMat) = countsData + countsSe <- SummarizedExperiment(assays = SimpleList(counts = countsDataMat$counts, + CPM = countsDataMat$CPM, + fullLengthCounts = countsDataMat$fullLengthCounts, + uniqueCounts = countsDataMat$uniqueCounts)) + metadata(countsSe)$incompatibleCounts <- countsDataMat$incompatibleCounts + rowRanges(countsSe) <- annotations return(countsSe) } From 06233227e1aaae6a6a7ab4e931658c6e2563b2b7 Mon Sep 17 00:00:00 2001 From: Andre Date: Wed, 4 Oct 2023 14:56:18 +0800 Subject: [PATCH 050/189] Enable demultiplexing and speed up splitReadClassFiles() --- R/bambu-processReads.R | 45 +++++++++++++++--------------------------- R/bambu.R | 2 +- R/prepareDataFromBam.R | 18 ++++++++--------- 3 files changed, 25 insertions(+), 40 deletions(-) diff --git a/R/bambu-processReads.R b/R/bambu-processReads.R index 17a46dad..ccac9829 100644 --- a/R/bambu-processReads.R +++ b/R/bambu-processReads.R @@ -52,7 +52,7 @@ bambu.processReads <- function(reads, annotations, genomeSequence, stranded = stranded, min.readCount = min.readCount, fitReadClassModel = fitReadClassModel, min.exonOverlap = min.exonOverlap, defaultModels = defaultModels, returnModel = returnModel, verbose = verbose, - lowMemory = lowMemory, trackReads = trackReads, fusionMode = fusionMode, demultiplexed = FALSE, index = i)}, + lowMemory = lowMemory, trackReads = trackReads, fusionMode = fusionMode, demultiplexed = demultiplexed, index = i)}, BPPARAM = bpParameters) readGrgList = do.call(c, readGrgList) mcols(readGrgList)$id <- seq_along(readGrgList) @@ -63,7 +63,10 @@ bambu.processReads <- function(reads, annotations, genomeSequence, fitReadClassModel = fitReadClassModel, min.exonOverlap = min.exonOverlap, defaultModels = defaultModels, returnModel = returnModel, verbose = verbose, lowMemory = lowMemory, trackReads = trackReads, fusionMode = fusionMode) + metadata(readClassList)$samples = names(reads) + if(demultiplexed)metadata(readClassList)$samples = metadata(readGrgList)$CB + return(readClassList) countMatrix = splitReadClassFiles(readClassList) colnames(countMatrix) = metadata(readClassList)$samples rownames(countMatrix) = rownames(readClassList) @@ -106,9 +109,7 @@ bambu.processReadsByFile <- function(bam.file, genomeSequence, annotations, readClass.outputDir = NULL, yieldSize = NULL, stranded = FALSE, min.readCount = 2, fitReadClassModel = TRUE, min.exonOverlap = 10, defaultModels = NULL, returnModel = FALSE, verbose = FALSE, lowMemory = FALSE, trackReads = FALSE, fusionMode = FALSE, demultiplexed = FALSE, index = 0) { - - readGrgList <- prepareDataFromBam(bam.file[[1]], verbose = verbose, use.names = trackReads, demultiplexed) - + readGrgList <- prepareDataFromBam(bam.file[[1]], verbose = verbose, yieldSize = yieldSize, use.names = trackReads, demultiplexed = demultiplexed) warnings = c() warnings = seqlevelCheckReadsAnnotation(readGrgList, annotations) if(verbose & length(warnings) > 0) warning(paste(warnings,collapse = "\n")) @@ -135,7 +136,10 @@ bambu.processReadsByFile <- function(bam.file, genomeSequence, annotations, # reassign Ids after seqlevels are dropped mcols(readGrgList)$id <- seq_along(readGrgList) } - mcols(readGrgList)$sampleID = index + if(demultiplexed){ + metadata(readGrgList)$CB = levels(mcols(readGrgList)$CB) + mcols(readGrgList)$sampleID = mcols(readGrgList)$sampleID = as.numeric(mcols(readGrgList)$CB) + } else {mcols(readGrgList)$sampleID = index} #removes reads that are outside genome coordinates badReads = which(max(end(ranges(readGrgList)))>= seqlengths(genomeSequence)[as.character(getChrFromGrList(readGrgList))]) @@ -257,28 +261,11 @@ seqlevelCheckReadsAnnotation <- function(reads, annotations){ } splitReadClassFiles = function(readClassFile){ - rowIndex = c() - sampleCount = c() - counts = c() - for(i in seq_along(metadata(readClassFile)$samples)){ - counts.sample = sapply(rowData(readClassFile)$sampleIDs, FUN = function(x){sum(x==i)}) - counts = c(counts, counts.sample[counts.sample != 0]) - rowIndex = c(rowIndex, which(counts.sample != 0)) - sampleCount = c(sampleCount, sum(counts.sample !=0)) - } - counts = sparseMatrix(i = rowIndex, - j = rep(seq_along(metadata(readClassFile)$samples), sampleCount), - x = counts) - -# countMat = sapply(seq_along(metadata(readClassFile)$samples), FUN = function(i){ -# counts.sample = sapply(rowData(readClassFile)$sampleIDs, FUN = function(x){sum(x==i)}) -# return(c(counts.sample[counts.sample != 0], #counts -# which(counts.sample != 0)), #rowindex -# sum(counts.sample !=0)) #sampleCount -# }) -# counts = sparseMatrix(i = countMat[2,], -# j = rep(seq_along(metadata(readClassFile)$samples), countMat[3,]), -# x = countMat[1,]) - - return(counts) + counts.table = lapply(rowData(readClassFile)$sampleIDs, FUN = function(x){table(x)}) + counts = sparseMatrix( + i = rep(seq_along(counts.table), lengths(counts.table)), + j = as.numeric(names(unlist(counts.table))), + x = unlist(counts.table), + dims = c(nrow(readClassFile), length(metadata(readClassFile)$samples))) + return(counts) } diff --git a/R/bambu.R b/R/bambu.R index ba6ac719..26c66549 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -169,7 +169,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, readClass.outputDir = rcOutDir, yieldSize, bpParameters, stranded, verbose, isoreParameters, trackReads = trackReads, fusionMode = fusionMode, - lowMemory = lowMemory, demultiplexed = FALSE) + lowMemory = lowMemory, demultiplexed = demultiplexed) } #warnings = handleWarnings(readClassList, verbose) diff --git a/R/prepareDataFromBam.R b/R/prepareDataFromBam.R index d595d6f1..f2e7cd26 100755 --- a/R/prepareDataFromBam.R +++ b/R/prepareDataFromBam.R @@ -27,24 +27,22 @@ prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE, use.n counter <- 1 cells <- c() umi <- c() - + if(demultiplexed) use.names = TRUE while (isIncomplete(bf)) { readGrgList[[counter]] <- grglist(readGAlignments(bf, param = ScanBamParam(flag = scanBamFlag(isSecondaryAlignment = FALSE)), use.names = use.names)) - ### add ### if (isTRUE(demultiplexed)){ - mcols(readGrgList[[counter]])$CB <- substr(names(readGrgList[[counter]]), 1, 16) - mcols(readGrgList[[counter]])$UMI <- substr(names(readGrgList[[counter]]), 18, 29) - names(readGrgList[[counter]]) <- NULL - cells <- unique(c(cells, mcols(readGrgList[[counter]])$CB)) - mcols(readGrgList[[counter]])$CB <- factor(mcols(readGrgList[[counter]])$CB, levels = cells) - - umi <- unique(c(umi, mcols(readGrgList[[counter]])$UMI)) - mcols(readGrgList[[counter]])$UMI <- factor(mcols(readGrgList[[counter]])$UMI, levels = umi) + mcols(readGrgList[[counter]])$CB <- substr(names(readGrgList[[counter]]), 1, 16) + mcols(readGrgList[[counter]])$UMI <- substr(names(readGrgList[[counter]]), 18, 29) + names(readGrgList[[counter]]) <- NULL + cells <- unique(c(cells, mcols(readGrgList[[counter]])$CB)) + mcols(readGrgList[[counter]])$CB <- factor(mcols(readGrgList[[counter]])$CB, levels = cells) + umi <- unique(c(umi, mcols(readGrgList[[counter]])$UMI)) + mcols(readGrgList[[counter]])$UMI <- factor(mcols(readGrgList[[counter]])$UMI, levels = umi) } ### add ### From 32b569274102fe37bf4a207c630ae1be18acd107 Mon Sep 17 00:00:00 2001 From: Andre Date: Wed, 4 Oct 2023 15:00:05 +0800 Subject: [PATCH 051/189] fix formatting issues --- R/bambu-processReads.R | 20 ++++---------------- 1 file changed, 4 insertions(+), 16 deletions(-) diff --git a/R/bambu-processReads.R b/R/bambu-processReads.R index ccac9829..401864b6 100644 --- a/R/bambu-processReads.R +++ b/R/bambu-processReads.R @@ -66,7 +66,6 @@ bambu.processReads <- function(reads, annotations, genomeSequence, metadata(readClassList)$samples = names(reads) if(demultiplexed)metadata(readClassList)$samples = metadata(readGrgList)$CB - return(readClassList) countMatrix = splitReadClassFiles(readClassList) colnames(countMatrix) = metadata(readClassList)$samples rownames(countMatrix) = rownames(readClassList) @@ -87,17 +86,6 @@ bambu.processReads <- function(reads, annotations, genomeSequence, # saveRDS(se, file = readClassFile) # se <- readClassFile # } - - - # readClassList <- bplapply(names(reads), function(bamFileName) { - # bambu.processReadsByFile(bam.file = reads[bamFileName], - # genomeSequence = genomeSequence,annotations = annotations, - # readClass.outputDir = readClass.outputDir, - # stranded = stranded, min.readCount = min.readCount, - # fitReadClassModel = fitReadClassModel, min.exonOverlap = min.exonOverlap, - # defaultModels = defaultModels, returnModel = returnModel, verbose = verbose, - # lowMemory = lowMemory, trackReads = trackReads, fusionMode = fusionMode)}, - # BPPARAM = bpParameters) return(readClassList) } @@ -263,9 +251,9 @@ seqlevelCheckReadsAnnotation <- function(reads, annotations){ splitReadClassFiles = function(readClassFile){ counts.table = lapply(rowData(readClassFile)$sampleIDs, FUN = function(x){table(x)}) counts = sparseMatrix( - i = rep(seq_along(counts.table), lengths(counts.table)), - j = as.numeric(names(unlist(counts.table))), - x = unlist(counts.table), - dims = c(nrow(readClassFile), length(metadata(readClassFile)$samples))) + i = rep(seq_along(counts.table), lengths(counts.table)), + j = as.numeric(names(unlist(counts.table))), + x = unlist(counts.table), + dims = c(nrow(readClassFile), length(metadata(readClassFile)$samples))) return(counts) } From c2b3bf5fb78b2150870f56e4f349a2f199536a14 Mon Sep 17 00:00:00 2001 From: Andre Date: Wed, 4 Oct 2023 16:05:10 +0800 Subject: [PATCH 052/189] fix bugs --- R/bambu-processReads.R | 3 ++- R/bambu-quantify.R | 2 ++ R/bambu.R | 6 +++--- R/bambu_utilityFunctions.R | 4 ++-- 4 files changed, 9 insertions(+), 6 deletions(-) diff --git a/R/bambu-processReads.R b/R/bambu-processReads.R index 401864b6..6d880596 100644 --- a/R/bambu-processReads.R +++ b/R/bambu-processReads.R @@ -86,7 +86,8 @@ bambu.processReads <- function(reads, annotations, genomeSequence, # saveRDS(se, file = readClassFile) # se <- readClassFile # } - return(readClassList) + #TODO don't output list, current there because discovery needs it + return(list(readClassList)) } #' Preprocess bam files and save read class files diff --git a/R/bambu-quantify.R b/R/bambu-quantify.R index 0a4d5e70..e7def6c1 100644 --- a/R/bambu-quantify.R +++ b/R/bambu-quantify.R @@ -5,6 +5,8 @@ bambu.quantify <- function(i, readClassDist, readClassDt, countMatrix, annotations, emParameters, trackReads = FALSE, returnDistTable = FALSE, verbose = FALSE, isoreParameters = setIsoreParameters(NULL)) { + print(i) + #TODO do not alter readClassDist and readClassDT objects to save memory metadata(readClassDist)$distTable$readCount <- countMatrix[,i] metadata(readClassDist)$distTable = metadata(readClassDist)$distTable[metadata(readClassDist)$distTable$readCount != 0,] readClassDt$nobs = calculateEqClassCounts(metadata(readClassDist)$distTable, readClassDt) diff --git a/R/bambu.R b/R/bambu.R index 26c66549..369be17e 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -176,7 +176,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, if (!discovery & !quant) return(readClassList) if (discovery) { message("--- Start extending annotations ---") - annotations <- bambu.extendAnnotations(list(readClassList), annotations, NDR, + annotations <- bambu.extendAnnotations(readClassList, annotations, NDR, isoreParameters, stranded, bpParameters, fusionMode, verbose) metadata(annotations)$warnings = warnings @@ -201,14 +201,14 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, countMatrix2 = as.matrix(metadata(readClassList)$countMatrix[metadata(readClassDist)$distTable$readClassId,]) colnames(countMatrix2) = colnames(metadata(readClassList)$countMatrix) readClassDt <- genEquiRCs(readClassDist, annotations, verbose) - + print(ncol(countMatrix2)) countsSeCompressed <- bplapply(seq_len(ncol(countMatrix2)), bambu.quantify, readClassDist = readClassDist, readClassDt = readClassDt, countMatrix = countMatrix2, annotations = annotations, isoreParameters = isoreParameters, emParameters = emParameters, trackReads = trackReads, returnDistTable = returnDistTable, verbose = verbose, BPPARAM = bpParameters) - countsSe <- combineCountSes(countsSe, annotations) + countsSe <- combineCountSes(countsSeCompressed, annotations) #metadata(countsSe)$warnings = warnings # if (trackReads) metadata(seOutput)$readToTranscriptMap = diff --git a/R/bambu_utilityFunctions.R b/R/bambu_utilityFunctions.R index 347a4268..e728b3f8 100644 --- a/R/bambu_utilityFunctions.R +++ b/R/bambu_utilityFunctions.R @@ -211,9 +211,9 @@ handleWarnings <- function(readClassList, verbose){ #' @noRd combineCountSes <- function(countsSe, annotations){ countsData <- c("counts", "CPM", "fullLengthCounts", "uniqueCounts", "incompatibleCounts") - sampleNames = sapply(countsSeCompressed, FUN = function(x){x$colnames}) + sampleNames = sapply(countsSe, FUN = function(x){x$colnames}) countsDataMat <- lapply(countsData, FUN = function(k){ - countsVecList <- lapply(countsSeCompressed, function(j){j[[k]]}) + countsVecList <- lapply(countsSe, function(j){j[[k]]}) countsMat <- sparseMatrix(i = unlist(lapply(countsVecList, function(j){j@i})), j = unlist(lapply(seq_along(countsVecList), function(j){rep(j, length(countsVecList[[j]]@i))})), x = unlist(lapply(countsVecList, function(j){j@x})), From 7b3eb82734e9ed44879dad48246048aea7263238 Mon Sep 17 00:00:00 2001 From: Andre Date: Wed, 4 Oct 2023 16:17:32 +0800 Subject: [PATCH 053/189] Enable threading for demultiplexed samples --- R/bambu.R | 2 ++ 1 file changed, 2 insertions(+) diff --git a/R/bambu.R b/R/bambu.R index 369be17e..c75d69ab 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -202,6 +202,8 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, colnames(countMatrix2) = colnames(metadata(readClassList)$countMatrix) readClassDt <- genEquiRCs(readClassDist, annotations, verbose) print(ncol(countMatrix2)) + bpParameters$workers = ncore #TODO temp fix because currently its set to number of input files + bpParameters$progressbar = TRUE countsSeCompressed <- bplapply(seq_len(ncol(countMatrix2)), bambu.quantify, readClassDist = readClassDist, readClassDt = readClassDt, countMatrix = countMatrix2, annotations = annotations, isoreParameters = isoreParameters, From f68e30d767ee1c4afb9c91ec433548c1ab500b5c Mon Sep 17 00:00:00 2001 From: Andre Date: Wed, 4 Oct 2023 16:21:36 +0800 Subject: [PATCH 054/189] Remove progress bar --- R/bambu.R | 1 - 1 file changed, 1 deletion(-) diff --git a/R/bambu.R b/R/bambu.R index c75d69ab..926cab81 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -203,7 +203,6 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, readClassDt <- genEquiRCs(readClassDist, annotations, verbose) print(ncol(countMatrix2)) bpParameters$workers = ncore #TODO temp fix because currently its set to number of input files - bpParameters$progressbar = TRUE countsSeCompressed <- bplapply(seq_len(ncol(countMatrix2)), bambu.quantify, readClassDist = readClassDist, readClassDt = readClassDt, countMatrix = countMatrix2, annotations = annotations, isoreParameters = isoreParameters, From fe146680ee30ee1a7fb5549c457809f2dff325a0 Mon Sep 17 00:00:00 2001 From: Andre Date: Wed, 4 Oct 2023 16:30:19 +0800 Subject: [PATCH 055/189] adapt threading for demultiplexing --- R/bambu.R | 3 +-- R/bambu_utilityFunctions.R | 4 ++-- 2 files changed, 3 insertions(+), 4 deletions(-) diff --git a/R/bambu.R b/R/bambu.R index 926cab81..2e52800b 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -148,7 +148,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, if(!is.null(isoreParameters$max.txNDR)) NDR = isoreParameters$max.txNDR emParameters <- setEmParameters(emParameters = opt.em) - bpParameters <- setBiocParallelParameters(reads, ncore, verbose) + bpParameters <- setBiocParallelParameters(reads, ncore, verbose, demultiplexed) rm.readClassSe <- FALSE readClassList = reads @@ -202,7 +202,6 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, colnames(countMatrix2) = colnames(metadata(readClassList)$countMatrix) readClassDt <- genEquiRCs(readClassDist, annotations, verbose) print(ncol(countMatrix2)) - bpParameters$workers = ncore #TODO temp fix because currently its set to number of input files countsSeCompressed <- bplapply(seq_len(ncol(countMatrix2)), bambu.quantify, readClassDist = readClassDist, readClassDt = readClassDt, countMatrix = countMatrix2, annotations = annotations, isoreParameters = isoreParameters, diff --git a/R/bambu_utilityFunctions.R b/R/bambu_utilityFunctions.R index e728b3f8..d8501e77 100644 --- a/R/bambu_utilityFunctions.R +++ b/R/bambu_utilityFunctions.R @@ -3,13 +3,13 @@ #' setBiocParallelParameters #' @importFrom BiocParallel bpparam #' @noRd -setBiocParallelParameters <- function(reads, ncore, verbose){ +setBiocParallelParameters <- function(reads, ncore, verbose, demultiplexed){ if(ncore >= 2) message("WARNING - If you change the number of cores (ncore) ", "between Bambu runs and there is no progress please restart your R session ", "to resolve the issue that originates from the XGboost package.") bpParameters <- bpparam() #===# set parallel options: otherwise use parallel to distribute samples - bpParameters$workers <- ifelse(length(reads) == 1, 1, ncore) + bpParameters$workers <- ifelse(length(reads) == 1 & !demultiplexed, 1, ncore) bpParameters$progressbar <- ifelse(length(reads) > 1 & !verbose, TRUE, FALSE) return(bpParameters) } From 64f2d9db4b9a4c10441ee6f779c217e9e02e78b9 Mon Sep 17 00:00:00 2001 From: Andre Date: Thu, 5 Oct 2023 11:14:12 +0800 Subject: [PATCH 056/189] Reduce memory input to threads --- R/bambu-quantify.R | 41 +++++++++-------------------- R/bambu-quantify_utilityFunctions.R | 26 +++++++----------- R/bambu.R | 17 +++++++++--- 3 files changed, 36 insertions(+), 48 deletions(-) diff --git a/R/bambu-quantify.R b/R/bambu-quantify.R index e7def6c1..f3f73237 100644 --- a/R/bambu-quantify.R +++ b/R/bambu-quantify.R @@ -2,40 +2,25 @@ #' @inheritParams bambu #' @import data.table #' @noRd -bambu.quantify <- function(i, readClassDist, readClassDt, countMatrix, annotations, emParameters, +bambu.quantify <- function(distTable, readClassDt, countMatrix, sampleName, txid.index, GENEIDs, emParameters, trackReads = FALSE, returnDistTable = FALSE, verbose = FALSE, isoreParameters = setIsoreParameters(NULL)) { - print(i) - #TODO do not alter readClassDist and readClassDT objects to save memory - metadata(readClassDist)$distTable$readCount <- countMatrix[,i] - metadata(readClassDist)$distTable = metadata(readClassDist)$distTable[metadata(readClassDist)$distTable$readCount != 0,] - readClassDt$nobs = calculateEqClassCounts(metadata(readClassDist)$distTable, readClassDt) - incompatibleCounts <- processIncompatibleCounts(readClassDist) + distTable$readCount <- countMatrix + distTable = metadata(readClassDist)$distTable[metadata(readClassDist)$distTable$readCount != 0,] + readClassDt$nobs = calculateEqClassCounts(distTable, readClassDt) + incompatibleCounts <- processIncompatibleCounts(distTable) compatibleCounts <- bambu.quantDT(readClassDt, emParameters = emParameters,verbose = verbose) - incompatibleCounts <- incompatibleCounts[data.table(GENEID = unique(mcols(annotations)$GENEID)), on = "GENEID"] + incompatibleCounts <- incompatibleCounts[data.table(GENEID.i = GENEIDs), on = "GENEID.i"] incompatibleCounts[is.na(counts), counts := 0] compatibleCounts <- calculateCPM(compatibleCounts, incompatibleCounts) - setnames(incompatibleCounts, "counts", colnames(countMatrix)[i]) - counts <- compatibleCounts[match(mcols(annotations)$txid, txid)] - colNameRC <- colnames(countMatrix)[i] - colDataRC <- NULL # TODO carry over coldata??!! + setnames(incompatibleCounts, "counts", sampleName) + counts <- compatibleCounts[match(txid.index, txid)] sig.digit <- emParameters[["sig.digit"]] - seOutput <- SummarizedExperiment( - assays = SimpleList(counts = matrix(round(counts$counts,sig.digit), ncol = 1, - dimnames = list(NULL, colNameRC)), CPM = matrix(round(counts$CPM,sig.digit), - ncol = 1, dimnames = list(NULL, colNameRC)), - fullLengthCounts = matrix(round(counts$fullLengthCounts,sig.digit), ncol = 1, - dimnames = list(NULL, colNameRC)), - uniqueCounts = matrix(counts$uniqueCounts, - ncol = 1, dimnames = list(NULL, colNameRC)))) - metadata(seOutput)$incompatibleCounts = incompatibleCounts - - seOutput <- list(incompatibleCounts = as(metadata(seOutput)$incompatibleCounts[[colnames(seOutput)]], "sparseVector"), - counts = as(assays(seOutput)$counts, "sparseVector"), - CPM = as(assays(seOutput)$CPM, "sparseVector"), - fullLengthCounts = as(assays(seOutput)$fullLengthCounts, "sparseVector"), - uniqueCounts = as(assays(seOutput)$uniqueCounts, "sparseVector"), - colnames = colnames(seOutput), colData = colData(seOutput)) + seOutput <- list(incompatibleCounts = as(incompatibleCounts[[sampleName]], "sparseVector"), + counts = as(round(counts$counts,sig.digit), "sparseVector"), + CPM = as(round(counts$CPM,sig.digit), "sparseVector"), + fullLengthCounts = as(round(counts$fullLengthCounts,sig.digit), "sparseVector"), + uniqueCounts = as(counts$uniqueCounts, "sparseVector")) return(seOutput) } diff --git a/R/bambu-quantify_utilityFunctions.R b/R/bambu-quantify_utilityFunctions.R index bf07d9dd..78b38534 100644 --- a/R/bambu-quantify_utilityFunctions.R +++ b/R/bambu-quantify_utilityFunctions.R @@ -19,22 +19,16 @@ modifyIncompatibleAssignment <- function(distTable){ #' Process incompatible counts #' @noRd -processIncompatibleCounts <- function(readClassDist){ - distTable <- data.table(as.data.frame(metadata(readClassDist)$distTable))[, - .(readClassId, annotationTxId, readCount, GENEID, dist,equal)] - distTableIncompatible <- distTable[grep("unidentified", annotationTxId)] - # filter out multiple geneIDs mapped to the same readClass using rowData(se) - geneRCMap <- as.data.table(as.data.frame(rowData(readClassDist)), - keep.rownames = TRUE) - setnames(geneRCMap, old = c("rn", "geneId"), - new = c("readClassId", "GENEID")) - distTable <- distTable[geneRCMap[ readClassId %in% - unique(distTableIncompatible$readClassId), .(readClassId, GENEID)], - on = c("readClassId", "GENEID")] - distTable[, readCount := sum(readCount), by = GENEID] - counts <- unique(distTable[,.(GENEID, readCount)]) - setnames(counts, "readCount", "counts") - return(counts) +processIncompatibleCounts <- function(distTable){ + distTable <- data.table(as.data.frame(distTable))[, + .(readClassId, annotationTxId, readCount, GENEID, GENEID.match, GENEID.i, dist,equal)] + distTable <- distTable[grep("unidentified", annotationTxId)] + # filter out multiple geneIDs mapped to the same readClass using rowData(se) + distTable[GENEID.match,] + distTable[, readCount := sum(readCount), by = GENEID] + counts <- unique(distTable[,.(GENEID, GENEID.i, readCount)]) + setnames(counts, "readCount", "counts") + return(counts) } diff --git a/R/bambu.R b/R/bambu.R index 2e52800b..19e25257 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -202,12 +202,21 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, colnames(countMatrix2) = colnames(metadata(readClassList)$countMatrix) readClassDt <- genEquiRCs(readClassDist, annotations, verbose) print(ncol(countMatrix2)) - countsSeCompressed <- bplapply(seq_len(ncol(countMatrix2)), bambu.quantify, - readClassDist = readClassDist, readClassDt = readClassDt, countMatrix = countMatrix2, - annotations = annotations, isoreParameters = isoreParameters, + GENEIDs = factor(unique(mcols(annotations)$GENEID)) + GENEID.i = as.numeric(GENEIDs) + metadata(readClassDist)$distTable$GENEID.i = GENEID.i[match(distTable$GENEID, GENEIDs)] + + metadata(readClassDist)$distTable$GENEID.match = rowData(readClassDist)$geneId[match(distTable$readClassId, rownames(rowData(readClassDist)))] + metadata(readClassDist)$distTable$GENEID.match = metadata(readClassDist)$distTable$GENEID.match == metadata(readClassDist)$distTable$GENEID + + countsSeCompressed <- bplapply(seq_len(ncol(countMatrix2)), FUN = function(i){ + print(i) + return(bambu.quantify(distTable = metadata(readClassDist)$distTable, readClassDt = readClassDt, countMatrix = unname(countMatrix2[,i]), + sampleName = colnames(countMatrix2)[i], txid.index = mcols(annotations)$txid, GENEIDs = GENEID.i, isoreParameters = isoreParameters, emParameters = emParameters, trackReads = trackReads, - returnDistTable = returnDistTable, verbose = verbose, + returnDistTable = returnDistTable, verbose = verbose))}, BPPARAM = bpParameters) + countsSeCompressed$colnames = colnames(countMatrix) countsSe <- combineCountSes(countsSeCompressed, annotations) #metadata(countsSe)$warnings = warnings From 5f87c7689fe9108857812dbbc8d7ea38d6556dc4 Mon Sep 17 00:00:00 2001 From: Andre Date: Thu, 5 Oct 2023 13:28:07 +0800 Subject: [PATCH 057/189] Reduce memory before threading --- R/bambu-quantify.R | 9 ++++----- R/bambu-quantify_utilityFunctions.R | 2 +- R/bambu.R | 19 ++++++++++++------- 3 files changed, 17 insertions(+), 13 deletions(-) diff --git a/R/bambu-quantify.R b/R/bambu-quantify.R index f3f73237..b6993528 100644 --- a/R/bambu-quantify.R +++ b/R/bambu-quantify.R @@ -2,25 +2,24 @@ #' @inheritParams bambu #' @import data.table #' @noRd -bambu.quantify <- function(distTable, readClassDt, countMatrix, sampleName, txid.index, GENEIDs, emParameters, +bambu.quantify <- function(distTable, readClassDt, countMatrix, txid.index, GENEIDs, emParameters, trackReads = FALSE, returnDistTable = FALSE, verbose = FALSE, isoreParameters = setIsoreParameters(NULL)) { distTable$readCount <- countMatrix - distTable = metadata(readClassDist)$distTable[metadata(readClassDist)$distTable$readCount != 0,] + distTable = distTable[distTable$readCount != 0,] readClassDt$nobs = calculateEqClassCounts(distTable, readClassDt) incompatibleCounts <- processIncompatibleCounts(distTable) compatibleCounts <- bambu.quantDT(readClassDt, emParameters = emParameters,verbose = verbose) incompatibleCounts <- incompatibleCounts[data.table(GENEID.i = GENEIDs), on = "GENEID.i"] incompatibleCounts[is.na(counts), counts := 0] compatibleCounts <- calculateCPM(compatibleCounts, incompatibleCounts) - setnames(incompatibleCounts, "counts", sampleName) counts <- compatibleCounts[match(txid.index, txid)] sig.digit <- emParameters[["sig.digit"]] - seOutput <- list(incompatibleCounts = as(incompatibleCounts[[sampleName]], "sparseVector"), + seOutput <- list(incompatibleCounts = as(incompatibleCounts$counts, "sparseVector"), counts = as(round(counts$counts,sig.digit), "sparseVector"), CPM = as(round(counts$CPM,sig.digit), "sparseVector"), fullLengthCounts = as(round(counts$fullLengthCounts,sig.digit), "sparseVector"), - uniqueCounts = as(counts$uniqueCounts, "sparseVector")) + uniqueCounts = as(round(counts$uniqueCounts,sig.digit), "sparseVector")) return(seOutput) } diff --git a/R/bambu-quantify_utilityFunctions.R b/R/bambu-quantify_utilityFunctions.R index 78b38534..f0ec3f25 100644 --- a/R/bambu-quantify_utilityFunctions.R +++ b/R/bambu-quantify_utilityFunctions.R @@ -24,7 +24,7 @@ processIncompatibleCounts <- function(distTable){ .(readClassId, annotationTxId, readCount, GENEID, GENEID.match, GENEID.i, dist,equal)] distTable <- distTable[grep("unidentified", annotationTxId)] # filter out multiple geneIDs mapped to the same readClass using rowData(se) - distTable[GENEID.match,] + distTable[GENEID.match==TRUE,] distTable[, readCount := sum(readCount), by = GENEID] counts <- unique(distTable[,.(GENEID, GENEID.i, readCount)]) setnames(counts, "readCount", "counts") diff --git a/R/bambu.R b/R/bambu.R index 19e25257..0402b77c 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -198,21 +198,26 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, verbose = verbose) metadata(readClassDist)$distTable <- modifyIncompatibleAssignment(metadata(readClassDist)$distTable) metadata(readClassDist)$distTable <- genEquiRCsBasedOnObservedReads(readClassDist) - countMatrix2 = as.matrix(metadata(readClassList)$countMatrix[metadata(readClassDist)$distTable$readClassId,]) + countMatrix2 = metadata(readClassList)$countMatrix[metadata(readClassDist)$distTable$readClassId,] colnames(countMatrix2) = colnames(metadata(readClassList)$countMatrix) readClassDt <- genEquiRCs(readClassDist, annotations, verbose) print(ncol(countMatrix2)) + distTable = metadata(readClassDist)$distTable GENEIDs = factor(unique(mcols(annotations)$GENEID)) GENEID.i = as.numeric(GENEIDs) - metadata(readClassDist)$distTable$GENEID.i = GENEID.i[match(distTable$GENEID, GENEIDs)] - - metadata(readClassDist)$distTable$GENEID.match = rowData(readClassDist)$geneId[match(distTable$readClassId, rownames(rowData(readClassDist)))] - metadata(readClassDist)$distTable$GENEID.match = metadata(readClassDist)$distTable$GENEID.match == metadata(readClassDist)$distTable$GENEID + distTable$GENEID.i = GENEID.i[match(distTable$GENEID, GENEIDs)] + #check distTable and rowData match for incompatible counts + distTable$GENEID.match = rowData(readClassDist)$geneId[match(distTable$readClassId, rownames(rowData(readClassDist)))] + distTable$GENEID.match = distTable$GENEID.match == distTable$GENEID + + rm(readClassDist) + rm(readClassList) + gc() countsSeCompressed <- bplapply(seq_len(ncol(countMatrix2)), FUN = function(i){ print(i) - return(bambu.quantify(distTable = metadata(readClassDist)$distTable, readClassDt = readClassDt, countMatrix = unname(countMatrix2[,i]), - sampleName = colnames(countMatrix2)[i], txid.index = mcols(annotations)$txid, GENEIDs = GENEID.i, isoreParameters = isoreParameters, + return(bambu.quantify(distTable = distTable, readClassDt = readClassDt, countMatrix = unname(countMatrix2[,i]), + txid.index = mcols(annotations)$txid, GENEIDs = GENEID.i, isoreParameters = isoreParameters, emParameters = emParameters, trackReads = trackReads, returnDistTable = returnDistTable, verbose = verbose))}, BPPARAM = bpParameters) From 8495cc8b9f1e5421f63acde8abbe6eb03b4bce7e Mon Sep 17 00:00:00 2001 From: Andre Date: Fri, 6 Oct 2023 13:42:44 +0800 Subject: [PATCH 058/189] Clean up distTable code --- R/bambu.R | 27 ++++++--------------------- R/bambu_utilityFunctions.R | 25 +++++++++++++++++++++++++ 2 files changed, 31 insertions(+), 21 deletions(-) diff --git a/R/bambu.R b/R/bambu.R index 0402b77c..98d0ce15 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -184,44 +184,29 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, } if (quant) { - message("--- Start isoform quantification ---") if(length(annotations)==0) stop("No valid annotations, if running de novo please try less stringent parameters") if (is.character(readClassList)) readClassList <- readRDS(file = readClassList) if(is.list(readClassList)) readClassList = readClassList[[1]] - readClassDist <- isore.estimateDistanceToAnnotations(readClassList, annotations, - min.exonDistance = isoreParameters[["min.exonDistance"]], - min.primarySecondaryDist = isoreParameters[['min.primarySecondaryDist']], - min.primarySecondaryDistStartEnd = isoreParameters[['min.primarySecondaryDistStartEnd2']], - verbose = verbose) - metadata(readClassDist)$distTable <- modifyIncompatibleAssignment(metadata(readClassDist)$distTable) - metadata(readClassDist)$distTable <- genEquiRCsBasedOnObservedReads(readClassDist) - countMatrix2 = metadata(readClassList)$countMatrix[metadata(readClassDist)$distTable$readClassId,] - colnames(countMatrix2) = colnames(metadata(readClassList)$countMatrix) + readClassDist <- calculateDistTable(readClassList, annotations, isoreParameters, verbose) readClassDt <- genEquiRCs(readClassDist, annotations, verbose) - print(ncol(countMatrix2)) - distTable = metadata(readClassDist)$distTable - GENEIDs = factor(unique(mcols(annotations)$GENEID)) - GENEID.i = as.numeric(GENEIDs) - distTable$GENEID.i = GENEID.i[match(distTable$GENEID, GENEIDs)] - #check distTable and rowData match for incompatible counts - distTable$GENEID.match = rowData(readClassDist)$geneId[match(distTable$readClassId, rownames(rowData(readClassDist)))] - distTable$GENEID.match = distTable$GENEID.match == distTable$GENEID + distTable = metadata(readClassDist)$distTable + countMatrix.matched = metadata(readClassList)$countMatrix.matched rm(readClassDist) rm(readClassList) gc() - countsSeCompressed <- bplapply(seq_len(ncol(countMatrix2)), FUN = function(i){ + countsSeCompressed <- bplapply(seq_len(ncol(countMatrix.matched)), FUN = function(i){ print(i) - return(bambu.quantify(distTable = distTable, readClassDt = readClassDt, countMatrix = unname(countMatrix2[,i]), + return(bambu.quantify(distTable = distTable, readClassDt = readClassDt, countMatrix = unname(countMatrix.matched[,i]), txid.index = mcols(annotations)$txid, GENEIDs = GENEID.i, isoreParameters = isoreParameters, emParameters = emParameters, trackReads = trackReads, returnDistTable = returnDistTable, verbose = verbose))}, BPPARAM = bpParameters) - countsSeCompressed$colnames = colnames(countMatrix) + countsSeCompressed$colnames = colnames(countMatrix.matched) countsSe <- combineCountSes(countsSeCompressed, annotations) #metadata(countsSe)$warnings = warnings diff --git a/R/bambu_utilityFunctions.R b/R/bambu_utilityFunctions.R index d8501e77..1ad2e57e 100644 --- a/R/bambu_utilityFunctions.R +++ b/R/bambu_utilityFunctions.R @@ -206,6 +206,31 @@ handleWarnings <- function(readClassList, verbose){ return(warnings) } +#' Calculate the dist table used for Bambu Quantification +calculateDistTable <- function(readClassList, annotations, isoreParameters, verbose){ + readClassDist <- isore.estimateDistanceToAnnotations(readClassList, annotations, + min.exonDistance = isoreParameters[["min.exonDistance"]], + min.primarySecondaryDist = isoreParameters[['min.primarySecondaryDist']], + min.primarySecondaryDistStartEnd = isoreParameters[['min.primarySecondaryDistStartEnd2']], + verbose = verbose) + metadata(readClassDist)$distTable <- modifyIncompatibleAssignment(metadata(readClassDist)$distTable) + metadata(readClassDist)$distTable <- genEquiRCsBasedOnObservedReads(readClassDist) + #match count matrix with distTable to speed up calculations + metadata(readClassList)$countMatrix.matched = + metadata(readClassList)$countMatrix[metadata(readClassDist)$distTable$readClassId,] + colnames(metadata(readClassList)$countMatrix.matched) = colnames(metadata(readClassList)$countMatrix) + #convert string gene ids into index to save memory + GENEIDs = factor(unique(mcols(annotations)$GENEID)) + GENEID.i = as.numeric(GENEIDs) + metadata(readClassDist)$distTable$GENEID.i = GENEID.i[match(metadata(readClassDist)$distTable$GENEID, GENEIDs)] + #check distTable and rowData match for incompatible counts + metadata(readClassDist)$distTable$GENEID.match = + rowData(readClassDist)$geneId[match(metadata(readClassDist)$distTable$readClassId, + rownames(rowData(readClassDist)))] + metadata(readClassDist)$distTable$GENEID.match = + metadata(readClassDist)$distTable$GENEID.match == distTable$GENEID + return(readClassDist) +} #' Combine count se object while preserving the metadata objects #' @noRd From 58351680c7f26e384d762e301bd74449931e2b5d Mon Sep 17 00:00:00 2001 From: Andre Date: Fri, 6 Oct 2023 14:58:46 +0800 Subject: [PATCH 059/189] Fix crash at end caused by sample names --- R/bambu.R | 2 +- R/bambu_utilityFunctions.R | 7 ++++--- 2 files changed, 5 insertions(+), 4 deletions(-) diff --git a/R/bambu.R b/R/bambu.R index 98d0ce15..9a1e4e2c 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -194,7 +194,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, readClassDt <- genEquiRCs(readClassDist, annotations, verbose) distTable = metadata(readClassDist)$distTable - countMatrix.matched = metadata(readClassList)$countMatrix.matched + countMatrix.matched = metadata(readClassDist)$countMatrix.matched rm(readClassDist) rm(readClassList) gc() diff --git a/R/bambu_utilityFunctions.R b/R/bambu_utilityFunctions.R index 1ad2e57e..f332ea9e 100644 --- a/R/bambu_utilityFunctions.R +++ b/R/bambu_utilityFunctions.R @@ -216,9 +216,9 @@ calculateDistTable <- function(readClassList, annotations, isoreParameters, verb metadata(readClassDist)$distTable <- modifyIncompatibleAssignment(metadata(readClassDist)$distTable) metadata(readClassDist)$distTable <- genEquiRCsBasedOnObservedReads(readClassDist) #match count matrix with distTable to speed up calculations - metadata(readClassList)$countMatrix.matched = + metadata(readClassDist)$countMatrix.matched = metadata(readClassList)$countMatrix[metadata(readClassDist)$distTable$readClassId,] - colnames(metadata(readClassList)$countMatrix.matched) = colnames(metadata(readClassList)$countMatrix) + colnames(metadata(readClassDist)$countMatrix.matched) = colnames(metadata(readClassList)$countMatrix) #convert string gene ids into index to save memory GENEIDs = factor(unique(mcols(annotations)$GENEID)) GENEID.i = as.numeric(GENEIDs) @@ -236,7 +236,8 @@ calculateDistTable <- function(readClassList, annotations, isoreParameters, verb #' @noRd combineCountSes <- function(countsSe, annotations){ countsData <- c("counts", "CPM", "fullLengthCounts", "uniqueCounts", "incompatibleCounts") - sampleNames = sapply(countsSe, FUN = function(x){x$colnames}) + sampleNames = countsSe$colnames + countsSe$colnames = NULL countsDataMat <- lapply(countsData, FUN = function(k){ countsVecList <- lapply(countsSe, function(j){j[[k]]}) countsMat <- sparseMatrix(i = unlist(lapply(countsVecList, function(j){j@i})), From 970c6284d3d7170c53102a21b16bfe36bf4bbced Mon Sep 17 00:00:00 2001 From: Andre Date: Thu, 12 Oct 2023 10:27:48 +0800 Subject: [PATCH 060/189] add in missing variable --- R/bambu.R | 4 ++-- R/bambu_utilityFunctions.R | 2 +- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/R/bambu.R b/R/bambu.R index 9a1e4e2c..df67bc5c 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -198,11 +198,11 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, rm(readClassDist) rm(readClassList) gc() - + GENEIDs.i = as.numeric(factor(unique(mcols(annotations)$GENEID))) countsSeCompressed <- bplapply(seq_len(ncol(countMatrix.matched)), FUN = function(i){ print(i) return(bambu.quantify(distTable = distTable, readClassDt = readClassDt, countMatrix = unname(countMatrix.matched[,i]), - txid.index = mcols(annotations)$txid, GENEIDs = GENEID.i, isoreParameters = isoreParameters, + txid.index = mcols(annotations)$txid, GENEIDs = GENEIDs.i, isoreParameters = isoreParameters, emParameters = emParameters, trackReads = trackReads, returnDistTable = returnDistTable, verbose = verbose))}, BPPARAM = bpParameters) diff --git a/R/bambu_utilityFunctions.R b/R/bambu_utilityFunctions.R index f332ea9e..ae793b3a 100644 --- a/R/bambu_utilityFunctions.R +++ b/R/bambu_utilityFunctions.R @@ -228,7 +228,7 @@ calculateDistTable <- function(readClassList, annotations, isoreParameters, verb rowData(readClassDist)$geneId[match(metadata(readClassDist)$distTable$readClassId, rownames(rowData(readClassDist)))] metadata(readClassDist)$distTable$GENEID.match = - metadata(readClassDist)$distTable$GENEID.match == distTable$GENEID + metadata(readClassDist)$distTable$GENEID.match == metadata(readClassDist)$distTable$GENEID return(readClassDist) } From 219d5e82781a5e8ec5410f9c5d17843a8404cb0c Mon Sep 17 00:00:00 2001 From: Andre Date: Thu, 19 Oct 2023 14:43:49 +0800 Subject: [PATCH 061/189] Instead calculate eqClass counts before parralellization --- R/bambu-processReads.R | 46 ++++++++++++++++++++++++++++++-------- R/bambu-quantify.R | 12 +++++----- R/bambu.R | 18 +++++++-------- R/bambu_utilityFunctions.R | 18 ++++++--------- 4 files changed, 58 insertions(+), 36 deletions(-) diff --git a/R/bambu-processReads.R b/R/bambu-processReads.R index 6d880596..4d00bb91 100644 --- a/R/bambu-processReads.R +++ b/R/bambu-processReads.R @@ -66,10 +66,8 @@ bambu.processReads <- function(reads, annotations, genomeSequence, metadata(readClassList)$samples = names(reads) if(demultiplexed)metadata(readClassList)$samples = metadata(readGrgList)$CB - countMatrix = splitReadClassFiles(readClassList) - colnames(countMatrix) = metadata(readClassList)$samples - rownames(countMatrix) = rownames(readClassList) - metadata(readClassList)$countMatrix = countMatrix + metadata(readClassList)$readClassDist <- calculateDistTable(readClassList, annotations, isoreParameters, verbose) + readClassList = splitReadClassFiles(readClassList) # TODO return output # if (!is.null(readClass.outputDir)) { @@ -173,7 +171,7 @@ constructReadClasses <- function(readGrgList, genomeSequence, annotations, warnings = c() ###TODO # construct read classes for each chromosome seperately if(lowMemory) {se <- lowMemoryConstructReadClasses(readGrgList, genomeSequence, - annotations, stranded, verbose,bam.file) + annotations, stranded, verbose,"TODO") } else { unlisted_junctions <- unlistIntrons(readGrgList, use.ids = TRUE) if(length(unlisted_junctions)==0){ @@ -222,7 +220,7 @@ lowMemoryConstructReadClasses <- function(readGrgList, genomeSequence, uniqueJunctions <- isore.constructJunctionTables(unlisted_junctions, annotations,genomeSequence, stranded = stranded, verbose = verbose) se.temp <- isore.constructReadClasses(readGrgList[[i]], - unlisted_junctions, uniqueJunctions, runName = names(bam.file)[1], + unlisted_junctions, uniqueJunctions, runName = "TODO", annotations, stranded, verbose) return(se.temp) }) @@ -250,11 +248,41 @@ seqlevelCheckReadsAnnotation <- function(reads, annotations){ } splitReadClassFiles = function(readClassFile){ - counts.table = lapply(rowData(readClassFile)$sampleIDs, FUN = function(x){table(x)}) + distTable = metadata(metadata(readClassFile)$readClassDist)$distTable + eqClasses = distTable %>% group_by(eqClassById) %>% + distinct(eqClassById, readCount,GENEID, .keep_all = TRUE) + eqClasses$sampleIDs = rowData(readClassFile)$sampleIDs[match(eqClasses$readClassId, rownames(readClassFile))] + eqClasses = eqClasses %>% summarise(nobs = sum(readCount), + sampleIDs = list(unlist(sampleIDs))) + counts.table = lapply(eqClasses$sampleIDs, FUN = function(x){table(x)}) counts = sparseMatrix( i = rep(seq_along(counts.table), lengths(counts.table)), j = as.numeric(names(unlist(counts.table))), x = unlist(counts.table), - dims = c(nrow(readClassFile), length(metadata(readClassFile)$samples))) - return(counts) + dims = c(nrow(eqClasses), length(metadata(readClassFile)$samples))) + #incompatible counts + distTable = metadata(metadata(readClassFile)$readClassDist)$distTable.incompatible + if(nrow(distTable)==0) { + counts.incompatible = sparseMatrix(i= 1, j = 1, x = 0, + dims = c(1, length(metadata(readClassFile)$samples))) + rownames(counts.incompatible) = "TODO" + } else{ + distTable$sampleIDs = rowData(readClassFile)$sampleIDs[match(distTable$readClassId, rownames(readClassFile))] + distTable = distTable %>% group_by(GENEID.i) %>% summarise(counts = sum(readCount), + sampleIDs = list(unlist(sampleIDs))) + counts.table = lapply(distTable$sampleIDs, FUN = function(x){table(x)}) + counts.incompatible = sparseMatrix( + i = rep(seq_along(counts.table), lengths(counts.table)), + j = as.numeric(names(unlist(counts.table))), + x = unlist(counts.table), + dims = c(nrow(distTable), length(metadata(readClassFile)$samples))) + colnames(counts.incompatible) = metadata(readClassFile)$samples + rownames(counts.incompatible) = distTable$GENEID.i + } + colnames(counts) = metadata(readClassFile)$samples + metadata(readClassFile)$eqClassById = eqClasses$eqClassById + #rownames(counts) = eqClasses$eqClassById + metadata(readClassFile)$countMatrix = counts + metadata(readClassFile)$incompatibleCountMatrix = counts.incompatible + return(readClassFile ) } diff --git a/R/bambu-quantify.R b/R/bambu-quantify.R index b6993528..3cd3d3ae 100644 --- a/R/bambu-quantify.R +++ b/R/bambu-quantify.R @@ -2,15 +2,13 @@ #' @inheritParams bambu #' @import data.table #' @noRd -bambu.quantify <- function(distTable, readClassDt, countMatrix, txid.index, GENEIDs, emParameters, +bambu.quantify <- function(readClassDt, countMatrix, incompatibleCountMatrix, txid.index, GENEIDs, emParameters, trackReads = FALSE, returnDistTable = FALSE, verbose = FALSE, isoreParameters = setIsoreParameters(NULL)) { - distTable$readCount <- countMatrix - distTable = distTable[distTable$readCount != 0,] - readClassDt$nobs = calculateEqClassCounts(distTable, readClassDt) - incompatibleCounts <- processIncompatibleCounts(distTable) + readClassDt$nobs = countMatrix[readClassDt$eqClass.match] + readClassDt$nobs[is.na(readClassDt$nobs)] = 0 compatibleCounts <- bambu.quantDT(readClassDt, emParameters = emParameters,verbose = verbose) - incompatibleCounts <- incompatibleCounts[data.table(GENEID.i = GENEIDs), on = "GENEID.i"] + incompatibleCounts <- incompatibleCountMatrix[data.table(GENEID.i = GENEIDs), on = "GENEID.i"] incompatibleCounts[is.na(counts), counts := 0] compatibleCounts <- calculateCPM(compatibleCounts, incompatibleCounts) counts <- compatibleCounts[match(txid.index, txid)] @@ -19,7 +17,7 @@ bambu.quantify <- function(distTable, readClassDt, countMatrix, txid.index, GENE counts = as(round(counts$counts,sig.digit), "sparseVector"), CPM = as(round(counts$CPM,sig.digit), "sparseVector"), fullLengthCounts = as(round(counts$fullLengthCounts,sig.digit), "sparseVector"), - uniqueCounts = as(round(counts$uniqueCounts,sig.digit), "sparseVector")) + uniqueCounts = as(round(counts$uniqueCounts,sig.digit), "sparseVector")) return(seOutput) } diff --git a/R/bambu.R b/R/bambu.R index df67bc5c..0c277372 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -190,23 +190,23 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, if (is.character(readClassList)) readClassList <- readRDS(file = readClassList) if(is.list(readClassList)) readClassList = readClassList[[1]] - readClassDist <- calculateDistTable(readClassList, annotations, isoreParameters, verbose) - readClassDt <- genEquiRCs(readClassDist, annotations, verbose) - - distTable = metadata(readClassDist)$distTable - countMatrix.matched = metadata(readClassDist)$countMatrix.matched - rm(readClassDist) + readClassDt <- genEquiRCs(metadata(readClassList)$readClassDist, annotations, verbose) + countMatrix = metadata(readClassList)$countMatrix + incompatibleCountMatrix = metadata(readClassList)$incompatibleCountMatrix + readClassDt$eqClass.match = match(readClassDt$eqClassById,metadata(readClassList)$eqClassById) + metadata(readClassList)$readClassDist = NULL rm(readClassList) gc() GENEIDs.i = as.numeric(factor(unique(mcols(annotations)$GENEID))) - countsSeCompressed <- bplapply(seq_len(ncol(countMatrix.matched)), FUN = function(i){ + countsSeCompressed <- bplapply(seq_len(ncol(countMatrix)), FUN = function(i){ print(i) - return(bambu.quantify(distTable = distTable, readClassDt = readClassDt, countMatrix = unname(countMatrix.matched[,i]), + return(bambu.quantify(readClassDt = readClassDt, countMatrix = unname(countMatrix[,i]), + incompatibleCountMatrix = data.table(GENEID.i = as.numeric(rownames(incompatibleCountMatrix)), counts = incompatibleCountMatrix[,i]), txid.index = mcols(annotations)$txid, GENEIDs = GENEIDs.i, isoreParameters = isoreParameters, emParameters = emParameters, trackReads = trackReads, returnDistTable = returnDistTable, verbose = verbose))}, BPPARAM = bpParameters) - countsSeCompressed$colnames = colnames(countMatrix.matched) + countsSeCompressed$colnames = colnames(countMatrix) countsSe <- combineCountSes(countsSeCompressed, annotations) #metadata(countsSe)$warnings = warnings diff --git a/R/bambu_utilityFunctions.R b/R/bambu_utilityFunctions.R index ae793b3a..6037ce2c 100644 --- a/R/bambu_utilityFunctions.R +++ b/R/bambu_utilityFunctions.R @@ -46,7 +46,7 @@ setIsoreParameters <- function(isoreParameters){ #' setEmParameters #' @noRd setEmParameters <- function(emParameters){ - emParameters.default <- list(degradationBias = TRUE, maxiter = 10000, + emParameters.default <- list(degradationBias = FALSE, maxiter = 10000, conv = 10^(-2), minvalue = 10^(-8), sig.digit = 5) emParameters <- updateParameters(emParameters, emParameters.default) return(emParameters) @@ -214,21 +214,17 @@ calculateDistTable <- function(readClassList, annotations, isoreParameters, verb min.primarySecondaryDistStartEnd = isoreParameters[['min.primarySecondaryDistStartEnd2']], verbose = verbose) metadata(readClassDist)$distTable <- modifyIncompatibleAssignment(metadata(readClassDist)$distTable) + #convert string gene ids into index to save memory + GENEIDs = factor(unique(mcols(annotations)$GENEID)) + GENEID.i = as.numeric(GENEIDs) + metadata(readClassDist)$distTable$GENEID.i = GENEID.i[match(metadata(readClassDist)$distTable$GENEID, GENEIDs)] + metadata(readClassDist)$distTable.incompatible = data.table(as.data.frame(metadata(readClassDist)$distTable)) %>% + filter(grepl("unidentified", annotationTxId)) %>% distinct(readClassId, .keep_all = TRUE) metadata(readClassDist)$distTable <- genEquiRCsBasedOnObservedReads(readClassDist) #match count matrix with distTable to speed up calculations metadata(readClassDist)$countMatrix.matched = metadata(readClassList)$countMatrix[metadata(readClassDist)$distTable$readClassId,] colnames(metadata(readClassDist)$countMatrix.matched) = colnames(metadata(readClassList)$countMatrix) - #convert string gene ids into index to save memory - GENEIDs = factor(unique(mcols(annotations)$GENEID)) - GENEID.i = as.numeric(GENEIDs) - metadata(readClassDist)$distTable$GENEID.i = GENEID.i[match(metadata(readClassDist)$distTable$GENEID, GENEIDs)] - #check distTable and rowData match for incompatible counts - metadata(readClassDist)$distTable$GENEID.match = - rowData(readClassDist)$geneId[match(metadata(readClassDist)$distTable$readClassId, - rownames(rowData(readClassDist)))] - metadata(readClassDist)$distTable$GENEID.match = - metadata(readClassDist)$distTable$GENEID.match == metadata(readClassDist)$distTable$GENEID return(readClassDist) } From 964fea8660f1686cb87b13419ef87e9403f73d41 Mon Sep 17 00:00:00 2001 From: Andre Date: Fri, 20 Oct 2023 13:41:09 +0800 Subject: [PATCH 062/189] Speed up addAval --- R/bambu-quantify.R | 12 +++++++- R/bambu-quantify_utilityFunctions.R | 48 +++++++++++++++++++---------- R/bambu.R | 6 ++++ 3 files changed, 48 insertions(+), 18 deletions(-) diff --git a/R/bambu-quantify.R b/R/bambu-quantify.R index 3cd3d3ae..9b094918 100644 --- a/R/bambu-quantify.R +++ b/R/bambu-quantify.R @@ -5,6 +5,7 @@ bambu.quantify <- function(readClassDt, countMatrix, incompatibleCountMatrix, txid.index, GENEIDs, emParameters, trackReads = FALSE, returnDistTable = FALSE, verbose = FALSE, isoreParameters = setIsoreParameters(NULL)) { + start.ptm <- proc.time() readClassDt$nobs = countMatrix[readClassDt$eqClass.match] readClassDt$nobs[is.na(readClassDt$nobs)] = 0 compatibleCounts <- bambu.quantDT(readClassDt, emParameters = emParameters,verbose = verbose) @@ -18,6 +19,8 @@ bambu.quantify <- function(readClassDt, countMatrix, incompatibleCountMatrix, tx CPM = as(round(counts$CPM,sig.digit), "sparseVector"), fullLengthCounts = as(round(counts$fullLengthCounts,sig.digit), "sparseVector"), uniqueCounts = as(round(counts$uniqueCounts,sig.digit), "sparseVector")) + end.ptm <- proc.time() + message("bambu.quantify ", round((end.ptm - start.ptm)[3] / 60, 3), " mins.") return(seOutput) } @@ -28,13 +31,19 @@ bambu.quantify <- function(readClassDt, countMatrix, incompatibleCountMatrix, tx bambu.quantDT <- function(readClassDt = readClassDt, emParameters = list(degradationBias = TRUE, maxiter = 10000, conv = 10^(-2), minvalue = 10^(-8)), ncore = 1, verbose = FALSE) { + start.ptm <- proc.time() rcPreOut <- addAval(readClassDt, emParameters, verbose) + end.ptm <- proc.time() + message("addAval ", round((end.ptm - start.ptm)[3] / 60, 3), " mins.") + start.ptm <- proc.time() readClassDt <- rcPreOut[[1]] outIni <- initialiseOutput(readClassDt) readClassDt <- filterTxRc(readClassDt) readClassDt <- assignGroups(readClassDt) inputRcDt <- getInputList(readClassDt) readClassDt <- split(readClassDt, by = "gene_grp_id") + end.ptm <- proc.time() + message("step2 ", round((end.ptm - start.ptm)[3] / 60, 3), " mins.") start.ptm <- proc.time() outEst <- abundance_quantification(inputRcDt, readClassDt, maxiter = emParameters[["maxiter"]], @@ -45,7 +54,8 @@ bambu.quantDT <- function(readClassDt = readClassDt, outEst <- modifyQuantOut(outEst,outIni) theta_est <- rbind(rcPreOut[[2]],outEst) theta_est <- removeDuplicates(theta_est) - return(theta_est) + end.ptm <- proc.time() + return(theta_est) } diff --git a/R/bambu-quantify_utilityFunctions.R b/R/bambu-quantify_utilityFunctions.R index f0ec3f25..5e92469e 100644 --- a/R/bambu-quantify_utilityFunctions.R +++ b/R/bambu-quantify_utilityFunctions.R @@ -188,15 +188,15 @@ createEqClassToTxMapping <- function(eqClassTable){ #' Add A matrix for total, full-length, unique #' @noRd addAval <- function(readClassDt, emParameters, verbose){ - if (is.null(readClassDt)) { - stop("Input object is missing.") - } else if (any(!(c("GENEID", "txid", "eqClassId","nobs") %in% - colnames(readClassDt)))) { - stop("Columns GENEID, txid, eqClassId, nobs, - are missing from object.") - } +# if (is.null(readClassDt)) { +# stop("Input object is missing.") +# } else if (any(!(c("GENEID", "txid", "eqClassId","nobs") %in% +# colnames(readClassDt)))) { +# stop("Columns GENEID, txid, eqClassId, nobs, +# are missing from object.") +# } ## ----step2: match to simple numbers to increase claculation efficiency - readClassDt <- simplifyNames(readClassDt) + #readClassDt <- simplifyNames(readClassDt) d_mode <- emParameters[["degradationBias"]] start.ptm <- proc.time() if (d_mode) { @@ -206,10 +206,15 @@ addAval <- function(readClassDt, emParameters, verbose){ } end.ptm <- proc.time() if (verbose) message("Finished estimate degradation bias in ", - round((end.ptm - start.ptm)[3] / 60, 1), " mins.") - readClassDt <- modifyAvaluewithDegradation_rate(readClassDt, - d_rateOut[1], d_mode = d_mode) + round((end.ptm - start.ptm)[3] / 60, 3), " mins.") +# readClassDt <- modifyAvaluewithDegradation_rate(readClassDt, +# d_rateOut[1], d_mode = d_mode) + start.ptm <- proc.time() + #readClassDt = data.table(readClassDt) removeList <- removeUnObservedGenes(readClassDt) +end.ptm <- proc.time() + message("removeUnObservedGenes ", round((end.ptm - start.ptm)[3] / 60, 3), " mins.") + start.ptm <- proc.time() readClassDt <- removeList[[1]] # keep only observed genes for estimation outList <- removeList[[2]] #for unobserved genes, set estimates to 0 readClassDt_withGeneCount <- select(readClassDt, gene_sid, eqClassId, nobs) %>% @@ -218,8 +223,14 @@ addAval <- function(readClassDt, emParameters, verbose){ mutate(K = sum(nobs), n.obs=nobs/K, nobs = NULL) %>% ## check if this is unique by eqClassId ungroup() %>% distinct() %>% - right_join(readClassDt, by = c("gene_sid","eqClassId")) %>% - data.table() + right_join(readClassDt, by = c("gene_sid","eqClassId")) +# readClassDt_withGeneCount <- readClassDt %>% +# group_by(gene_sid, eqClassId, nobs) %>% mutate(n = n(), n = replace(n,1,1)) %>% +# ungroup() %>% group_by(gene_sid) %>% +# mutate(K = sum(nobs), n.obs=(nobs)/(K)) %>% +# ungroup() + end.ptm <- proc.time() + message("dplyr ", round((end.ptm - start.ptm)[3] / 60, 3), " mins.") return(list(readClassDt_withGeneCount,outList)) } @@ -293,11 +304,14 @@ modifyAvaluewithDegradation_rate <- function(tmp, d_rate, d_mode){ #' @import data.table #' @noRd removeUnObservedGenes <- function(readClassDt){ - uoGenes <- unique(readClassDt[,.I[sum(nobs) == 0], by = gene_sid]$gene_sid) + uoGenes <- readClassDt %>% group_by(gene_sid) %>% + summarise(nobs = sum(nobs)) %>% filter(nobs == 0) %>% + select(gene_sid) %>% distinct() if (length(uoGenes) > 0) { - uo_txGeneDt <- - unique(readClassDt[(gene_sid %in% uoGenes),.(txid,gene_sid)]) - readClassDt <- readClassDt[!(gene_sid %in% uoGenes)] + readClassDt <- readClassDt %>% filter(gene_sid %in% uoGenes$gene_sid) + uo_txGeneDt <- readClassDt %>% + select(txid,gene_sid) %>% distinct() + outList <- data.table(txid = uo_txGeneDt$txid, counts = 0, fullLengthCounts = 0, diff --git a/R/bambu.R b/R/bambu.R index 0c277372..1e98f5a2 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -198,6 +198,10 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, rm(readClassList) gc() GENEIDs.i = as.numeric(factor(unique(mcols(annotations)$GENEID))) + start.ptm <- proc.time() + readClassDt <- simplifyNames(readClassDt) + readClassDt = readClassDt %>% group_by(eqClassId, gene_sid) %>% + mutate(multi_align = length(unique(txid))>1) %>% ungroup() %>% mutate(aval = 1) countsSeCompressed <- bplapply(seq_len(ncol(countMatrix)), FUN = function(i){ print(i) return(bambu.quantify(readClassDt = readClassDt, countMatrix = unname(countMatrix[,i]), @@ -206,6 +210,8 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, emParameters = emParameters, trackReads = trackReads, returnDistTable = returnDistTable, verbose = verbose))}, BPPARAM = bpParameters) + end.ptm <- proc.time() + message("Total Time ", round((end.ptm - start.ptm)[3] / 60, 3), " mins.") countsSeCompressed$colnames = colnames(countMatrix) countsSe <- combineCountSes(countsSeCompressed, annotations) From 82dc9d4cfa4130603cc3993475002df5de657ee7 Mon Sep 17 00:00:00 2001 From: Andre Date: Fri, 20 Oct 2023 14:21:55 +0800 Subject: [PATCH 063/189] Make readClassDt a data.table from the start --- R/bambu-quantify.R | 6 ------ R/bambu-quantify_utilityFunctions.R | 18 ++++-------------- R/bambu.R | 3 ++- 3 files changed, 6 insertions(+), 21 deletions(-) diff --git a/R/bambu-quantify.R b/R/bambu-quantify.R index 9b094918..8dbbfacb 100644 --- a/R/bambu-quantify.R +++ b/R/bambu-quantify.R @@ -31,19 +31,13 @@ bambu.quantify <- function(readClassDt, countMatrix, incompatibleCountMatrix, tx bambu.quantDT <- function(readClassDt = readClassDt, emParameters = list(degradationBias = TRUE, maxiter = 10000, conv = 10^(-2), minvalue = 10^(-8)), ncore = 1, verbose = FALSE) { - start.ptm <- proc.time() rcPreOut <- addAval(readClassDt, emParameters, verbose) - end.ptm <- proc.time() - message("addAval ", round((end.ptm - start.ptm)[3] / 60, 3), " mins.") - start.ptm <- proc.time() readClassDt <- rcPreOut[[1]] outIni <- initialiseOutput(readClassDt) readClassDt <- filterTxRc(readClassDt) readClassDt <- assignGroups(readClassDt) inputRcDt <- getInputList(readClassDt) readClassDt <- split(readClassDt, by = "gene_grp_id") - end.ptm <- proc.time() - message("step2 ", round((end.ptm - start.ptm)[3] / 60, 3), " mins.") start.ptm <- proc.time() outEst <- abundance_quantification(inputRcDt, readClassDt, maxiter = emParameters[["maxiter"]], diff --git a/R/bambu-quantify_utilityFunctions.R b/R/bambu-quantify_utilityFunctions.R index 5e92469e..821192af 100644 --- a/R/bambu-quantify_utilityFunctions.R +++ b/R/bambu-quantify_utilityFunctions.R @@ -209,12 +209,7 @@ addAval <- function(readClassDt, emParameters, verbose){ round((end.ptm - start.ptm)[3] / 60, 3), " mins.") # readClassDt <- modifyAvaluewithDegradation_rate(readClassDt, # d_rateOut[1], d_mode = d_mode) - start.ptm <- proc.time() - #readClassDt = data.table(readClassDt) removeList <- removeUnObservedGenes(readClassDt) -end.ptm <- proc.time() - message("removeUnObservedGenes ", round((end.ptm - start.ptm)[3] / 60, 3), " mins.") - start.ptm <- proc.time() readClassDt <- removeList[[1]] # keep only observed genes for estimation outList <- removeList[[2]] #for unobserved genes, set estimates to 0 readClassDt_withGeneCount <- select(readClassDt, gene_sid, eqClassId, nobs) %>% @@ -229,8 +224,6 @@ end.ptm <- proc.time() # ungroup() %>% group_by(gene_sid) %>% # mutate(K = sum(nobs), n.obs=(nobs)/(K)) %>% # ungroup() - end.ptm <- proc.time() - message("dplyr ", round((end.ptm - start.ptm)[3] / 60, 3), " mins.") return(list(readClassDt_withGeneCount,outList)) } @@ -304,14 +297,11 @@ modifyAvaluewithDegradation_rate <- function(tmp, d_rate, d_mode){ #' @import data.table #' @noRd removeUnObservedGenes <- function(readClassDt){ - uoGenes <- readClassDt %>% group_by(gene_sid) %>% - summarise(nobs = sum(nobs)) %>% filter(nobs == 0) %>% - select(gene_sid) %>% distinct() + uoGenes <- unique(readClassDt[,.I[sum(nobs) == 0], by = gene_sid]$gene_sid) if (length(uoGenes) > 0) { - readClassDt <- readClassDt %>% filter(gene_sid %in% uoGenes$gene_sid) - uo_txGeneDt <- readClassDt %>% - select(txid,gene_sid) %>% distinct() - + uo_txGeneDt <- + unique(readClassDt[(gene_sid %in% uoGenes),.(txid,gene_sid)]) + readClassDt <- readClassDt[!(gene_sid %in% uoGenes)] outList <- data.table(txid = uo_txGeneDt$txid, counts = 0, fullLengthCounts = 0, diff --git a/R/bambu.R b/R/bambu.R index 1e98f5a2..372676e1 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -201,7 +201,8 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, start.ptm <- proc.time() readClassDt <- simplifyNames(readClassDt) readClassDt = readClassDt %>% group_by(eqClassId, gene_sid) %>% - mutate(multi_align = length(unique(txid))>1) %>% ungroup() %>% mutate(aval = 1) + mutate(multi_align = length(unique(txid))>1) %>% ungroup() %>% mutate(aval = 1) %>% + data.table() countsSeCompressed <- bplapply(seq_len(ncol(countMatrix)), FUN = function(i){ print(i) return(bambu.quantify(readClassDt = readClassDt, countMatrix = unname(countMatrix[,i]), From f59f8bd067611142a32110c3c5e55570eb2cac8d Mon Sep 17 00:00:00 2001 From: Andre Date: Fri, 27 Oct 2023 10:10:36 +0800 Subject: [PATCH 064/189] Fix bug where counts were not assigned to correct transcripts Now disttable and splitting of read class counts is done in the quant step --- R/bambu-processReads.R | 2 -- R/bambu.R | 3 ++- R/bambu_utilityFunctions.R | 4 ---- 3 files changed, 2 insertions(+), 7 deletions(-) diff --git a/R/bambu-processReads.R b/R/bambu-processReads.R index 4d00bb91..20b6c02e 100644 --- a/R/bambu-processReads.R +++ b/R/bambu-processReads.R @@ -66,8 +66,6 @@ bambu.processReads <- function(reads, annotations, genomeSequence, metadata(readClassList)$samples = names(reads) if(demultiplexed)metadata(readClassList)$samples = metadata(readGrgList)$CB - metadata(readClassList)$readClassDist <- calculateDistTable(readClassList, annotations, isoreParameters, verbose) - readClassList = splitReadClassFiles(readClassList) # TODO return output # if (!is.null(readClass.outputDir)) { diff --git a/R/bambu.R b/R/bambu.R index 372676e1..44321fff 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -190,8 +190,9 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, if (is.character(readClassList)) readClassList <- readRDS(file = readClassList) if(is.list(readClassList)) readClassList = readClassList[[1]] + metadata(readClassList)$readClassDist <- calculateDistTable(readClassList, annotations, isoreParameters, verbose) + readClassList = splitReadClassFiles(readClassList) readClassDt <- genEquiRCs(metadata(readClassList)$readClassDist, annotations, verbose) - countMatrix = metadata(readClassList)$countMatrix incompatibleCountMatrix = metadata(readClassList)$incompatibleCountMatrix readClassDt$eqClass.match = match(readClassDt$eqClassById,metadata(readClassList)$eqClassById) metadata(readClassList)$readClassDist = NULL diff --git a/R/bambu_utilityFunctions.R b/R/bambu_utilityFunctions.R index 6037ce2c..cdce9ef4 100644 --- a/R/bambu_utilityFunctions.R +++ b/R/bambu_utilityFunctions.R @@ -221,10 +221,6 @@ calculateDistTable <- function(readClassList, annotations, isoreParameters, verb metadata(readClassDist)$distTable.incompatible = data.table(as.data.frame(metadata(readClassDist)$distTable)) %>% filter(grepl("unidentified", annotationTxId)) %>% distinct(readClassId, .keep_all = TRUE) metadata(readClassDist)$distTable <- genEquiRCsBasedOnObservedReads(readClassDist) - #match count matrix with distTable to speed up calculations - metadata(readClassDist)$countMatrix.matched = - metadata(readClassList)$countMatrix[metadata(readClassDist)$distTable$readClassId,] - colnames(metadata(readClassDist)$countMatrix.matched) = colnames(metadata(readClassList)$countMatrix) return(readClassDist) } From 9e5930f83fb6da6b796f2e5e1ede07c150d43620 Mon Sep 17 00:00:00 2001 From: Andre Date: Fri, 27 Oct 2023 10:19:39 +0800 Subject: [PATCH 065/189] Missed line --- R/bambu.R | 1 + 1 file changed, 1 insertion(+) diff --git a/R/bambu.R b/R/bambu.R index 44321fff..3e96777e 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -193,6 +193,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, metadata(readClassList)$readClassDist <- calculateDistTable(readClassList, annotations, isoreParameters, verbose) readClassList = splitReadClassFiles(readClassList) readClassDt <- genEquiRCs(metadata(readClassList)$readClassDist, annotations, verbose) + countMatrix = metadata(readClassList)$countMatrix incompatibleCountMatrix = metadata(readClassList)$incompatibleCountMatrix readClassDt$eqClass.match = match(readClassDt$eqClassById,metadata(readClassList)$eqClassById) metadata(readClassList)$readClassDist = NULL From 1b664b168bc8880e74393fe64695dce1a27be7d3 Mon Sep 17 00:00:00 2001 From: Andre Date: Fri, 27 Oct 2023 13:50:25 +0800 Subject: [PATCH 066/189] Tidy up --- R/bambu.R | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/R/bambu.R b/R/bambu.R index 3e96777e..5c41a215 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -196,17 +196,16 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, countMatrix = metadata(readClassList)$countMatrix incompatibleCountMatrix = metadata(readClassList)$incompatibleCountMatrix readClassDt$eqClass.match = match(readClassDt$eqClassById,metadata(readClassList)$eqClassById) - metadata(readClassList)$readClassDist = NULL rm(readClassList) gc() GENEIDs.i = as.numeric(factor(unique(mcols(annotations)$GENEID))) - start.ptm <- proc.time() readClassDt <- simplifyNames(readClassDt) readClassDt = readClassDt %>% group_by(eqClassId, gene_sid) %>% mutate(multi_align = length(unique(txid))>1) %>% ungroup() %>% mutate(aval = 1) %>% data.table() + start.ptm <- proc.time() countsSeCompressed <- bplapply(seq_len(ncol(countMatrix)), FUN = function(i){ - print(i) + #print(i) return(bambu.quantify(readClassDt = readClassDt, countMatrix = unname(countMatrix[,i]), incompatibleCountMatrix = data.table(GENEID.i = as.numeric(rownames(incompatibleCountMatrix)), counts = incompatibleCountMatrix[,i]), txid.index = mcols(annotations)$txid, GENEIDs = GENEIDs.i, isoreParameters = isoreParameters, From 0e246414dca9ae5827f6c304f5ee733b9abf71af Mon Sep 17 00:00:00 2001 From: Andre Date: Fri, 27 Oct 2023 14:53:45 +0800 Subject: [PATCH 067/189] Fix bug where reads were missing after splitReadClassFile --- R/bambu-processReads.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/R/bambu-processReads.R b/R/bambu-processReads.R index 20b6c02e..67bb4cf3 100644 --- a/R/bambu-processReads.R +++ b/R/bambu-processReads.R @@ -248,7 +248,7 @@ seqlevelCheckReadsAnnotation <- function(reads, annotations){ splitReadClassFiles = function(readClassFile){ distTable = metadata(metadata(readClassFile)$readClassDist)$distTable eqClasses = distTable %>% group_by(eqClassById) %>% - distinct(eqClassById, readCount,GENEID, .keep_all = TRUE) + distinct(eqClassById, readCount,GENEID, totalWidth, firstExonWidth, .keep_all = TRUE) eqClasses$sampleIDs = rowData(readClassFile)$sampleIDs[match(eqClasses$readClassId, rownames(readClassFile))] eqClasses = eqClasses %>% summarise(nobs = sum(readCount), sampleIDs = list(unlist(sampleIDs))) From 1f22942a29a8f59a205c9c6d51e6eedd974ac876 Mon Sep 17 00:00:00 2001 From: Andre Date: Tue, 31 Oct 2023 12:57:25 +0800 Subject: [PATCH 068/189] Add in helper splitReadClassByRC for old functionality --- R/bambu-processReads.R | 17 ++++++++++++++--- 1 file changed, 14 insertions(+), 3 deletions(-) diff --git a/R/bambu-processReads.R b/R/bambu-processReads.R index 67bb4cf3..fa538c85 100644 --- a/R/bambu-processReads.R +++ b/R/bambu-processReads.R @@ -147,8 +147,8 @@ bambu.processReadsByFile <- function(bam.file, genomeSequence, annotations, } ## add ### - if (isTRUE(demultiplexed)){ - cellBarcodeAssign <- tibble(index = mcols(readGrgList)$id, CB = mcols(readGrgList)$CB) %>% nest(.by = "CB") + #if (isTRUE(demultiplexed)){ + # cellBarcodeAssign <- tibble(index = mcols(readGrgList)$id, CB = mcols(readGrgList)$CB) %>% nest(.by = "CB") # if (!dir.exists("CB")){ # dir.create("CB") @@ -158,7 +158,7 @@ bambu.processReadsByFile <- function(bam.file, genomeSequence, annotations, # invisible(lapply(seq(nrow(cellBarcodeAssign)), # function(x){saveRDS(readGrgList[pull(cellBarcodeAssign$data[[x]])], paste0("CB/", cellBarcodeAssign$CB[[x]],".rds"))})) - } + #} return(readGrgList) } @@ -284,3 +284,14 @@ splitReadClassFiles = function(readClassFile){ metadata(readClassFile)$incompatibleCountMatrix = counts.incompatible return(readClassFile ) } + +splitReadClassFilesByRC = function(readClassFile){ + counts.table = lapply(rowData(readClassFile)$sampleIDs, FUN = function(x){table(x)}) + counts = sparseMatrix( + i = rep(seq_along(counts.table), lengths(counts.table)), + j = as.numeric(names(unlist(counts.table))), + x = unlist(counts.table), + dims = c(nrow(readClassFile), length(metadata(readClassFile)$samples))) + return(counts) +} + From e890af933ef999ae8b1fd61d35a04b9bb5a4681a Mon Sep 17 00:00:00 2001 From: Andre Date: Wed, 1 Nov 2023 11:39:39 +0800 Subject: [PATCH 069/189] Fix bug caused by different sorting of unspliced reads --- R/bambu-processReads_utilityConstructReadClasses.R | 7 ++----- 1 file changed, 2 insertions(+), 5 deletions(-) diff --git a/R/bambu-processReads_utilityConstructReadClasses.R b/R/bambu-processReads_utilityConstructReadClasses.R index 8058ac09..e73aa2da 100644 --- a/R/bambu-processReads_utilityConstructReadClasses.R +++ b/R/bambu-processReads_utilityConstructReadClasses.R @@ -251,12 +251,9 @@ constructUnsplicedReadClasses <- function(reads.singleExon, annotations, mutate(id = mcols(reads.singleExon)$id, sampleID = mcols(reads.singleExon)$sampleID) %>% group_by(seqnames,start,end,strand) %>% - summarise(n=n(), id = list(id), sampleID = list(sampleID)) %>% + summarise(counts=n(), id = list(id), sampleID = list(sampleID)) %>% as.data.frame() - reads.singleExon = unique(reads.singleExon) - mcols(reads.singleExon)$counts <- counts$n - mcols(reads.singleExon)$id <- counts$id - mcols(reads.singleExon)$sampleID <- counts$sampleID + reads.singleExon = GRanges(counts) rcUnsplicedAnnotation <- getUnsplicedReadClassByReference( granges = reads.singleExon, grangesReference = referenceExons, From 1ae237c2b15fb51e7fcdf4a68095835c07964c06 Mon Sep 17 00:00:00 2001 From: Andre Date: Tue, 14 Nov 2023 18:18:42 +0800 Subject: [PATCH 070/189] Stop incompatibleCounts from being converted away from sparseMatrix --- R/bambu_utilityFunctions.R | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/R/bambu_utilityFunctions.R b/R/bambu_utilityFunctions.R index cdce9ef4..7df58f17 100644 --- a/R/bambu_utilityFunctions.R +++ b/R/bambu_utilityFunctions.R @@ -239,9 +239,7 @@ combineCountSes <- function(countsSe, annotations){ if(all(countsMat==0)){return(NULL)} colnames(countsMat) <- sampleNames if (k == "incompatibleCounts"){ - countsMat <- data.table(as.data.frame(as.matrix(countsMat)) %>% - mutate(GENEID = unique(mcols(annotations)$GENEID)) %>% - select(GENEID, everything())) + rownames(countsMat) = unique(mcols(annotations)$GENEID) } return(countsMat) }) From 85292f22ee35cea14e26c58bfb43257305968cee Mon Sep 17 00:00:00 2001 From: Andre Date: Tue, 14 Nov 2023 18:49:56 +0800 Subject: [PATCH 071/189] make transcriptToGene compatible with sparseMatrix --- R/transcriptToGeneExpression.R | 47 ++++++++-------------------------- 1 file changed, 11 insertions(+), 36 deletions(-) diff --git a/R/transcriptToGeneExpression.R b/R/transcriptToGeneExpression.R index b145a2ac..f517633a 100644 --- a/R/transcriptToGeneExpression.R +++ b/R/transcriptToGeneExpression.R @@ -11,30 +11,18 @@ #' )) #' transcriptToGeneExpression(se) transcriptToGeneExpression <- function(se) { - counts <- as.data.table(as.matrix(assays(se)$counts), keep.rownames = TRUE) + counts <- assays(se)$counts runnames <- colnames(counts)[-1] - colnames(counts)[-1] <- rename_duplicatedNames(runnames) - colData(se)@rownames <- rename_duplicatedNames(colData(se)@rownames) - counts <- melt(counts, id.vars = "rn", measure.vars = colnames(counts)[-1]) - setnames(counts, "rn", "TXNAME") rowDataSe <- as.data.table(rowData(se)) - counts <- rowDataSe[, .(TXNAME, GENEID)][counts, on = "TXNAME"] + counts = fac2sparse(rowData(se)$GENEID) %*% counts incompatibleCounts <- metadata(se)$incompatibleCounts - incompatibleCounts[, TXNAME := "incompatible"] - counts_incompatible <- melt(incompatibleCounts, id.vars = c("GENEID","TXNAME"), - measure.vars = setdiff(colnames(incompatibleCounts), c("GENEID","TXNAME"))) - # GENEID, TXNAME, variable, value - counts <- rbind(counts, counts_incompatible[variable %in% unique(counts$variable)]) - counts[, valueGene := sum(value), by = list(variable, GENEID)] - counts[, valueGeneCPM := valueGene / max(sum(value), 1) * 10^6, - by = list(variable)] + incompatibleCounts = incompatibleCounts[match(rownames(counts), rownames(incompatibleCounts)),] + counts = counts + incompatibleCounts + counts.total = colSums(counts) + counts.total[counts.total==0] = 1 + counts.CPM = counts/counts.total * 10^6 - ## counts - counts_gene <- dcast(unique(counts[, .(GENEID, variable, - valueGene)]), GENEID ~ variable, value.var = "valueGene") - counts_gene_CPM <- dcast(unique(counts[, .(GENEID, variable, - valueGeneCPM)]), GENEID ~ variable, value.var = "valueGeneCPM") ## geneRanges exByGene <- reducedRangesByGenes(rowRanges(se)) if ("txClassDescription" %in% colnames(rowDataSe)) { @@ -45,29 +33,16 @@ transcriptToGeneExpression <- function(se) { newGeneClass)])[match(names(exByGene), GENEID)] } ## SE - counts_gene <- setDF(counts_gene) - RowNames <- counts_gene$GENEID - rownames(counts_gene) <- RowNames - counts_gene_CPM <- setDF(counts_gene_CPM) - rownames(counts_gene_CPM) <- RowNames - ColNames <- colnames(counts_gene)[-1] + RowNames <- rownames(counts) + ColNames <- colnames(counts) ColData <- colData(se) ColData@rownames <- ColNames ColData@listData$name <- ColNames seOutput <- SummarizedExperiment( - assays = SimpleList(counts = as.matrix(counts_gene[, -1, drop = FALSE], - ncol = length(ColNames), - dimnames = list(RowNames, ColNames)), - CPM = as.matrix(counts_gene_CPM[match(RowNames, - counts_gene_CPM$GENEID), -1, drop = FALSE], ncol = length(ColNames), - dimnames = list(RowNames, ColNames))), + assays = SimpleList(counts = counts, + CPM = counts.CPM), rowRanges = exByGene[RowNames], colData = ColData) - if(is(assays(se)$counts, "sparseMatrix")) { - assays(seOutput)$counts <- as(assays(seOutput)$counts, "sparseMatrix") - assays(seOutput)$CPM <- as(assays(seOutput)$CPM, "sparseMatrix") - } - return(seOutput) } \ No newline at end of file From 9ab07675a479deea436b9a60e62e888c45392f3e Mon Sep 17 00:00:00 2001 From: Andre Date: Wed, 15 Nov 2023 16:15:32 +0800 Subject: [PATCH 072/189] Enable Bambu to restart with readClassDt to help with R hogging memory --- R/bambu.R | 44 ++++++++++++++++++++++++-------------------- 1 file changed, 24 insertions(+), 20 deletions(-) diff --git a/R/bambu.R b/R/bambu.R index 5c41a215..87064153 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -137,9 +137,9 @@ #' @export bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, opt.discovery = NULL, opt.em = NULL, rcOutDir = NULL, discovery = TRUE, - quant = TRUE, stranded = FALSE, ncore = 1, yieldSize = NULL, + assignDist = TRUE, quant = TRUE, stranded = FALSE, ncore = 1, yieldSize = NULL, trackReads = FALSE, returnDistTable = FALSE, lowMemory = FALSE, - fusionMode = FALSE, verbose = FALSE, demultiplexed = FALSE) { + fusionMode = FALSE, verbose = FALSE, demultiplexed = FALSE, quantData = NULL) { if(is.null(annotations)) { annotations = GRangesList() } else annotations <- checkInputs(annotations, reads, readClass.outputDir = rcOutDir, genomeSequence = genome) @@ -173,41 +173,45 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, } #warnings = handleWarnings(readClassList, verbose) - if (!discovery & !quant) return(readClassList) + if (!discovery & !assignDist & !quant) return(readClassList) if (discovery) { message("--- Start extending annotations ---") annotations <- bambu.extendAnnotations(readClassList, annotations, NDR, isoreParameters, stranded, bpParameters, fusionMode, verbose) metadata(annotations)$warnings = warnings - if (!quant) return(annotations) + if (!quant & !assignDist) return(annotations) } - if (quant) { - message("--- Start isoform quantification ---") - if(length(annotations)==0) stop("No valid annotations, if running - de novo please try less stringent parameters") - + if(assignDist){ + message("--- Start calculate equivilance classes ---") if (is.character(readClassList)) readClassList <- readRDS(file = readClassList) if(is.list(readClassList)) readClassList = readClassList[[1]] metadata(readClassList)$readClassDist <- calculateDistTable(readClassList, annotations, isoreParameters, verbose) readClassList = splitReadClassFiles(readClassList) - readClassDt <- genEquiRCs(metadata(readClassList)$readClassDist, annotations, verbose) - countMatrix = metadata(readClassList)$countMatrix - incompatibleCountMatrix = metadata(readClassList)$incompatibleCountMatrix - readClassDt$eqClass.match = match(readClassDt$eqClassById,metadata(readClassList)$eqClassById) - rm(readClassList) - gc() - GENEIDs.i = as.numeric(factor(unique(mcols(annotations)$GENEID))) - readClassDt <- simplifyNames(readClassDt) - readClassDt = readClassDt %>% group_by(eqClassId, gene_sid) %>% + quantData = list() + quantData$readClassDt <- genEquiRCs(metadata(readClassList)$readClassDist, annotations, verbose) + quantData$countMatrix = metadata(readClassList)$countMatrix + quantData$incompatibleCountMatrix = metadata(readClassList)$incompatibleCountMatrix + quantData$readClassDt$eqClass.match = match(quantData$readClassDt$eqClassById,metadata(readClassList)$eqClassById) + quantData$readClassDt <- simplifyNames(quantData$readClassDt) + quantData$readClassDt = quantData$readClassDt %>% group_by(eqClassId, gene_sid) %>% mutate(multi_align = length(unique(txid))>1) %>% ungroup() %>% mutate(aval = 1) %>% data.table() + if (!quant) return(quantData) + } + + if (quant) { + message("--- Start isoform quantification ---") + if(length(annotations)==0) stop("No valid annotations, if running + de novo please try less stringent parameters") + if(is.null(quantData)) stop("quantData must be provided or assignDist = TRUE") + GENEIDs.i = as.numeric(factor(unique(mcols(annotations)$GENEID))) start.ptm <- proc.time() countsSeCompressed <- bplapply(seq_len(ncol(countMatrix)), FUN = function(i){ #print(i) - return(bambu.quantify(readClassDt = readClassDt, countMatrix = unname(countMatrix[,i]), - incompatibleCountMatrix = data.table(GENEID.i = as.numeric(rownames(incompatibleCountMatrix)), counts = incompatibleCountMatrix[,i]), + return(bambu.quantify(readClassDt = quantData$readClassDt, countMatrix = unname(quantData$countMatrix[,i]), + incompatibleCountMatrix = data.table(GENEID.i = as.numeric(rownames(quantData$incompatibleCountMatrix)), counts = quantData$incompatibleCountMatrix[,i]), txid.index = mcols(annotations)$txid, GENEIDs = GENEIDs.i, isoreParameters = isoreParameters, emParameters = emParameters, trackReads = trackReads, returnDistTable = returnDistTable, verbose = verbose))}, From ff69eac1ddd60db9f5b6444582a3f1b30915ebcf Mon Sep 17 00:00:00 2001 From: Andre Date: Wed, 15 Nov 2023 17:57:43 +0800 Subject: [PATCH 073/189] fix missing reference due to change --- R/bambu.R | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/R/bambu.R b/R/bambu.R index 87064153..e1dea8a7 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -208,7 +208,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, if(is.null(quantData)) stop("quantData must be provided or assignDist = TRUE") GENEIDs.i = as.numeric(factor(unique(mcols(annotations)$GENEID))) start.ptm <- proc.time() - countsSeCompressed <- bplapply(seq_len(ncol(countMatrix)), FUN = function(i){ + countsSeCompressed <- bplapply(seq_len(ncol(quantData$countMatrix)), FUN = function(i){ #print(i) return(bambu.quantify(readClassDt = quantData$readClassDt, countMatrix = unname(quantData$countMatrix[,i]), incompatibleCountMatrix = data.table(GENEID.i = as.numeric(rownames(quantData$incompatibleCountMatrix)), counts = quantData$incompatibleCountMatrix[,i]), @@ -218,7 +218,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, BPPARAM = bpParameters) end.ptm <- proc.time() message("Total Time ", round((end.ptm - start.ptm)[3] / 60, 3), " mins.") - countsSeCompressed$colnames = colnames(countMatrix) + countsSeCompressed$colnames = colnames(quantData$countMatrix) countsSe <- combineCountSes(countsSeCompressed, annotations) #metadata(countsSe)$warnings = warnings From e6fa212a5dd6dbf6dea2e2a526ded92a6fd8eb48 Mon Sep 17 00:00:00 2001 From: Andre Date: Fri, 1 Dec 2023 11:01:32 +0800 Subject: [PATCH 074/189] Resolve lack of incompatible rcs better --- R/bambu_utilityFunctions.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/R/bambu_utilityFunctions.R b/R/bambu_utilityFunctions.R index 7df58f17..6351071d 100644 --- a/R/bambu_utilityFunctions.R +++ b/R/bambu_utilityFunctions.R @@ -236,7 +236,7 @@ combineCountSes <- function(countsSe, annotations){ j = unlist(lapply(seq_along(countsVecList), function(j){rep(j, length(countsVecList[[j]]@i))})), x = unlist(lapply(countsVecList, function(j){j@x})), dims = c(length(countsVecList[[1]]), length(countsVecList))) - if(all(countsMat==0)){return(NULL)} + if(all(is.na(countsMat))){countsMat = matrix(0,nrow(countsMat),ncol(countsMat))} colnames(countsMat) <- sampleNames if (k == "incompatibleCounts"){ rownames(countsMat) = unique(mcols(annotations)$GENEID) From a1de0dc335f237d34a99c92bd9ad65021637dc64 Mon Sep 17 00:00:00 2001 From: Andre Date: Mon, 4 Dec 2023 11:12:36 +0800 Subject: [PATCH 075/189] Insert missing fix for assignGeneIds --- ...processReads_utilityConstructReadClasses.R | 67 ++++++++++--------- 1 file changed, 34 insertions(+), 33 deletions(-) diff --git a/R/bambu-processReads_utilityConstructReadClasses.R b/R/bambu-processReads_utilityConstructReadClasses.R index e73aa2da..fbcc72c5 100644 --- a/R/bambu-processReads_utilityConstructReadClasses.R +++ b/R/bambu-processReads_utilityConstructReadClasses.R @@ -386,13 +386,15 @@ assignGeneIds <- function(grl, annotations, min.exonOverlap = 10, fusionMode = } mcols(grl)$GENEID[strandedRanges] <- assignGeneIdsByReference(grl[strandedRanges], annotations, min.exonOverlap = min.exonOverlap, - fusionMode = fusionMode) + fusionMode = fusionMode) #iteratively assign gene ids for stranded granges newGeneSet <- is.na(mcols(grl)$GENEID) & strandedRanges - referenceGeneSet <- !is.na(mcols(grl)$GENEID) & strandedRanges - mcols(grl)$GENEID[newGeneSet] <- assignGeneIdsByReference(grl[newGeneSet], grl[referenceGeneSet], - min.exonOverlap = min.exonOverlap, - fusionMode = FALSE) # fusion assignment is only done based on original annotations + if(sum(newGeneSet != 0)){ + referenceGeneSet <- !is.na(mcols(grl)$GENEID) & strandedRanges + mcols(grl)$GENEID[newGeneSet] <- assignGeneIdsByReference(grl[newGeneSet], grl[referenceGeneSet], + min.exonOverlap = min.exonOverlap, + fusionMode = FALSE) # fusion assignment is only done based on original annotations + } chainCount <- 1 # first iteration is outside of while loop while(any(!is.na(mcols(grl)$GENEID[newGeneSet])) & chainCount < maxChainIteration) { referenceGeneSet <- newGeneSet & !is.na(mcols(grl)$GENEID) & strandedRanges @@ -410,13 +412,13 @@ assignGeneIds <- function(grl, annotations, min.exonOverlap = 10, fusionMode = mcols(grl)$GENEID[!strandedRanges] <- assignGeneIdsByReference(grl[!strandedRanges], grl[!is.na(mcols(grl)$GENEID)], min.exonOverlap = min.exonOverlap, - fusionMode = FALSE) + fusionMode = FALSE) if(any(is.na(mcols(grl)$GENEID)) & length(annotations)>0) { newGeneSet <- is.na(mcols(grl)$GENEID) mcols(grl)$GENEID[newGeneSet] <- assignGeneIdsByReference(grl[newGeneSet], annotations, min.exonOverlap = min.exonOverlap, - fusionMode = FALSE) + fusionMode = FALSE) } if(any(is.na(mcols(grl)$GENEID))) { @@ -444,32 +446,31 @@ assignGeneIdsByReference <- function(grl, annotations, min.exonOverlap = 10, uniqueHits <- which(queryHits(ov) %in% which(countQueryHits(ov)==1)) geneIds[queryHits(ov)[uniqueHits]] <- names(geneRanges)[subjectHits(ov)[uniqueHits]] - - ## next for non unique hits select one gene (maximum overlap) - multiHits <- which(queryHits(ov) %in% which(countQueryHits(ov)>1)) - expandedRanges <- expandRangesList(ranges(grl[queryHits(ov)[multiHits]]), - ranges(geneRanges[subjectHits(ov)[multiHits]])) - rangeIntersect <- pintersect(expandedRanges, - mcols(expandedRanges)$matchRng, resolve.empty = 'start.x') - intersectById <- tapply(width(rangeIntersect), - mcols(expandedRanges)$IdMap, sum) - - filteredMultiHits <- as_tibble(ov[multiHits]) %>% - mutate(intersectWidth = intersectById) - if(fusionMode) { - filteredMultiHits <- filteredMultiHits %>% - filter(intersectWidth>min.exonOverlap) %>% - mutate(geneid = names(geneRanges)[subjectHits]) %>% distinct() %>% - group_by(queryHits) %>% summarise(geneid = paste(geneid, collapse=':')) - geneIds[filteredMultiHits$queryHits] <- filteredMultiHits$geneid - - } else { - filteredMultiHits <- filteredMultiHits %>% - group_by(queryHits) %>% arrange(desc(intersectWidth)) %>% - dplyr::slice(1) - geneIds[filteredMultiHits$queryHits] <- - names(geneRanges)[filteredMultiHits$subjectHits] - } + if(length(ov)>0){ + ## next for non unique hits select one gene (maximum overlap) + multiHits <- which(queryHits(ov) %in% which(countQueryHits(ov)>1)) + rangeIntersect= intersect(ranges(grl[queryHits(ov)[multiHits]]), + ranges(geneRanges[subjectHits(ov)[multiHits]])) + filteredMultiHits = data.frame(queryHits = queryHits(ov)[multiHits], + intersectWidth = sum(width(rangeIntersect)), + subjectHits = subjectHits(ov)[multiHits]) %>% + group_by(queryHits) %>% summarise(subjectHits = subjectHits[which.max(intersectWidth)], + intersectWidth = max(intersectWidth)) + if(fusionMode) { + filteredMultiHits <- filteredMultiHits %>% + filter(intersectWidth>min.exonOverlap) %>% + mutate(geneid = names(geneRanges)[subjectHits]) %>% distinct() %>% + group_by(queryHits) %>% summarise(geneid = paste(geneid, collapse=':')) + geneIds[filteredMultiHits$queryHits] <- filteredMultiHits$geneid + + } else { + filteredMultiHits <- filteredMultiHits %>% + group_by(queryHits) %>% arrange(desc(intersectWidth)) %>% + dplyr::slice(1) + geneIds[filteredMultiHits$queryHits] <- + names(geneRanges)[filteredMultiHits$subjectHits] + } + } return(geneIds) } From 98c37041419c9f6bb094e0619b8d333efaa7e79c Mon Sep 17 00:00:00 2001 From: Andre Date: Tue, 12 Dec 2023 15:34:37 +0800 Subject: [PATCH 076/189] reallow deg bias --- R/bambu-quantify_utilityFunctions.R | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/R/bambu-quantify_utilityFunctions.R b/R/bambu-quantify_utilityFunctions.R index 821192af..dbcaae63 100644 --- a/R/bambu-quantify_utilityFunctions.R +++ b/R/bambu-quantify_utilityFunctions.R @@ -201,14 +201,14 @@ addAval <- function(readClassDt, emParameters, verbose){ start.ptm <- proc.time() if (d_mode) { d_rateOut <- calculateDegradationRate(readClassDt) + readClassDt <- modifyAvaluewithDegradation_rate(readClassDt, + d_rateOut[1], d_mode = d_mode) }else{ d_rateOut <- rep(NA,2) } end.ptm <- proc.time() if (verbose) message("Finished estimate degradation bias in ", round((end.ptm - start.ptm)[3] / 60, 3), " mins.") -# readClassDt <- modifyAvaluewithDegradation_rate(readClassDt, -# d_rateOut[1], d_mode = d_mode) removeList <- removeUnObservedGenes(readClassDt) readClassDt <- removeList[[1]] # keep only observed genes for estimation outList <- removeList[[2]] #for unobserved genes, set estimates to 0 From a8063cb363b05e01e17dcb0d0c3ff9d9237e1fe9 Mon Sep 17 00:00:00 2001 From: Andre Date: Wed, 20 Dec 2023 11:49:05 +0800 Subject: [PATCH 077/189] Reenable writeBambuOutput --- R/readWrite.R | 14 +------------- 1 file changed, 1 insertion(+), 13 deletions(-) diff --git a/R/readWrite.R b/R/readWrite.R index b317267d..83e171c0 100644 --- a/R/readWrite.R +++ b/R/readWrite.R @@ -35,19 +35,7 @@ writeBambuOutput <- function(se, path, prefix = "") { writeCountsOutput(se, varname=d, feature='transcript',outdir, prefix) } - - seGene <- transcriptToGeneExpression(se[,1]) - - for (i in seq(ceiling(length(colnames(se)) / 100))){ - if (i == ceiling(length(colnames(se)) / 100)){ - seGene <- cbind(seGene, transcriptToGeneExpression(se[,(100*i-99):length(colnames(se))])) - } else{ - seGene <- cbind(seGene, transcriptToGeneExpression(se[,(100*i-99):(100*i)])) - } - } - - seGene <- seGene[,-1] - + seGene <- transcriptToGeneExpression(se) writeCountsOutput(seGene, varname='counts', feature='gene',outdir, prefix) } } From 22702d480eb626a3e98d779dcf15a8acd89695e8 Mon Sep 17 00:00:00 2001 From: lingminhao Date: Fri, 5 Jan 2024 14:59:21 +0800 Subject: [PATCH 078/189] different bam input for CB --- R/prepareDataFromBam.R | 19 ++++++++++++------- 1 file changed, 12 insertions(+), 7 deletions(-) diff --git a/R/prepareDataFromBam.R b/R/prepareDataFromBam.R index f2e7cd26..e1df4fab 100755 --- a/R/prepareDataFromBam.R +++ b/R/prepareDataFromBam.R @@ -29,15 +29,20 @@ prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE, use.n umi <- c() if(demultiplexed) use.names = TRUE while (isIncomplete(bf)) { - readGrgList[[counter]] <- - grglist(readGAlignments(bf, - param = ScanBamParam(flag = - scanBamFlag(isSecondaryAlignment = FALSE)), - use.names = use.names)) + ### add ### + alignmentInfo <- readGAlignments(bf, param = ScanBamParam(tag = c("BC", "UG"), + flag = scanBamFlag(isSecondaryAlignment = FALSE)), + use.names = use.names) + ### add ### + readGrgList[[counter]] <-grglist(alignmentInfo) ### add ### if (isTRUE(demultiplexed)){ - mcols(readGrgList[[counter]])$CB <- substr(names(readGrgList[[counter]]), 1, 16) - mcols(readGrgList[[counter]])$UMI <- substr(names(readGrgList[[counter]]), 18, 29) + mcols(readGrgList[[counter]])$CB <- ifelse(!is.na(mcols(alignmentInfo)$BC), mcols(alignmentInfo)$BC, + substr(names(readGrgList[[counter]]), 1, 16)) + + mcols(readGrgList[[counter]])$UMI <- ifelse(!is.na(mcols(alignmentInfo)$UG), mcols(alignmentInfo)$UG, + substr(names(readGrgList[[counter]]), 18, 29)) + names(readGrgList[[counter]]) <- NULL cells <- unique(c(cells, mcols(readGrgList[[counter]])$CB)) mcols(readGrgList[[counter]])$CB <- factor(mcols(readGrgList[[counter]])$CB, levels = cells) From 3d2b79438a21b827f66c266d1f124ce74cf5b9d1 Mon Sep 17 00:00:00 2001 From: lingminhao Date: Tue, 16 Jan 2024 18:24:19 +0800 Subject: [PATCH 079/189] update quantification output file format --- R/readWrite.R | 25 ++++++++++++++++++------- 1 file changed, 18 insertions(+), 7 deletions(-) diff --git a/R/readWrite.R b/R/readWrite.R index 83e171c0..318da9f0 100644 --- a/R/readWrite.R +++ b/R/readWrite.R @@ -34,9 +34,22 @@ writeBambuOutput <- function(se, path, prefix = "") { for(d in names(assays(se))){ writeCountsOutput(se, varname=d, feature='transcript',outdir, prefix) + print(d) } seGene <- transcriptToGeneExpression(se) writeCountsOutput(seGene, varname='counts', feature='gene',outdir, prefix) + + txANDGenes <- data.table(as.data.frame(rowData(se))[,c("TXNAME","GENEID")]) + utils::write.table(txANDGenes, file = paste0(outdir, "txANDgenes.tsv"), + sep = "\t", quote = FALSE, row.names = FALSE, col.names = FALSE) + utils::write.table(paste0(colnames(se), "-1"), file = paste0(outdir, "barcodes.tsv"), quote = FALSE, row.names = FALSE, col.names = FALSE) + utils::write.table(names(seGene), file = paste0(outdir, "genes.tsv"), + sep = "\t", quote = FALSE, row.names = FALSE, col.names = FALSE) + + R.utils::gzip(paste0(outdir, "txANDgenes.tsv")) + R.utils::gzip(paste0(outdir, "barcodes.tsv")) + R.utils::gzip(paste0(outdir, "genes.tsv")) + } } @@ -46,8 +59,8 @@ writeBambuOutput <- function(se, path, prefix = "") { writeCountsOutput <- function(se, varname = "counts", feature = "transcript", outdir, prefix){ - estimatesfn <- paste(outdir, prefix, varname,"_",feature,".txt", sep = "") if(!is(assays(se)[[varname]], "sparseMatrix")){ + estimatesfn <- paste(outdir, prefix, varname,"_",feature,".txt", sep = "") estimates <- data.table(as.data.frame(assays(se)[[varname]]), keep.rownames = TRUE) if(feature == "transcript"){ @@ -63,16 +76,14 @@ writeCountsOutput <- function(se, varname = "counts", } else{ estimates <- assays(se)[[varname]] if (feature == "transcript"){ + estimatesfn <- paste(outdir, prefix, varname,"_",feature,".mtx", sep = "") Matrix::writeMM(estimates, estimatesfn) - geneIDs <- data.table(as.data.frame(rowData(se))[,c("TXNAME","GENEID")]) - utils::write.table(geneIDs, file = paste0(outdir, "txANDgenes.txt"), - sep = "\t", quote = FALSE, row.names = FALSE, col.names = FALSE) - utils::write.table(colnames(se), file = paste0(outdir, "barcodes.txt"), quote = FALSE, row.names = FALSE, col.names = FALSE) + R.utils::gzip(estimatesfn) } else{ + estimatesfn <- paste(outdir, prefix, varname,"_",feature,".mtx", sep = "") Matrix::writeMM(estimates, estimatesfn) - utils::write.table(names(se), file = paste0(outdir, "genes.txt"), - sep = "\t", quote = FALSE, row.names = FALSE, col.names = FALSE) + R.utils::gzip(estimatesfn) } } } From 74532cf33509de51ede23cf698b92b5dbc382d16 Mon Sep 17 00:00:00 2001 From: lingminhao Date: Fri, 19 Jan 2024 16:56:48 +0800 Subject: [PATCH 080/189] added spatial location information --- R/bambu.R | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/R/bambu.R b/R/bambu.R index e1dea8a7..a67a7397 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -139,7 +139,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, opt.discovery = NULL, opt.em = NULL, rcOutDir = NULL, discovery = TRUE, assignDist = TRUE, quant = TRUE, stranded = FALSE, ncore = 1, yieldSize = NULL, trackReads = FALSE, returnDistTable = FALSE, lowMemory = FALSE, - fusionMode = FALSE, verbose = FALSE, demultiplexed = FALSE, quantData = NULL) { + fusionMode = FALSE, verbose = FALSE, demultiplexed = FALSE, spatial = NULL, quantData = NULL) { if(is.null(annotations)) { annotations = GRangesList() } else annotations <- checkInputs(annotations, reads, readClass.outputDir = rcOutDir, genomeSequence = genome) @@ -226,6 +226,10 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, # generateReadToTranscriptMap(readClass, metadata(readClassDist)$distTable, # annotations) # if (returnDistTable) metadata(seOutput)$distTable = metadata(readClassDist)$distTable + + colData(countsSe) <- DataFrame(read.table(gzfile(spatial), col.names = c("Barcode", "x_coordinate", "y_coordinate")) %>% + filter(Barcode %in% colnames(countsSe)), row.names = colnames(countsSe)) + return(countsSe) } } From 77dae23db6292a7148e8deb5d0273e11b5ff363a Mon Sep 17 00:00:00 2001 From: lingminhao Date: Tue, 23 Jan 2024 14:25:50 +0800 Subject: [PATCH 081/189] updated gzfile function --- R/bambu.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/R/bambu.R b/R/bambu.R index a67a7397..03dc00c1 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -227,7 +227,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, # annotations) # if (returnDistTable) metadata(seOutput)$distTable = metadata(readClassDist)$distTable - colData(countsSe) <- DataFrame(read.table(gzfile(spatial), col.names = c("Barcode", "x_coordinate", "y_coordinate")) %>% + colData(countsSe) <- DataFrame(read.table(R.utils::gzfile(spatial), col.names = c("Barcode", "x_coordinate", "y_coordinate")) %>% filter(Barcode %in% colnames(countsSe)), row.names = colnames(countsSe)) return(countsSe) From c78c793d9bdfaaccd0d51aae9b03aa978c31c409 Mon Sep 17 00:00:00 2001 From: lingminhao Date: Tue, 23 Jan 2024 17:23:18 +0800 Subject: [PATCH 082/189] revert changes in gzfile --- R/bambu.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/R/bambu.R b/R/bambu.R index 03dc00c1..a67a7397 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -227,7 +227,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, # annotations) # if (returnDistTable) metadata(seOutput)$distTable = metadata(readClassDist)$distTable - colData(countsSe) <- DataFrame(read.table(R.utils::gzfile(spatial), col.names = c("Barcode", "x_coordinate", "y_coordinate")) %>% + colData(countsSe) <- DataFrame(read.table(gzfile(spatial), col.names = c("Barcode", "x_coordinate", "y_coordinate")) %>% filter(Barcode %in% colnames(countsSe)), row.names = colnames(countsSe)) return(countsSe) From 95d883066d9aaf7cf09a803683a42e502d999ec0 Mon Sep 17 00:00:00 2001 From: lingminhao Date: Tue, 23 Jan 2024 23:00:42 +0800 Subject: [PATCH 083/189] added ifelse test for spatial --- R/bambu.R | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/R/bambu.R b/R/bambu.R index a67a7397..c4332ca7 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -227,8 +227,10 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, # annotations) # if (returnDistTable) metadata(seOutput)$distTable = metadata(readClassDist)$distTable - colData(countsSe) <- DataFrame(read.table(gzfile(spatial), col.names = c("Barcode", "x_coordinate", "y_coordinate")) %>% - filter(Barcode %in% colnames(countsSe)), row.names = colnames(countsSe)) + if(!is.null(spatial)){ + colData(countsSe) <- DataFrame(read.table(gzfile(spatial), col.names = c("Barcode", "x_coordinate", "y_coordinate")) %>% + filter(Barcode %in% colnames(countsSe)), row.names = colnames(countsSe)) + } return(countsSe) } From 2fd51f8b872fee782b8b2f1a20a69801e84fb746 Mon Sep 17 00:00:00 2001 From: Andre Date: Fri, 2 Feb 2024 10:33:40 +0800 Subject: [PATCH 084/189] Enable fusion mode again --- ...processReads_utilityConstructReadClasses.R | 46 +++++++++++++++++-- 1 file changed, 41 insertions(+), 5 deletions(-) diff --git a/R/bambu-processReads_utilityConstructReadClasses.R b/R/bambu-processReads_utilityConstructReadClasses.R index fbcc72c5..1972dab5 100644 --- a/R/bambu-processReads_utilityConstructReadClasses.R +++ b/R/bambu-processReads_utilityConstructReadClasses.R @@ -453,9 +453,7 @@ assignGeneIdsByReference <- function(grl, annotations, min.exonOverlap = 10, ranges(geneRanges[subjectHits(ov)[multiHits]])) filteredMultiHits = data.frame(queryHits = queryHits(ov)[multiHits], intersectWidth = sum(width(rangeIntersect)), - subjectHits = subjectHits(ov)[multiHits]) %>% - group_by(queryHits) %>% summarise(subjectHits = subjectHits[which.max(intersectWidth)], - intersectWidth = max(intersectWidth)) + subjectHits = subjectHits(ov)[multiHits]) if(fusionMode) { filteredMultiHits <- filteredMultiHits %>% filter(intersectWidth>min.exonOverlap) %>% @@ -465,8 +463,8 @@ assignGeneIdsByReference <- function(grl, annotations, min.exonOverlap = 10, } else { filteredMultiHits <- filteredMultiHits %>% - group_by(queryHits) %>% arrange(desc(intersectWidth)) %>% - dplyr::slice(1) + group_by(queryHits) %>% summarise(subjectHits = subjectHits[which.max(intersectWidth)], + intersectWidth = max(intersectWidth)) geneIds[filteredMultiHits$queryHits] <- names(geneRanges)[filteredMultiHits$subjectHits] } @@ -474,6 +472,44 @@ assignGeneIdsByReference <- function(grl, annotations, min.exonOverlap = 10, return(geneIds) } +# assignGeneIdsByReference <- function(grl, annotations, min.exonOverlap = 10, +# fusionMode=FALSE, prefix = 'Bambu') { +# # (1) assign gene Ids based on first intron match to annotations +# geneRanges <- reducedRangesByGenes(annotations) +# ov=findOverlaps(grl, geneRanges, minoverlap = min.exonOverlap) +# geneIds <- rep(NA, length(grl)) +# uniqueHits <- which(queryHits(ov) %in% which(countQueryHits(ov)==1)) +# geneIds[queryHits(ov)[uniqueHits]] <- +# names(geneRanges)[subjectHits(ov)[uniqueHits]] + +# ## next for non unique hits select one gene (maximum overlap) +# multiHits <- which(queryHits(ov) %in% which(countQueryHits(ov)>1)) +# expandedRanges <- expandRangesList(ranges(grl[queryHits(ov)[multiHits]]), +# ranges(geneRanges[subjectHits(ov)[multiHits]])) +# rangeIntersect <- pintersect(expandedRanges, +# mcols(expandedRanges)$matchRng, resolve.empty = 'start.x') +# intersectById <- tapply(width(rangeIntersect), +# mcols(expandedRanges)$IdMap, sum) + +# filteredMultiHits <- as_tibble(ov[multiHits]) %>% +# mutate(intersectWidth = intersectById) +# if(fusionMode) { +# filteredMultiHits <- filteredMultiHits %>% +# filter(intersectWidth>min.exonOverlap) %>% +# mutate(geneid = names(geneRanges)[subjectHits]) %>% distinct() %>% +# group_by(queryHits) %>% summarise(geneid = paste(geneid, collapse=':')) +# geneIds[filteredMultiHits$queryHits] <- filteredMultiHits$geneid + +# } else { +# filteredMultiHits <- filteredMultiHits %>% +# group_by(queryHits) %>% arrange(desc(intersectWidth)) %>% +# dplyr::slice(1) +# geneIds[filteredMultiHits$queryHits] <- +# names(geneRanges)[filteredMultiHits$subjectHits] +# } +# return(geneIds) +# } + #' Create new gene ids for groups of overlapping read classes which #' don't overlap with known annotations. #' @param grl a GrangesList object with read classes From 11807cd88c4768024e40ddc84f7c86956845084a Mon Sep 17 00:00:00 2001 From: Andre Date: Fri, 2 Feb 2024 10:56:52 +0800 Subject: [PATCH 085/189] Remove warning about bambu annotations if discovery not being done --- R/bambu.R | 2 +- R/bambu_utilityFunctions.R | 6 +++--- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/R/bambu.R b/R/bambu.R index c4332ca7..441491e9 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -142,7 +142,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, fusionMode = FALSE, verbose = FALSE, demultiplexed = FALSE, spatial = NULL, quantData = NULL) { if(is.null(annotations)) { annotations = GRangesList() } else annotations <- checkInputs(annotations, reads, - readClass.outputDir = rcOutDir, genomeSequence = genome) + readClass.outputDir = rcOutDir, genomeSequence = genome, discovery = discovery) isoreParameters <- setIsoreParameters(isoreParameters = opt.discovery) #below line is to be compatible with earlier version of running bambu if(!is.null(isoreParameters$max.txNDR)) NDR = isoreParameters$max.txNDR diff --git a/R/bambu_utilityFunctions.R b/R/bambu_utilityFunctions.R index 6351071d..c977cd40 100644 --- a/R/bambu_utilityFunctions.R +++ b/R/bambu_utilityFunctions.R @@ -74,7 +74,7 @@ updateParameters <- function(Parameters, Parameters.default) { #' @param readClass.outputDir path to readClass output directory #' @importFrom methods is #' @noRd -checkInputs <- function(annotations, reads, readClass.outputDir, genomeSequence){ +checkInputs <- function(annotations, reads, readClass.outputDir, genomeSequence, discovery){ # ===# Check annotation inputs #===# if (!is.null(annotations)) { if (is(annotations, "CompressedGRangesList")) { @@ -97,8 +97,8 @@ checkInputs <- function(annotations, reads, readClass.outputDir, genomeSequence) } else { stop("The annotations is not a GRangesList object a TxDb or a path to a .gtf.") } - if(any(grepl("^BambuGene", names(annotations))) | - any(grepl("^BambuTx", mcols(annotations)$TXNAME))){ + if(discovery & (any(grepl("^BambuGene", names(annotations))) | + any(grepl("^BambuTx", mcols(annotations)$TXNAME)))){ message("Detected Bambu derived annotations in the annotations. ", "Set a new prefix with opt.discovery(list(prefix='newPrefix')) ", "to prevent ambigious id assignment.") From c392d086f9d42155ae2f384f6e367e9a63013af9 Mon Sep 17 00:00:00 2001 From: Andre Date: Thu, 8 Feb 2024 11:12:04 +0800 Subject: [PATCH 086/189] Keep readnames even if demultiplexed --- R/prepareDataFromBam.R | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/R/prepareDataFromBam.R b/R/prepareDataFromBam.R index e1df4fab..ddcaefa3 100755 --- a/R/prepareDataFromBam.R +++ b/R/prepareDataFromBam.R @@ -27,6 +27,7 @@ prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE, use.n counter <- 1 cells <- c() umi <- c() + use.names.OG = use.names if(demultiplexed) use.names = TRUE while (isIncomplete(bf)) { ### add ### @@ -43,7 +44,7 @@ prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE, use.n mcols(readGrgList[[counter]])$UMI <- ifelse(!is.na(mcols(alignmentInfo)$UG), mcols(alignmentInfo)$UG, substr(names(readGrgList[[counter]]), 18, 29)) - names(readGrgList[[counter]]) <- NULL + if(!use.names.OG) {names(readGrgList[[counter]]) <- NULL } cells <- unique(c(cells, mcols(readGrgList[[counter]])$CB)) mcols(readGrgList[[counter]])$CB <- factor(mcols(readGrgList[[counter]])$CB, levels = cells) umi <- unique(c(umi, mcols(readGrgList[[counter]])$UMI)) From 1ed88ebda02b7ea4a399d4f6114eeb130d74a7c8 Mon Sep 17 00:00:00 2001 From: Andre Date: Thu, 8 Feb 2024 18:31:31 +0800 Subject: [PATCH 087/189] Enable messyForest to take in multiple samples can use the sampleName parameter to decide if the barcodes of two different files should be combined or treated as seperate. I.e if you have a technical replicate you would give them the same samplename where as a biological replicate would have different sample names --- R/bambu-processReads.R | 29 ++++++++++++++++++++++------- R/bambu.R | 6 ++++-- R/prepareDataFromBam.R | 2 +- 3 files changed, 27 insertions(+), 10 deletions(-) diff --git a/R/bambu-processReads.R b/R/bambu-processReads.R index fa538c85..76a3ce66 100644 --- a/R/bambu-processReads.R +++ b/R/bambu-processReads.R @@ -15,7 +15,8 @@ bambu.processReads <- function(reads, annotations, genomeSequence, readClass.outputDir=NULL, yieldSize=1000000, bpParameters, stranded=FALSE, verbose=FALSE, isoreParameters = setIsoreParameters(NULL), - lowMemory=FALSE, trackReads = trackReads, fusionMode = fusionMode, demultiplexed = FALSE) { + lowMemory=FALSE, trackReads = trackReads, fusionMode = fusionMode, + demultiplexed = FALSE, sampleNames = NULL) { genomeSequence <- checkInputSequence(genomeSequence) # ===# create BamFileList object from character #===# if (is(reads, "BamFile")) { @@ -39,6 +40,14 @@ bambu.processReads <- function(reads, annotations, genomeSequence, reads <- BamFileList(reads, yieldSize = yieldSize) names(reads) <- tools::file_path_sans_ext(BiocGenerics::basename(reads)) } + if(!is.null(sampleNames)){ + if(length(sampleNames==length(reads))){ + names(reads) <- sampleNames + } else{ + message("Not enough provided sample names. Using them in order of inputted files and the remaining files will use the file names") + names(reads)[seq_along(sampleNames)] <- sampleNames + } + } min.readCount = isoreParameters[["min.readCount"]] fitReadClassModel = isoreParameters[["fitReadClassModel"]] defaultModels = isoreParameters[["defaultModels"]] @@ -54,9 +63,19 @@ bambu.processReads <- function(reads, annotations, genomeSequence, defaultModels = defaultModels, returnModel = returnModel, verbose = verbose, lowMemory = lowMemory, trackReads = trackReads, fusionMode = fusionMode, demultiplexed = demultiplexed, index = i)}, BPPARAM = bpParameters) + + sampleNames = as.numeric(as.factor(sampleNames)) + for(i in seq_along(readGrgList)){ + if(demultiplexed){ + mcols(readGrgList[[i]])$CB = paste0(names(reads)[i], mcols(readGrgList[[i]])$CB) + } else{mcols(readGrgList[[i]])$CB = sampleNames[i]} + mcols(readGrgList[[i]])$CB = as.factor(mcols(readGrgList[[i]])$CB) + } readGrgList = do.call(c, readGrgList) mcols(readGrgList)$id <- seq_along(readGrgList) - + if(demultiplexed){ + mcols(readGrgList)$sampleID = as.numeric(mcols(readGrgList)$CB) + } else {mcols(readGrgList)$sampleID = mcols(readGrgList)$CB} readClassList <- constructReadClasses(readGrgList, genomeSequence = genomeSequence,annotations = annotations, readClass.outputDir = readClass.outputDir, stranded = stranded, min.readCount = min.readCount, @@ -65,7 +84,7 @@ bambu.processReads <- function(reads, annotations, genomeSequence, lowMemory = lowMemory, trackReads = trackReads, fusionMode = fusionMode) metadata(readClassList)$samples = names(reads) - if(demultiplexed)metadata(readClassList)$samples = metadata(readGrgList)$CB + if(demultiplexed)metadata(readClassList)$samples = levels(mcols(readGrgList)$CB) # TODO return output # if (!is.null(readClass.outputDir)) { @@ -121,10 +140,6 @@ bambu.processReadsByFile <- function(bam.file, genomeSequence, annotations, # reassign Ids after seqlevels are dropped mcols(readGrgList)$id <- seq_along(readGrgList) } - if(demultiplexed){ - metadata(readGrgList)$CB = levels(mcols(readGrgList)$CB) - mcols(readGrgList)$sampleID = mcols(readGrgList)$sampleID = as.numeric(mcols(readGrgList)$CB) - } else {mcols(readGrgList)$sampleID = index} #removes reads that are outside genome coordinates badReads = which(max(end(ranges(readGrgList)))>= seqlengths(genomeSequence)[as.character(getChrFromGrList(readGrgList))]) diff --git a/R/bambu.R b/R/bambu.R index 441491e9..d5e74aa6 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -139,7 +139,8 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, opt.discovery = NULL, opt.em = NULL, rcOutDir = NULL, discovery = TRUE, assignDist = TRUE, quant = TRUE, stranded = FALSE, ncore = 1, yieldSize = NULL, trackReads = FALSE, returnDistTable = FALSE, lowMemory = FALSE, - fusionMode = FALSE, verbose = FALSE, demultiplexed = FALSE, spatial = NULL, quantData = NULL) { + fusionMode = FALSE, verbose = FALSE, demultiplexed = FALSE, spatial = NULL, quantData = NULL, + sampleNames = NULL) { if(is.null(annotations)) { annotations = GRangesList() } else annotations <- checkInputs(annotations, reads, readClass.outputDir = rcOutDir, genomeSequence = genome, discovery = discovery) @@ -169,7 +170,8 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, readClass.outputDir = rcOutDir, yieldSize, bpParameters, stranded, verbose, isoreParameters, trackReads = trackReads, fusionMode = fusionMode, - lowMemory = lowMemory, demultiplexed = demultiplexed) + lowMemory = lowMemory, demultiplexed = demultiplexed, + sampleNames = sampleNames) } #warnings = handleWarnings(readClassList, verbose) diff --git a/R/prepareDataFromBam.R b/R/prepareDataFromBam.R index ddcaefa3..8f664d13 100755 --- a/R/prepareDataFromBam.R +++ b/R/prepareDataFromBam.R @@ -64,7 +64,7 @@ prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE, use.n } # remove microexons of width 1bp from list readGrgList <- readGrgList[width(readGrgList) > 1] - + mcols(readGrgList[[counter]])$CB return(readGrgList) } From ab546636a778e73d5faf6f0269f0bf17086c7a8b Mon Sep 17 00:00:00 2001 From: Andre Date: Wed, 21 Feb 2024 17:23:16 +0800 Subject: [PATCH 088/189] Add cleanRead argument This looks at flexiplex reads and only keeps the alignment closest to the barcode to reduce the impact of the duplicated reads creating supplimentary alignments that are barcoded incorrectly --- R/bambu-processReads.R | 10 ++++++---- R/bambu.R | 4 ++-- R/prepareDataFromBam.R | 38 +++++++++++++++++++++++++++++++++----- 3 files changed, 41 insertions(+), 11 deletions(-) diff --git a/R/bambu-processReads.R b/R/bambu-processReads.R index 76a3ce66..f15a2397 100644 --- a/R/bambu-processReads.R +++ b/R/bambu-processReads.R @@ -16,7 +16,7 @@ bambu.processReads <- function(reads, annotations, genomeSequence, readClass.outputDir=NULL, yieldSize=1000000, bpParameters, stranded=FALSE, verbose=FALSE, isoreParameters = setIsoreParameters(NULL), lowMemory=FALSE, trackReads = trackReads, fusionMode = fusionMode, - demultiplexed = FALSE, sampleNames = NULL) { + demultiplexed = FALSE, cleanReads = FALSE, sampleNames = NULL) { genomeSequence <- checkInputSequence(genomeSequence) # ===# create BamFileList object from character #===# if (is(reads, "BamFile")) { @@ -61,7 +61,8 @@ bambu.processReads <- function(reads, annotations, genomeSequence, stranded = stranded, min.readCount = min.readCount, fitReadClassModel = fitReadClassModel, min.exonOverlap = min.exonOverlap, defaultModels = defaultModels, returnModel = returnModel, verbose = verbose, - lowMemory = lowMemory, trackReads = trackReads, fusionMode = fusionMode, demultiplexed = demultiplexed, index = i)}, + lowMemory = lowMemory, trackReads = trackReads, fusionMode = fusionMode, + demultiplexed = demultiplexed, cleanReads = cleanReads, index = i)}, BPPARAM = bpParameters) sampleNames = as.numeric(as.factor(sampleNames)) @@ -112,8 +113,9 @@ bambu.processReads <- function(reads, annotations, genomeSequence, bambu.processReadsByFile <- function(bam.file, genomeSequence, annotations, readClass.outputDir = NULL, yieldSize = NULL, stranded = FALSE, min.readCount = 2, fitReadClassModel = TRUE, min.exonOverlap = 10, defaultModels = NULL, returnModel = FALSE, - verbose = FALSE, lowMemory = FALSE, trackReads = FALSE, fusionMode = FALSE, demultiplexed = FALSE, index = 0) { - readGrgList <- prepareDataFromBam(bam.file[[1]], verbose = verbose, yieldSize = yieldSize, use.names = trackReads, demultiplexed = demultiplexed) + verbose = FALSE, lowMemory = FALSE, trackReads = FALSE, fusionMode = FALSE, demultiplexed = FALSE, + cleanReads = FALSE, index = 0) { + readGrgList <- prepareDataFromBam(bam.file[[1]], verbose = verbose, yieldSize = yieldSize, use.names = trackReads, demultiplexed = demultiplexed, cleanReads = cleanReads) warnings = c() warnings = seqlevelCheckReadsAnnotation(readGrgList, annotations) if(verbose & length(warnings) > 0) warning(paste(warnings,collapse = "\n")) diff --git a/R/bambu.R b/R/bambu.R index d5e74aa6..3ebfe832 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -140,7 +140,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, assignDist = TRUE, quant = TRUE, stranded = FALSE, ncore = 1, yieldSize = NULL, trackReads = FALSE, returnDistTable = FALSE, lowMemory = FALSE, fusionMode = FALSE, verbose = FALSE, demultiplexed = FALSE, spatial = NULL, quantData = NULL, - sampleNames = NULL) { + sampleNames = NULL, cleanReads = FALSE) { if(is.null(annotations)) { annotations = GRangesList() } else annotations <- checkInputs(annotations, reads, readClass.outputDir = rcOutDir, genomeSequence = genome, discovery = discovery) @@ -171,7 +171,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, bpParameters, stranded, verbose, isoreParameters, trackReads = trackReads, fusionMode = fusionMode, lowMemory = lowMemory, demultiplexed = demultiplexed, - sampleNames = sampleNames) + sampleNames = sampleNames, cleanReads = cleanReads) } #warnings = handleWarnings(readClassList, verbose) diff --git a/R/prepareDataFromBam.R b/R/prepareDataFromBam.R index 8f664d13..35d6cc16 100755 --- a/R/prepareDataFromBam.R +++ b/R/prepareDataFromBam.R @@ -7,7 +7,7 @@ #' @importFrom GenomicAlignments grglist readGAlignments #' @importFrom GenomicRanges width #' @noRd -prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE, use.names = FALSE, demultiplexed = NULL) { +prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE, use.names = FALSE, demultiplexed = NULL, cleanReads = FALSE) { if (is(bamFile, "BamFile")) { if (!is.null(yieldSize)) { yieldSize(bamFile) <- yieldSize @@ -30,13 +30,10 @@ prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE, use.n use.names.OG = use.names if(demultiplexed) use.names = TRUE while (isIncomplete(bf)) { - ### add ### alignmentInfo <- readGAlignments(bf, param = ScanBamParam(tag = c("BC", "UG"), flag = scanBamFlag(isSecondaryAlignment = FALSE)), use.names = use.names) - ### add ### readGrgList[[counter]] <-grglist(alignmentInfo) - ### add ### if (isTRUE(demultiplexed)){ mcols(readGrgList[[counter]])$CB <- ifelse(!is.na(mcols(alignmentInfo)$BC), mcols(alignmentInfo)$BC, substr(names(readGrgList[[counter]]), 1, 16)) @@ -50,7 +47,19 @@ prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE, use.n umi <- unique(c(umi, mcols(readGrgList[[counter]])$UMI)) mcols(readGrgList[[counter]])$UMI <- factor(mcols(readGrgList[[counter]])$UMI, levels = umi) } - ### add ### + if(cleanReads){ + softClip5Prime <-pmax(0,as.numeric(gsub('^(\\d*)[S].*','\\1',GenomicAlignments::cigar(reads))), na.rm=T) + softClip3Prime <-pmax(0,as.numeric(gsub('.*\\D(\\d*)[S]$','\\1',GenomicAlignments::cigar(reads))), na.rm=T) + hardClip5Prime <-pmax(0,as.numeric(gsub('^(\\d*)[H].*','\\1',GenomicAlignments::cigar(reads))), na.rm=T) + hardClip3Prime <-pmax(0,as.numeric(gsub('.*\\D(\\d*)[H]$','\\1',GenomicAlignments::cigar(reads))), na.rm=T) + mcols(readGrgList[[counter]])$clip5Prime = pmax(softClip5Prime, hardClip5Prime) + mcols(readGrgList[[counter]])$clip3Prime = pmax(softClip3Prime, hardClip3Prime) + rev = as.vector(strand(reads) == '-') + rev2 = grepl("_-.+of", names(reads)) + temp = mcols(readGrgList[[counter]])$clip5Prime + mcols(readGrgList[[counter]])$clip5Prime[rev != rev2] = mcols(readGrgList[[counter]])$clip3Prime[rev != rev2] + mcols(readGrgList[[counter]])$clip3Prime[rev != rev2] = temp[rev != rev2] + } counter <- counter + 1 } @@ -65,6 +74,25 @@ prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE, use.n # remove microexons of width 1bp from list readGrgList <- readGrgList[width(readGrgList) > 1] mcols(readGrgList[[counter]])$CB + + if(cleanReads){ + #extract duplicated reads from flexiplex to clean + #leave other reads alone as supplimental alignments maybe fusion transcripts + #commented out because it takes awhile + # dt = data.table(name = substr(readNames2,0,nchar(readNames2[1])-2), + # strand = substr(readNames2,nchar(readNames2[1]),nchar(readNames2[1]))) + # dt[, id := .I] + # dt <- dt[, .(ids = list(id), toFilt = any(strand == "+" & strand == "-")), by = name] + # readGrgList.keep = readGrgList[c(dt$ids[!dt$toFilt])] + # readGrgList.filt = readGrgList[c(dt$ids[dt$toFilt])] + + df = data.frame(name = names(readGrgList), + clip5 = mcols(readGrgList)$clip5Prime) + df = df %>% mutate(id = row_number()) %>% group_by(name) %>% summarise(primary.id = id[which.mix(clip5)]) + readGrgList = unname(readGrgList[df$primary.id]) + #readGrgList = c(readGrgList.filt, unname(readGrgList.keep)) + } + return(readGrgList) } From 6ec31de63a714844c322b16fe33d73740e520362 Mon Sep 17 00:00:00 2001 From: Andre Date: Thu, 29 Feb 2024 13:57:28 +0800 Subject: [PATCH 089/189] Tidy up clean reads --- R/prepareDataFromBam.R | 24 +++++++++++------------- 1 file changed, 11 insertions(+), 13 deletions(-) diff --git a/R/prepareDataFromBam.R b/R/prepareDataFromBam.R index 35d6cc16..0230adc6 100755 --- a/R/prepareDataFromBam.R +++ b/R/prepareDataFromBam.R @@ -7,7 +7,8 @@ #' @importFrom GenomicAlignments grglist readGAlignments #' @importFrom GenomicRanges width #' @noRd -prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE, use.names = FALSE, demultiplexed = NULL, cleanReads = FALSE) { +prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE, + use.names = FALSE, demultiplexed = FALSE, cleanReads = FALSE) { if (is(bamFile, "BamFile")) { if (!is.null(yieldSize)) { yieldSize(bamFile) <- yieldSize @@ -28,7 +29,7 @@ prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE, use.n cells <- c() umi <- c() use.names.OG = use.names - if(demultiplexed) use.names = TRUE + if(demultiplexed | cleanReads) use.names = TRUE while (isIncomplete(bf)) { alignmentInfo <- readGAlignments(bf, param = ScanBamParam(tag = c("BC", "UG"), flag = scanBamFlag(isSecondaryAlignment = FALSE)), @@ -41,21 +42,20 @@ prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE, use.n mcols(readGrgList[[counter]])$UMI <- ifelse(!is.na(mcols(alignmentInfo)$UG), mcols(alignmentInfo)$UG, substr(names(readGrgList[[counter]]), 18, 29)) - if(!use.names.OG) {names(readGrgList[[counter]]) <- NULL } cells <- unique(c(cells, mcols(readGrgList[[counter]])$CB)) mcols(readGrgList[[counter]])$CB <- factor(mcols(readGrgList[[counter]])$CB, levels = cells) umi <- unique(c(umi, mcols(readGrgList[[counter]])$UMI)) mcols(readGrgList[[counter]])$UMI <- factor(mcols(readGrgList[[counter]])$UMI, levels = umi) } if(cleanReads){ - softClip5Prime <-pmax(0,as.numeric(gsub('^(\\d*)[S].*','\\1',GenomicAlignments::cigar(reads))), na.rm=T) - softClip3Prime <-pmax(0,as.numeric(gsub('.*\\D(\\d*)[S]$','\\1',GenomicAlignments::cigar(reads))), na.rm=T) - hardClip5Prime <-pmax(0,as.numeric(gsub('^(\\d*)[H].*','\\1',GenomicAlignments::cigar(reads))), na.rm=T) - hardClip3Prime <-pmax(0,as.numeric(gsub('.*\\D(\\d*)[H]$','\\1',GenomicAlignments::cigar(reads))), na.rm=T) + softClip5Prime <-pmax(0,as.numeric(gsub('^(\\d*)[S].*','\\1',GenomicAlignments::cigar(alignmentInfo))), na.rm=T) + softClip3Prime <-pmax(0,as.numeric(gsub('.*\\D(\\d*)[S]$','\\1',GenomicAlignments::cigar(alignmentInfo))), na.rm=T) + hardClip5Prime <-pmax(0,as.numeric(gsub('^(\\d*)[H].*','\\1',GenomicAlignments::cigar(alignmentInfo))), na.rm=T) + hardClip3Prime <-pmax(0,as.numeric(gsub('.*\\D(\\d*)[H]$','\\1',GenomicAlignments::cigar(alignmentInfo))), na.rm=T) mcols(readGrgList[[counter]])$clip5Prime = pmax(softClip5Prime, hardClip5Prime) mcols(readGrgList[[counter]])$clip3Prime = pmax(softClip3Prime, hardClip3Prime) - rev = as.vector(strand(reads) == '-') - rev2 = grepl("_-.+of", names(reads)) + rev = as.vector(strand(alignmentInfo) == '-') + rev2 = grepl("_-.+of", names(alignmentInfo)) temp = mcols(readGrgList[[counter]])$clip5Prime mcols(readGrgList[[counter]])$clip5Prime[rev != rev2] = mcols(readGrgList[[counter]])$clip3Prime[rev != rev2] mcols(readGrgList[[counter]])$clip3Prime[rev != rev2] = temp[rev != rev2] @@ -73,8 +73,6 @@ prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE, use.n } # remove microexons of width 1bp from list readGrgList <- readGrgList[width(readGrgList) > 1] - mcols(readGrgList[[counter]])$CB - if(cleanReads){ #extract duplicated reads from flexiplex to clean #leave other reads alone as supplimental alignments maybe fusion transcripts @@ -88,11 +86,11 @@ prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE, use.n df = data.frame(name = names(readGrgList), clip5 = mcols(readGrgList)$clip5Prime) - df = df %>% mutate(id = row_number()) %>% group_by(name) %>% summarise(primary.id = id[which.mix(clip5)]) + df = df %>% mutate(id = row_number()) %>% group_by(name) %>% summarise(primary.id = id[which.min(clip5)]) readGrgList = unname(readGrgList[df$primary.id]) #readGrgList = c(readGrgList.filt, unname(readGrgList.keep)) } - + if(!use.names.OG) {names(readGrgList) <- NULL } return(readGrgList) } From fac48720d05a8d28e5ac8eb1d46728550d00dd3f Mon Sep 17 00:00:00 2001 From: Andre Date: Tue, 5 Mar 2024 15:27:52 +0800 Subject: [PATCH 090/189] UMI deduplication --- R/prepareDataFromBam.R | 17 +++++++++++++++++ 1 file changed, 17 insertions(+) diff --git a/R/prepareDataFromBam.R b/R/prepareDataFromBam.R index 0230adc6..178b9566 100755 --- a/R/prepareDataFromBam.R +++ b/R/prepareDataFromBam.R @@ -84,10 +84,27 @@ prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE, # readGrgList.keep = readGrgList[c(dt$ids[!dt$toFilt])] # readGrgList.filt = readGrgList[c(dt$ids[dt$toFilt])] + #UMI deduplication by barcode + start.ptm <- proc.time() + print(length(readGrgList)) + df = data.frame(umi = mcols(readGrgList)$CB, + barcode = mcols(readGrgList)$UMI, + lengths = sum(width(readGrgList))) + df = df %>% mutate(id = row_number()) %>% group_by(barcode, umi) %>% summarise(primary.id = id[which.max(lengths)]) + readGrgList = unname(readGrgList[df$primary.id]) + print(length(readGrgList)) + end.ptm <- proc.time() + message("UMI deduplication Time ", round((end.ptm - start.ptm)[3] / 60, 3), " mins.") + #select alignments closest to barcode + start.ptm <- proc.time() + print(length(readGrgList)) df = data.frame(name = names(readGrgList), clip5 = mcols(readGrgList)$clip5Prime) df = df %>% mutate(id = row_number()) %>% group_by(name) %>% summarise(primary.id = id[which.min(clip5)]) readGrgList = unname(readGrgList[df$primary.id]) + print(length(readGrgList)) + end.ptm <- proc.time() + message("Primary alignment selection Time ", round((end.ptm - start.ptm)[3] / 60, 3), " mins.") #readGrgList = c(readGrgList.filt, unname(readGrgList.keep)) } if(!use.names.OG) {names(readGrgList) <- NULL } From 26afc663f20e34d667b1744d8ea3104d9b763595 Mon Sep 17 00:00:00 2001 From: Andre Date: Tue, 12 Mar 2024 17:03:09 +0800 Subject: [PATCH 091/189] change order of UMI dedup with cleaning reads --- R/prepareDataFromBam.R | 24 +++++++++++++----------- 1 file changed, 13 insertions(+), 11 deletions(-) diff --git a/R/prepareDataFromBam.R b/R/prepareDataFromBam.R index 178b9566..1e558f5f 100755 --- a/R/prepareDataFromBam.R +++ b/R/prepareDataFromBam.R @@ -84,6 +84,17 @@ prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE, # readGrgList.keep = readGrgList[c(dt$ids[!dt$toFilt])] # readGrgList.filt = readGrgList[c(dt$ids[dt$toFilt])] + #select alignments closest to barcode + start.ptm <- proc.time() + print(length(readGrgList)) + df = data.frame(name = names(readGrgList), + clip5 = mcols(readGrgList)$clip5Prime) + df = df %>% mutate(id = row_number()) %>% group_by(name) %>% summarise(primary.id = id[which.min(clip5)]) + readGrgList = unname(readGrgList[df$primary.id]) + print(length(readGrgList)) + end.ptm <- proc.time() + message("Primary alignment selection Time ", round((end.ptm - start.ptm)[3] / 60, 3), " mins.") + #UMI deduplication by barcode start.ptm <- proc.time() print(length(readGrgList)) @@ -91,20 +102,11 @@ prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE, barcode = mcols(readGrgList)$UMI, lengths = sum(width(readGrgList))) df = df %>% mutate(id = row_number()) %>% group_by(barcode, umi) %>% summarise(primary.id = id[which.max(lengths)]) - readGrgList = unname(readGrgList[df$primary.id]) + readGrgList = readGrgList[df$primary.id] print(length(readGrgList)) end.ptm <- proc.time() message("UMI deduplication Time ", round((end.ptm - start.ptm)[3] / 60, 3), " mins.") - #select alignments closest to barcode - start.ptm <- proc.time() - print(length(readGrgList)) - df = data.frame(name = names(readGrgList), - clip5 = mcols(readGrgList)$clip5Prime) - df = df %>% mutate(id = row_number()) %>% group_by(name) %>% summarise(primary.id = id[which.min(clip5)]) - readGrgList = unname(readGrgList[df$primary.id]) - print(length(readGrgList)) - end.ptm <- proc.time() - message("Primary alignment selection Time ", round((end.ptm - start.ptm)[3] / 60, 3), " mins.") + #readGrgList = c(readGrgList.filt, unname(readGrgList.keep)) } if(!use.names.OG) {names(readGrgList) <- NULL } From f31c1825241d4f24213a69d090393c983f1e8fde Mon Sep 17 00:00:00 2001 From: Andre Date: Tue, 12 Mar 2024 17:32:06 +0800 Subject: [PATCH 092/189] add extra messages --- R/bambu-extendAnnotations-utilityCombine.R | 2 ++ 1 file changed, 2 insertions(+) diff --git a/R/bambu-extendAnnotations-utilityCombine.R b/R/bambu-extendAnnotations-utilityCombine.R index cdf0c5ef..58ec1dfa 100644 --- a/R/bambu-extendAnnotations-utilityCombine.R +++ b/R/bambu-extendAnnotations-utilityCombine.R @@ -14,10 +14,12 @@ isore.combineTranscriptCandidates <- function(readClassList, stranded, ## stranded used for unspliced reduce min.readCount , min.readFractionByGene, min.txScore.multiExon, min.txScore.singleExon, bpParameters ,verbose){ + message("starting combineSplicedTranscriptModels") combinedSplicedTranscripts <- combineSplicedTranscriptModels(readClassList, bpParameters, min.readCount, min.readFractionByGene, min.txScore.multiExon, min.txScore.singleExon, verbose) %>% data.table() + message("finished combineSplicedTranscriptModels") combinedSplicedTranscripts[,confidenceType := "highConfidenceJunctionReads"] return(combinedSplicedTranscripts) # combinedUnsplicedTranscripts <- From cb12d54908bd26c44a8ea7a99a84bb003d4fc6e4 Mon Sep 17 00:00:00 2001 From: Andre Date: Tue, 19 Mar 2024 16:37:06 +0800 Subject: [PATCH 093/189] add in argument --- R/bambu-processReads.R | 7 ++++--- R/bambu.R | 4 ++-- 2 files changed, 6 insertions(+), 5 deletions(-) diff --git a/R/bambu-processReads.R b/R/bambu-processReads.R index f15a2397..0863ca3d 100644 --- a/R/bambu-processReads.R +++ b/R/bambu-processReads.R @@ -16,7 +16,7 @@ bambu.processReads <- function(reads, annotations, genomeSequence, readClass.outputDir=NULL, yieldSize=1000000, bpParameters, stranded=FALSE, verbose=FALSE, isoreParameters = setIsoreParameters(NULL), lowMemory=FALSE, trackReads = trackReads, fusionMode = fusionMode, - demultiplexed = FALSE, cleanReads = FALSE, sampleNames = NULL) { + demultiplexed = FALSE, cleanReads = FALSE, sampleNames = NULL, barcodesToFilter = NULL) { genomeSequence <- checkInputSequence(genomeSequence) # ===# create BamFileList object from character #===# if (is(reads, "BamFile")) { @@ -62,7 +62,7 @@ bambu.processReads <- function(reads, annotations, genomeSequence, fitReadClassModel = fitReadClassModel, min.exonOverlap = min.exonOverlap, defaultModels = defaultModels, returnModel = returnModel, verbose = verbose, lowMemory = lowMemory, trackReads = trackReads, fusionMode = fusionMode, - demultiplexed = demultiplexed, cleanReads = cleanReads, index = i)}, + demultiplexed = demultiplexed, cleanReads = cleanReads, index = i, barcodesToFilter = barcodesToFilter)}, BPPARAM = bpParameters) sampleNames = as.numeric(as.factor(sampleNames)) @@ -114,9 +114,10 @@ bambu.processReadsByFile <- function(bam.file, genomeSequence, annotations, readClass.outputDir = NULL, yieldSize = NULL, stranded = FALSE, min.readCount = 2, fitReadClassModel = TRUE, min.exonOverlap = 10, defaultModels = NULL, returnModel = FALSE, verbose = FALSE, lowMemory = FALSE, trackReads = FALSE, fusionMode = FALSE, demultiplexed = FALSE, - cleanReads = FALSE, index = 0) { + cleanReads = FALSE, index = 0, barcodesToFilter = NULL) { readGrgList <- prepareDataFromBam(bam.file[[1]], verbose = verbose, yieldSize = yieldSize, use.names = trackReads, demultiplexed = demultiplexed, cleanReads = cleanReads) warnings = c() + if(!is.null(barcodesToFilter) & demultiplexed){ readGrgList = readGrgList[!mcols(readGrgList)$CB %in% barcodesToFilter]} warnings = seqlevelCheckReadsAnnotation(readGrgList, annotations) if(verbose & length(warnings) > 0) warning(paste(warnings,collapse = "\n")) #check seqlevels for consistency, drop ranges not present in genomeSequence diff --git a/R/bambu.R b/R/bambu.R index 3ebfe832..ef8ba677 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -140,7 +140,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, assignDist = TRUE, quant = TRUE, stranded = FALSE, ncore = 1, yieldSize = NULL, trackReads = FALSE, returnDistTable = FALSE, lowMemory = FALSE, fusionMode = FALSE, verbose = FALSE, demultiplexed = FALSE, spatial = NULL, quantData = NULL, - sampleNames = NULL, cleanReads = FALSE) { + sampleNames = NULL, cleanReads = FALSE, barcodesToFilter = NULL) { if(is.null(annotations)) { annotations = GRangesList() } else annotations <- checkInputs(annotations, reads, readClass.outputDir = rcOutDir, genomeSequence = genome, discovery = discovery) @@ -171,7 +171,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, bpParameters, stranded, verbose, isoreParameters, trackReads = trackReads, fusionMode = fusionMode, lowMemory = lowMemory, demultiplexed = demultiplexed, - sampleNames = sampleNames, cleanReads = cleanReads) + sampleNames = sampleNames, cleanReads = cleanReads, barcodesToFilter = barcodesToFilter) } #warnings = handleWarnings(readClassList, verbose) From a1484654be753d3bd5928ef3a9568ccc0f318f2b Mon Sep 17 00:00:00 2001 From: Andre Date: Mon, 1 Apr 2024 15:02:41 +0800 Subject: [PATCH 094/189] Transcript discovery at cluster level --- R/bambu.R | 55 ++++++++++++++++++++++++++++++++++++++++++++++++++++++- 1 file changed, 54 insertions(+), 1 deletion(-) diff --git a/R/bambu.R b/R/bambu.R index ef8ba677..5e2db7fc 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -140,7 +140,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, assignDist = TRUE, quant = TRUE, stranded = FALSE, ncore = 1, yieldSize = NULL, trackReads = FALSE, returnDistTable = FALSE, lowMemory = FALSE, fusionMode = FALSE, verbose = FALSE, demultiplexed = FALSE, spatial = NULL, quantData = NULL, - sampleNames = NULL, cleanReads = FALSE, barcodesToFilter = NULL) { + sampleNames = NULL, cleanReads = FALSE, barcodesToFilter = NULL, clustering = NULL) { if(is.null(annotations)) { annotations = GRangesList() } else annotations <- checkInputs(annotations, reads, readClass.outputDir = rcOutDir, genomeSequence = genome, discovery = discovery) @@ -182,6 +182,59 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, isoreParameters, stranded, bpParameters, fusionMode, verbose) metadata(annotations)$warnings = warnings + #### split rcf into clusters + if(!is.null(clustering)){ + message("--- Start extending annotations for clusters ---") + #if clustering is a csv, create a list with the barcodes for each cluster + #csv must have two cols with heading barcode, cluster + if(!is.list(clustering)){ + clustering = read.csv(clustering) + clustering = clustering %>% group_by(cluster) %>% summarise(barcodes = list(barcode)) + clusters = clustering$cluster + clustering = clustering$barcodes + names(clustering) = clusters + } + annotations.clusters = list() + rcfs.clusters = list() + clusters.rc = splitReadClassFilesByRC(readClassList[[1]]) + txScores = c() + for(i in seq_along(clustering)){ + print(names(clustering)[i]) + ###TODO need to account for the sample name here which is added to the barcode + index = match(clustering[[i]],gsub('demultiplexed','',metadata(rcf[[1]])$samples)) + index = index[!is.na(index)] + print(length(index)) + if(length(index)<20) next + rcf.counts = clusters.rc[,index] + rcf.filt = readClassList[[1]][rowSums(rcf.counts)>0,] + rowData(rcf.filt)$readCount = rowSums(rcf.counts)[rowSums(rcf.counts)>0] + countsTBL = calculateGeneProportion(counts=mcols(rcf.filt)$readCount, + geneIds=mcols(rcf.filt)$GENEID) + rowData(rcf.filt)$geneReadProp = countsTBL$geneReadProp + rowData(rcf.filt)$geneReadCount = countsTBL$geneReadCount + rowData(rcf.filt)$startSD = 0 + rowData(rcf.filt)$endSD = 0 + rowData(rcf.filt)$readCount.posStrand = 0 + thresholdIndex = which(rowData(rcf.filt)$readCount>=2) + model = trainBambu(rcf.filt, verbose = TRUE, min.readCount = 2) + txScore = getTranscriptScore(rowData(rcf.filt)[thresholdIndex,], model, + defaultModels) + rowData(rcf.filt)$txScore = rep(NA,nrow(rcf.filt)) + rowData(rcf.filt)$txScore[thresholdIndex] = txScore + #txScores = cbind(txScores, rowData(rcf.filt)$txScore) + rcfs.clusters[[names(clustering)[i]]] = rcf.filt + annotations.clusters[[names(clustering)[i]]] <- bambu.extendAnnotations(list(rcf.filt), annotations, NDR, + isoreParameters, stranded, bpParameters, fusionMode, verbose) + } + print("test") + if(length(rcfs.clusters)>0){ + print("--- Merging all individual clusters ---") + annotations.clusters[["merged"]] <- bambu.extendAnnotations(rcfs.clusters, annotations, NDR, + isoreParameters, stranded, bpParameters, fusionMode, verbose) + } + metadata(annotations)$clusters = annotations.clusters + } + if (!quant & !assignDist) return(annotations) } From 089f86b98fc1783e403d9a0221ca071d2aebc3a2 Mon Sep 17 00:00:00 2001 From: Andre Date: Thu, 11 Apr 2024 11:30:41 +0800 Subject: [PATCH 095/189] keep txScore in extendAnno --- R/bambu-extendAnnotations-utilityExtend.R | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/R/bambu-extendAnnotations-utilityExtend.R b/R/bambu-extendAnnotations-utilityExtend.R index b675f2c4..cc7fba6c 100644 --- a/R/bambu-extendAnnotations-utilityExtend.R +++ b/R/bambu-extendAnnotations-utilityExtend.R @@ -626,7 +626,7 @@ combineWithAnnotations <- function(rowDataCombinedFiltered, extendedAnnotationRanges <- exonRangesCombinedFiltered mcols(extendedAnnotationRanges) <- rowDataCombinedFiltered[, c("GENEID", "novelGene", "novelTranscript", "txClassDescription","readCount", "NDR", - "relReadCount", "relSubsetCount")] + "maxTxScore", "relReadCount", "relSubsetCount")] equalRanges = rowDataCombinedFiltered[!is.na(rowDataCombinedFiltered$TXNAME),] #remove extended ranges that are already present in annotation extendedAnnotationRanges <- extendedAnnotationRanges[is.na(rowDataCombinedFiltered$TXNAME)] @@ -637,9 +637,11 @@ combineWithAnnotations <- function(rowDataCombinedFiltered, mcols(annotationRangesToMerge)$novelTranscript <- FALSE mcols(annotationRangesToMerge)$novelGene <- FALSE mcols(annotationRangesToMerge)$NDR <- NA + mcols(annotationRangesToMerge)$txScore <- NA mcols(extendedAnnotationRanges) <- mcols(extendedAnnotationRanges)[,colnames(mcols(extendedAnnotationRanges))] #copy over stats to annotations from read classes mcols(annotationRangesToMerge[equalRanges$TXNAME])$NDR = equalRanges$NDR + mcols(annotationRangesToMerge[equalRanges$TXNAME])$maxTxScore = equalRanges$maxTxScore mcols(annotationRangesToMerge[equalRanges$TXNAME])$readCount = equalRanges$readCount mcols(annotationRangesToMerge[equalRanges$TXNAME])$relReadCount = equalRanges$relReadCount mcols(annotationRangesToMerge[equalRanges$TXNAME])$relSubsetCount = equalRanges$relSubsetCount @@ -662,7 +664,7 @@ combineWithAnnotations <- function(rowDataCombinedFiltered, if(!identical(names(extendedAnnotationRanges),minEqClasses$queryTxId)) warning('eq classes might be incorrect') mcols(extendedAnnotationRanges)$eqClassById <- minEqClasses$eqClassById mcols(extendedAnnotationRanges) <- mcols(extendedAnnotationRanges)[, - c("TXNAME", "GENEID", "NDR", "novelGene", "novelTranscript", "txClassDescription","readCount","relReadCount", "relSubsetCount", "txid", "eqClassById")] + c("TXNAME", "GENEID", "NDR", "maxTxScore", "novelGene", "novelTranscript", "txClassDescription","readCount","relReadCount", "relSubsetCount", "txid", "eqClassById")] return(extendedAnnotationRanges) } From 50a00903a6c8aeb3bd00915ef9acc80174c7616c Mon Sep 17 00:00:00 2001 From: Andre Date: Fri, 12 Apr 2024 15:53:18 +0800 Subject: [PATCH 096/189] Allow demultiplexing from file File should have 3 coloums, readName, BC, and UMI --- R/bambu-processReads.R | 6 +++--- R/bambu_utilityFunctions.R | 2 +- R/prepareDataFromBam.R | 25 +++++++++++++++++-------- 3 files changed, 21 insertions(+), 12 deletions(-) diff --git a/R/bambu-processReads.R b/R/bambu-processReads.R index f15a2397..bf9bebca 100644 --- a/R/bambu-processReads.R +++ b/R/bambu-processReads.R @@ -67,14 +67,14 @@ bambu.processReads <- function(reads, annotations, genomeSequence, sampleNames = as.numeric(as.factor(sampleNames)) for(i in seq_along(readGrgList)){ - if(demultiplexed){ + if(!isFALSE(demultiplexed)){ mcols(readGrgList[[i]])$CB = paste0(names(reads)[i], mcols(readGrgList[[i]])$CB) } else{mcols(readGrgList[[i]])$CB = sampleNames[i]} mcols(readGrgList[[i]])$CB = as.factor(mcols(readGrgList[[i]])$CB) } readGrgList = do.call(c, readGrgList) mcols(readGrgList)$id <- seq_along(readGrgList) - if(demultiplexed){ + if(!isFALSE(demultiplexed)){ mcols(readGrgList)$sampleID = as.numeric(mcols(readGrgList)$CB) } else {mcols(readGrgList)$sampleID = mcols(readGrgList)$CB} readClassList <- constructReadClasses(readGrgList, genomeSequence = genomeSequence,annotations = annotations, @@ -85,7 +85,7 @@ bambu.processReads <- function(reads, annotations, genomeSequence, lowMemory = lowMemory, trackReads = trackReads, fusionMode = fusionMode) metadata(readClassList)$samples = names(reads) - if(demultiplexed)metadata(readClassList)$samples = levels(mcols(readGrgList)$CB) + if(!isFALSE(demultiplexed))metadata(readClassList)$samples = levels(mcols(readGrgList)$CB) # TODO return output # if (!is.null(readClass.outputDir)) { diff --git a/R/bambu_utilityFunctions.R b/R/bambu_utilityFunctions.R index c977cd40..db60b55e 100644 --- a/R/bambu_utilityFunctions.R +++ b/R/bambu_utilityFunctions.R @@ -9,7 +9,7 @@ setBiocParallelParameters <- function(reads, ncore, verbose, demultiplexed){ "to resolve the issue that originates from the XGboost package.") bpParameters <- bpparam() #===# set parallel options: otherwise use parallel to distribute samples - bpParameters$workers <- ifelse(length(reads) == 1 & !demultiplexed, 1, ncore) + bpParameters$workers <- ifelse(length(reads) == 1 & isFALSE(demultiplexed), 1, ncore) bpParameters$progressbar <- ifelse(length(reads) > 1 & !verbose, TRUE, FALSE) return(bpParameters) } diff --git a/R/prepareDataFromBam.R b/R/prepareDataFromBam.R index 1e558f5f..a978959d 100755 --- a/R/prepareDataFromBam.R +++ b/R/prepareDataFromBam.R @@ -29,19 +29,28 @@ prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE, cells <- c() umi <- c() use.names.OG = use.names - if(demultiplexed | cleanReads) use.names = TRUE + if(!isFALSE(demultiplexed) | cleanReads) use.names = TRUE + if(grepl(".[ct]sv$",demultiplexed)){ + readMap = read.table(demultiplexed, + sep = ifelse(grepl(".tsv$",demultiplexed), "\t", ","), header = FALSE) + } while (isIncomplete(bf)) { alignmentInfo <- readGAlignments(bf, param = ScanBamParam(tag = c("BC", "UG"), flag = scanBamFlag(isSecondaryAlignment = FALSE)), use.names = use.names) readGrgList[[counter]] <-grglist(alignmentInfo) - if (isTRUE(demultiplexed)){ - mcols(readGrgList[[counter]])$CB <- ifelse(!is.na(mcols(alignmentInfo)$BC), mcols(alignmentInfo)$BC, - substr(names(readGrgList[[counter]]), 1, 16)) - - mcols(readGrgList[[counter]])$UMI <- ifelse(!is.na(mcols(alignmentInfo)$UG), mcols(alignmentInfo)$UG, - substr(names(readGrgList[[counter]]), 18, 29)) - + if (!isFALSE(demultiplexed)){ + if(isTRUE(demultiplexed)){ + mcols(readGrgList[[counter]])$CB <- ifelse(!is.na(mcols(alignmentInfo)$BC), mcols(alignmentInfo)$BC, + substr(names(readGrgList[[counter]]), 1, 16)) + mcols(readGrgList[[counter]])$UMI <- ifelse(!is.na(mcols(alignmentInfo)$UG), mcols(alignmentInfo)$UG, + substr(names(readGrgList[[counter]]), 18, 29)) + } else{ + mcols(readGrgList[[counter]])$CB = "NA" + mcols(readGrgList[[counter]])$UMI = "NA" + mcols(readGrgList[[counter]])$CB = readMap[,2][match(names(readGrgList[[counter]]),readMap[,1])] + mcols(readGrgList[[counter]])$UMI = readMap[,3][match(names(readGrgList[[counter]]),readMap[,1])] + } cells <- unique(c(cells, mcols(readGrgList[[counter]])$CB)) mcols(readGrgList[[counter]])$CB <- factor(mcols(readGrgList[[counter]])$CB, levels = cells) umi <- unique(c(umi, mcols(readGrgList[[counter]])$UMI)) From 76681eab2fa91f2e1be1a6d3dc857fc8b5004d2a Mon Sep 17 00:00:00 2001 From: Andre Date: Fri, 19 Apr 2024 14:40:22 +0800 Subject: [PATCH 097/189] Flexible BC and UMI lengths Also will warn if UMIs arn't provided and if there are reads without barcodes --- R/prepareDataFromBam.R | 33 ++++++++++++++++++++------------- 1 file changed, 20 insertions(+), 13 deletions(-) diff --git a/R/prepareDataFromBam.R b/R/prepareDataFromBam.R index a978959d..2fa2b027 100755 --- a/R/prepareDataFromBam.R +++ b/R/prepareDataFromBam.R @@ -42,9 +42,9 @@ prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE, if (!isFALSE(demultiplexed)){ if(isTRUE(demultiplexed)){ mcols(readGrgList[[counter]])$CB <- ifelse(!is.na(mcols(alignmentInfo)$BC), mcols(alignmentInfo)$BC, - substr(names(readGrgList[[counter]]), 1, 16)) + gsub("(^[GACT]+(?=_)).*", '\\1', x, perl = TRUE)) mcols(readGrgList[[counter]])$UMI <- ifelse(!is.na(mcols(alignmentInfo)$UG), mcols(alignmentInfo)$UG, - substr(names(readGrgList[[counter]]), 18, 29)) + gsub(".*((?<=_)[GACT]*(?=#)).*", '\\1', x, perl = TRUE)) } else{ mcols(readGrgList[[counter]])$CB = "NA" mcols(readGrgList[[counter]])$UMI = "NA" @@ -82,6 +82,11 @@ prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE, } # remove microexons of width 1bp from list readGrgList <- readGrgList[width(readGrgList) > 1] + numNoBCs = sum(mcols(readGrgList)$CB != "NA") + if(numNoBCs > 0){ + message("Removing ", , " reads that were not assigned barcodes. If this is unexpected check the barcode map input") + readGrgList = readGrgList[mcols(readGrgList)$CB != "NA"] + } if(cleanReads){ #extract duplicated reads from flexiplex to clean #leave other reads alone as supplimental alignments maybe fusion transcripts @@ -95,26 +100,28 @@ prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE, #select alignments closest to barcode start.ptm <- proc.time() - print(length(readGrgList)) df = data.frame(name = names(readGrgList), clip5 = mcols(readGrgList)$clip5Prime) df = df %>% mutate(id = row_number()) %>% group_by(name) %>% summarise(primary.id = id[which.min(clip5)]) readGrgList = unname(readGrgList[df$primary.id]) - print(length(readGrgList)) end.ptm <- proc.time() message("Primary alignment selection Time ", round((end.ptm - start.ptm)[3] / 60, 3), " mins.") #UMI deduplication by barcode start.ptm <- proc.time() - print(length(readGrgList)) - df = data.frame(umi = mcols(readGrgList)$CB, - barcode = mcols(readGrgList)$UMI, - lengths = sum(width(readGrgList))) - df = df %>% mutate(id = row_number()) %>% group_by(barcode, umi) %>% summarise(primary.id = id[which.max(lengths)]) - readGrgList = readGrgList[df$primary.id] - print(length(readGrgList)) - end.ptm <- proc.time() - message("UMI deduplication Time ", round((end.ptm - start.ptm)[3] / 60, 3), " mins.") + numUMIs = length(unique(mcols(readGrgList)$UMI)) + if(numUMIs > 100){ + df = data.frame(umi = mcols(readGrgList)$CB, + barcode = mcols(readGrgList)$UMI, + lengths = sum(width(readGrgList))) + df = df %>% mutate(id = row_number()) %>% group_by(barcode, umi) %>% summarise(primary.id = id[which.max(lengths)]) + readGrgList = readGrgList[df$primary.id] + end.ptm <- proc.time() + message("UMI deduplication Time ", round((end.ptm - start.ptm)[3] / 60, 3), " mins.") + } else { + message("Only ", numUMIs, " detected. Not performing UMI deduplication. If this is unexpected, double check the --chemistry argument") + } + #readGrgList = c(readGrgList.filt, unname(readGrgList.keep)) } From 28f2ca84bcb4326cdef68119fef9a450ab24b95f Mon Sep 17 00:00:00 2001 From: Andre Date: Fri, 19 Apr 2024 14:42:04 +0800 Subject: [PATCH 098/189] Refactor CB to BC --- R/bambu-processReads.R | 12 ++++++------ R/prepareDataFromBam.R | 16 ++++++++-------- 2 files changed, 14 insertions(+), 14 deletions(-) diff --git a/R/bambu-processReads.R b/R/bambu-processReads.R index bf9bebca..2b95ca93 100644 --- a/R/bambu-processReads.R +++ b/R/bambu-processReads.R @@ -68,15 +68,15 @@ bambu.processReads <- function(reads, annotations, genomeSequence, sampleNames = as.numeric(as.factor(sampleNames)) for(i in seq_along(readGrgList)){ if(!isFALSE(demultiplexed)){ - mcols(readGrgList[[i]])$CB = paste0(names(reads)[i], mcols(readGrgList[[i]])$CB) - } else{mcols(readGrgList[[i]])$CB = sampleNames[i]} - mcols(readGrgList[[i]])$CB = as.factor(mcols(readGrgList[[i]])$CB) + mcols(readGrgList[[i]])$BC = paste0(names(reads)[i], mcols(readGrgList[[i]])$BC) + } else{mcols(readGrgList[[i]])$BC = sampleNames[i]} + mcols(readGrgList[[i]])$BC = as.factor(mcols(readGrgList[[i]])$BC) } readGrgList = do.call(c, readGrgList) mcols(readGrgList)$id <- seq_along(readGrgList) if(!isFALSE(demultiplexed)){ - mcols(readGrgList)$sampleID = as.numeric(mcols(readGrgList)$CB) - } else {mcols(readGrgList)$sampleID = mcols(readGrgList)$CB} + mcols(readGrgList)$sampleID = as.numeric(mcols(readGrgList)$BC) + } else {mcols(readGrgList)$sampleID = mcols(readGrgList)$BC} readClassList <- constructReadClasses(readGrgList, genomeSequence = genomeSequence,annotations = annotations, readClass.outputDir = readClass.outputDir, stranded = stranded, min.readCount = min.readCount, @@ -85,7 +85,7 @@ bambu.processReads <- function(reads, annotations, genomeSequence, lowMemory = lowMemory, trackReads = trackReads, fusionMode = fusionMode) metadata(readClassList)$samples = names(reads) - if(!isFALSE(demultiplexed))metadata(readClassList)$samples = levels(mcols(readGrgList)$CB) + if(!isFALSE(demultiplexed))metadata(readClassList)$samples = levels(mcols(readGrgList)$BC) # TODO return output # if (!is.null(readClass.outputDir)) { diff --git a/R/prepareDataFromBam.R b/R/prepareDataFromBam.R index 2fa2b027..c84b0012 100755 --- a/R/prepareDataFromBam.R +++ b/R/prepareDataFromBam.R @@ -41,18 +41,18 @@ prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE, readGrgList[[counter]] <-grglist(alignmentInfo) if (!isFALSE(demultiplexed)){ if(isTRUE(demultiplexed)){ - mcols(readGrgList[[counter]])$CB <- ifelse(!is.na(mcols(alignmentInfo)$BC), mcols(alignmentInfo)$BC, + mcols(readGrgList[[counter]])$BC <- ifelse(!is.na(mcols(alignmentInfo)$BC), mcols(alignmentInfo)$BC, gsub("(^[GACT]+(?=_)).*", '\\1', x, perl = TRUE)) mcols(readGrgList[[counter]])$UMI <- ifelse(!is.na(mcols(alignmentInfo)$UG), mcols(alignmentInfo)$UG, gsub(".*((?<=_)[GACT]*(?=#)).*", '\\1', x, perl = TRUE)) } else{ - mcols(readGrgList[[counter]])$CB = "NA" + mcols(readGrgList[[counter]])$BC = "NA" mcols(readGrgList[[counter]])$UMI = "NA" - mcols(readGrgList[[counter]])$CB = readMap[,2][match(names(readGrgList[[counter]]),readMap[,1])] + mcols(readGrgList[[counter]])$BC = readMap[,2][match(names(readGrgList[[counter]]),readMap[,1])] mcols(readGrgList[[counter]])$UMI = readMap[,3][match(names(readGrgList[[counter]]),readMap[,1])] } - cells <- unique(c(cells, mcols(readGrgList[[counter]])$CB)) - mcols(readGrgList[[counter]])$CB <- factor(mcols(readGrgList[[counter]])$CB, levels = cells) + cells <- unique(c(cells, mcols(readGrgList[[counter]])$BC)) + mcols(readGrgList[[counter]])$BC <- factor(mcols(readGrgList[[counter]])$BC, levels = cells) umi <- unique(c(umi, mcols(readGrgList[[counter]])$UMI)) mcols(readGrgList[[counter]])$UMI <- factor(mcols(readGrgList[[counter]])$UMI, levels = umi) } @@ -82,10 +82,10 @@ prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE, } # remove microexons of width 1bp from list readGrgList <- readGrgList[width(readGrgList) > 1] - numNoBCs = sum(mcols(readGrgList)$CB != "NA") + numNoBCs = sum(mcols(readGrgList)$BC != "NA") if(numNoBCs > 0){ message("Removing ", , " reads that were not assigned barcodes. If this is unexpected check the barcode map input") - readGrgList = readGrgList[mcols(readGrgList)$CB != "NA"] + readGrgList = readGrgList[mcols(readGrgList)$BC != "NA"] } if(cleanReads){ #extract duplicated reads from flexiplex to clean @@ -111,7 +111,7 @@ prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE, start.ptm <- proc.time() numUMIs = length(unique(mcols(readGrgList)$UMI)) if(numUMIs > 100){ - df = data.frame(umi = mcols(readGrgList)$CB, + df = data.frame(umi = mcols(readGrgList)$BC, barcode = mcols(readGrgList)$UMI, lengths = sum(width(readGrgList))) df = df %>% mutate(id = row_number()) %>% group_by(barcode, umi) %>% summarise(primary.id = id[which.max(lengths)]) From 39e3862dfd53bc3ad497fa47525727945c16c17f Mon Sep 17 00:00:00 2001 From: Andre Date: Thu, 25 Apr 2024 14:52:07 +0800 Subject: [PATCH 099/189] Seperate umi dedup from cleanReads --- R/bambu-processReads.R | 8 ++++---- R/bambu.R | 4 ++-- R/prepareDataFromBam.R | 8 +++++--- 3 files changed, 11 insertions(+), 9 deletions(-) diff --git a/R/bambu-processReads.R b/R/bambu-processReads.R index 2b95ca93..65ea4335 100644 --- a/R/bambu-processReads.R +++ b/R/bambu-processReads.R @@ -16,7 +16,7 @@ bambu.processReads <- function(reads, annotations, genomeSequence, readClass.outputDir=NULL, yieldSize=1000000, bpParameters, stranded=FALSE, verbose=FALSE, isoreParameters = setIsoreParameters(NULL), lowMemory=FALSE, trackReads = trackReads, fusionMode = fusionMode, - demultiplexed = FALSE, cleanReads = FALSE, sampleNames = NULL) { + demultiplexed = FALSE, cleanReads = TRUE, dedupUMI = FALSE, sampleNames = NULL) { genomeSequence <- checkInputSequence(genomeSequence) # ===# create BamFileList object from character #===# if (is(reads, "BamFile")) { @@ -62,7 +62,7 @@ bambu.processReads <- function(reads, annotations, genomeSequence, fitReadClassModel = fitReadClassModel, min.exonOverlap = min.exonOverlap, defaultModels = defaultModels, returnModel = returnModel, verbose = verbose, lowMemory = lowMemory, trackReads = trackReads, fusionMode = fusionMode, - demultiplexed = demultiplexed, cleanReads = cleanReads, index = i)}, + demultiplexed = demultiplexed, cleanReads = cleanReads, dedupUMI = dedupUMI, index = i)}, BPPARAM = bpParameters) sampleNames = as.numeric(as.factor(sampleNames)) @@ -114,8 +114,8 @@ bambu.processReadsByFile <- function(bam.file, genomeSequence, annotations, readClass.outputDir = NULL, yieldSize = NULL, stranded = FALSE, min.readCount = 2, fitReadClassModel = TRUE, min.exonOverlap = 10, defaultModels = NULL, returnModel = FALSE, verbose = FALSE, lowMemory = FALSE, trackReads = FALSE, fusionMode = FALSE, demultiplexed = FALSE, - cleanReads = FALSE, index = 0) { - readGrgList <- prepareDataFromBam(bam.file[[1]], verbose = verbose, yieldSize = yieldSize, use.names = trackReads, demultiplexed = demultiplexed, cleanReads = cleanReads) + cleanReads = TRUE, dedupUMI = FALSE, index = 0) { + readGrgList <- prepareDataFromBam(bam.file[[1]], verbose = verbose, yieldSize = yieldSize, use.names = trackReads, demultiplexed = demultiplexed, cleanReads = cleanReads, dedupUMI = dedupUMI) warnings = c() warnings = seqlevelCheckReadsAnnotation(readGrgList, annotations) if(verbose & length(warnings) > 0) warning(paste(warnings,collapse = "\n")) diff --git a/R/bambu.R b/R/bambu.R index 3ebfe832..2a2c51d8 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -140,7 +140,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, assignDist = TRUE, quant = TRUE, stranded = FALSE, ncore = 1, yieldSize = NULL, trackReads = FALSE, returnDistTable = FALSE, lowMemory = FALSE, fusionMode = FALSE, verbose = FALSE, demultiplexed = FALSE, spatial = NULL, quantData = NULL, - sampleNames = NULL, cleanReads = FALSE) { + sampleNames = NULL, cleanReads = TRUE, dedupUMI = FALSE) { if(is.null(annotations)) { annotations = GRangesList() } else annotations <- checkInputs(annotations, reads, readClass.outputDir = rcOutDir, genomeSequence = genome, discovery = discovery) @@ -171,7 +171,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, bpParameters, stranded, verbose, isoreParameters, trackReads = trackReads, fusionMode = fusionMode, lowMemory = lowMemory, demultiplexed = demultiplexed, - sampleNames = sampleNames, cleanReads = cleanReads) + sampleNames = sampleNames, cleanReads = cleanReads, dedupUMI = dedupUMI) } #warnings = handleWarnings(readClassList, verbose) diff --git a/R/prepareDataFromBam.R b/R/prepareDataFromBam.R index c84b0012..a1f55f31 100755 --- a/R/prepareDataFromBam.R +++ b/R/prepareDataFromBam.R @@ -8,7 +8,7 @@ #' @importFrom GenomicRanges width #' @noRd prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE, - use.names = FALSE, demultiplexed = FALSE, cleanReads = FALSE) { + use.names = FALSE, demultiplexed = FALSE, cleanReads = TRUE, dedupUMI = FALSE) { if (is(bamFile, "BamFile")) { if (!is.null(yieldSize)) { yieldSize(bamFile) <- yieldSize @@ -105,8 +105,10 @@ prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE, df = df %>% mutate(id = row_number()) %>% group_by(name) %>% summarise(primary.id = id[which.min(clip5)]) readGrgList = unname(readGrgList[df$primary.id]) end.ptm <- proc.time() - message("Primary alignment selection Time ", round((end.ptm - start.ptm)[3] / 60, 3), " mins.") + message("Primary alignment selection time ", round((end.ptm - start.ptm)[3] / 60, 3), " mins.") + } + if(dedupUMI){ #UMI deduplication by barcode start.ptm <- proc.time() numUMIs = length(unique(mcols(readGrgList)$UMI)) @@ -117,7 +119,7 @@ prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE, df = df %>% mutate(id = row_number()) %>% group_by(barcode, umi) %>% summarise(primary.id = id[which.max(lengths)]) readGrgList = readGrgList[df$primary.id] end.ptm <- proc.time() - message("UMI deduplication Time ", round((end.ptm - start.ptm)[3] / 60, 3), " mins.") + message("UMI deduplication time ", round((end.ptm - start.ptm)[3] / 60, 3), " mins.") } else { message("Only ", numUMIs, " detected. Not performing UMI deduplication. If this is unexpected, double check the --chemistry argument") } From 0295a42f25947732872fdbb5103f9702dbbe0c58 Mon Sep 17 00:00:00 2001 From: Andre Date: Mon, 29 Apr 2024 11:44:03 +0800 Subject: [PATCH 100/189] write rowData to gtf --- R/readWrite.R | 35 +++++++++++++++++++++++++++++++---- 1 file changed, 31 insertions(+), 4 deletions(-) diff --git a/R/readWrite.R b/R/readWrite.R index 318da9f0..dee80fc3 100644 --- a/R/readWrite.R +++ b/R/readWrite.R @@ -112,9 +112,29 @@ writeToGTF <- function(annotation, file, geneIDs = NULL) { } else if (!is(annotation, "CompressedGRangesList")) { stop("The inputted GRangesList is of the wrong class.") } + NDR = NULL + txScore = NULL + txScore.noFit = NULL + novelGene = NULL + novelTranscript = NULL + txClassDescription = NULL df <- as_tibble(annotation) df$exon_rank <- paste('exon_number "', df$exon_rank, '";', sep = "") - if (missing(geneIDs)) { + if(!is.null(mcols(annotation)$NDR)){ + NDR = rep(mcols(annotation)$NDR, unname(elementNROWS(annotation))) + df$NDR <- paste('NDR "', as.character(NDR), '";', sep = "") + txScore = rep(mcols(annotation)$maxTxScore, unname(elementNROWS(annotation))) + df$txScore <- paste('maxTxScore "', as.character(txScore), '";', sep = "") + txScore.noFit = rep(mcols(annotation)$maxTxScore.noFit, unname(elementNROWS(annotation))) + df$txScore.noFit <- paste('maxTxScore.noFit "', as.character(txScore.noFit), '";', sep = "") + novelGene = rep(mcols(annotation)$novelGene, unname(elementNROWS(annotation))) + df$novelGene <- paste('novelGene "', as.character(novelGene), '";', sep = "") + novelTranscript = rep(mcols(annotation)$novelTranscript, unname(elementNROWS(annotation))) + df$novelTranscript <- paste('novelTranscript "', as.character(novelTranscript), '";', sep = "") + txClassDescription = rep(mcols(annotation)$txClassDescription, unname(elementNROWS(annotation))) + df$txClassDescription <- paste('txClassDescription "', as.character(txClassDescription), '";', sep = "") + } + if (is.null(geneIDs)) { if (!is.null(mcols(annotation, use.names = FALSE)$GENEID)) { geneIDs <- as_tibble(mcols(annotation, use.names = FALSE)[, c("TXNAME", "GENEID")]) @@ -127,7 +147,7 @@ writeToGTF <- function(annotation, file, geneIDs = NULL) { df$group_name <- paste('transcript_id "', df$group_name, '";', sep = "") df$GENEID <- paste('gene_id "', df$GENEID, '";', sep = "") dfExon <- mutate(df, source = "Bambu", feature = "exon", score = ".", - frame = ".", attributes = paste(GENEID, group_name, exon_rank)) %>% + frame = ".", attributes = paste(GENEID, group_name, exon_rank, NDR, txScore, txScore.noFit, novelGene, novelTranscript, txClassDescription )) %>% select(seqnames, source, feature, start, end, score, strand, frame, attributes, group_name) dfTx <- as.data.frame(range(ranges(annotation))) @@ -136,9 +156,16 @@ writeToGTF <- function(annotation, file, geneIDs = NULL) { dfTx$group_name <- paste('transcript_id "', dfTx$group_name, '";', sep = "") dfTx$GENEID <- paste('gene_id "', dfTx$GENEID, '";', sep = "") - + if(!is.null(mcols(annotation)$NDR)) { + dfTx$NDR <- paste('NDR "', mcols(annotation)$NDR, '";', sep = "") + dfTx$txScore <- paste('txScore "', mcols(annotation)$txScore, '";', sep = "") + dfTx$txScore.noFit <- paste('txScore.noFit "', mcols(annotation)$txScore.noFit, '";', sep = "") + dfTx$novelGene <- paste('novelGene "', mcols(annotation)$novelGene, '";', sep = "") + dfTx$novelTranscript <- paste('novelTranscript "', mcols(annotation)$novelTranscript, '";', sep = "") + dfTx$txClassDescription <- paste('txClassDescription "', mcols(annotation)$txClassDescription, '";', sep = "") + } dfTx <- mutate(dfTx,source = "Bambu", feature = "transcript", score = ".", - frame = ".", attributes = paste(GENEID, group_name)) %>% + frame = ".", attributes = paste(GENEID, group_name, NDR, txScore, txScore.noFit, novelGene, novelTranscript, txClassDescription )) %>% select(seqnames, source, feature, start, end, score, strand, frame, attributes, group_name) From ddc0ed95384cf933c665d84ecbfb142506b61319 Mon Sep 17 00:00:00 2001 From: Andre Date: Mon, 29 Apr 2024 11:44:30 +0800 Subject: [PATCH 101/189] read in attributes as rowData --- R/prepareAnnotations_utilityFunctions.R | 18 ++++++++++++++++++ 1 file changed, 18 insertions(+) diff --git a/R/prepareAnnotations_utilityFunctions.R b/R/prepareAnnotations_utilityFunctions.R index ffa2f48d..bee77db6 100644 --- a/R/prepareAnnotations_utilityFunctions.R +++ b/R/prepareAnnotations_utilityFunctions.R @@ -27,6 +27,21 @@ prepareAnnotationsFromGTF <- function(file) { data$strand[data$strand == "."] <- "*" data$GENEID <- gsub("gene_id (.*?);.*", "\\1", data$attribute) data$TXNAME <- gsub(".*transcript_id (.*?);.*", "\\1", data$attribute) + data$NDR <- NULL + data$maxTxScore <- NULL + data$maxTxScore.noFit <- NULL + data$novelGene = NULL + data$novelTranscript = NULL + data$txClassDescription = NULL + hasNDR = all(grepl("NDR ", data$attribute)) + if(hasNDR) { + data$NDR <- as.numeric(gsub(".*NDR (.*?);.*", "\\1", data$attribute)) + data$maxTxScore <- as.numeric(gsub(".*maxTxScore (.*?);.*", "\\1", data$attribute)) + data$maxTxScore.noFit <- as.numeric(gsub(".*maxTxScore.noFit (.*?);.*", "\\1", data$attribute)) + data$novelGene <- as.logical(gsub(".*novelGene (.*?);.*", "\\1", data$attribute)) + data$novelTranscript <- as.logical(gsub(".*novelTranscript (.*?);.*", "\\1", data$attribute)) + data$txClassDescription <- gsub(".*txClassDescription (.*?);.*", "\\1", data$attribute) + } multiTxCheck <- as_tibble(data) %>% select(seqname, GENEID) %>% distinct() %>% group_by(GENEID) %>% mutate(n=n(), id=paste0('-',row_number())) if(any(multiTxCheck$n>1)) { # identical TXNAMES @@ -45,6 +60,9 @@ prepareAnnotationsFromGTF <- function(file) { data$GENEID <- uniqueNamesTbl$gene_unique } geneData <- unique(data[, c("TXNAME", "GENEID")]) + geneData <- if(hasNDR) { unique(data[, c("TXNAME", "GENEID", "NDR", "maxTxScore", + "maxTxScore.noFit", "novelGene", "novelTranscript", "txClassDescription")]) + } else {unique(data[, c("TXNAME", "GENEID")])} grlist <- makeGRangesListFromDataFrame( data[, c("seqname", "start", "end", "strand", "TXNAME")], split.field = "TXNAME", keep.extra.columns = TRUE) From 31ca44dc6acf75930e60c4f73d30e4c3b881d066 Mon Sep 17 00:00:00 2001 From: Andre Date: Mon, 29 Apr 2024 11:54:49 +0800 Subject: [PATCH 102/189] Ensure assays stays a sparse matrix even if empty --- R/bambu_utilityFunctions.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/R/bambu_utilityFunctions.R b/R/bambu_utilityFunctions.R index db60b55e..284cc8e8 100644 --- a/R/bambu_utilityFunctions.R +++ b/R/bambu_utilityFunctions.R @@ -236,7 +236,7 @@ combineCountSes <- function(countsSe, annotations){ j = unlist(lapply(seq_along(countsVecList), function(j){rep(j, length(countsVecList[[j]]@i))})), x = unlist(lapply(countsVecList, function(j){j@x})), dims = c(length(countsVecList[[1]]), length(countsVecList))) - if(all(is.na(countsMat))){countsMat = matrix(0,nrow(countsMat),ncol(countsMat))} + if(all(is.na(countsMat))){countsMat = sparseMatrix(i=NULL, j = NULL, dims = c(length(countsVecList[[1]]), length(countsVecList)))} colnames(countsMat) <- sampleNames if (k == "incompatibleCounts"){ rownames(countsMat) = unique(mcols(annotations)$GENEID) From 0336e6bc04de6bcc5043fc2d5d5896d48b05ec92 Mon Sep 17 00:00:00 2001 From: Andre Date: Mon, 29 Apr 2024 14:23:33 +0800 Subject: [PATCH 103/189] Fix flexible barcode lengths --- R/prepareDataFromBam.R | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/R/prepareDataFromBam.R b/R/prepareDataFromBam.R index a1f55f31..419aa165 100755 --- a/R/prepareDataFromBam.R +++ b/R/prepareDataFromBam.R @@ -42,9 +42,9 @@ prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE, if (!isFALSE(demultiplexed)){ if(isTRUE(demultiplexed)){ mcols(readGrgList[[counter]])$BC <- ifelse(!is.na(mcols(alignmentInfo)$BC), mcols(alignmentInfo)$BC, - gsub("(^[GACT]+(?=_)).*", '\\1', x, perl = TRUE)) + gsub("(^[GACT]+(?=_)).*", '\\1', names(readGrgList[[counter]]), perl = TRUE)) mcols(readGrgList[[counter]])$UMI <- ifelse(!is.na(mcols(alignmentInfo)$UG), mcols(alignmentInfo)$UG, - gsub(".*((?<=_)[GACT]*(?=#)).*", '\\1', x, perl = TRUE)) + gsub(".*((?<=_)[GACT]*(?=#)).*", '\\1', names(readGrgList[[counter]]), perl = TRUE)) } else{ mcols(readGrgList[[counter]])$BC = "NA" mcols(readGrgList[[counter]])$UMI = "NA" From 6790ce7e517d464b418e2148bc80375c20c4b95a Mon Sep 17 00:00:00 2001 From: Andre Date: Mon, 29 Apr 2024 16:47:14 +0800 Subject: [PATCH 104/189] fix importing bam --- R/bambu-processReads.R | 2 +- R/prepareDataFromBam.R | 6 +++--- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/R/bambu-processReads.R b/R/bambu-processReads.R index 65ea4335..08da3ed3 100644 --- a/R/bambu-processReads.R +++ b/R/bambu-processReads.R @@ -68,7 +68,7 @@ bambu.processReads <- function(reads, annotations, genomeSequence, sampleNames = as.numeric(as.factor(sampleNames)) for(i in seq_along(readGrgList)){ if(!isFALSE(demultiplexed)){ - mcols(readGrgList[[i]])$BC = paste0(names(reads)[i], mcols(readGrgList[[i]])$BC) + mcols(readGrgList[[i]])$BC = paste0(names(reads)[i], '_', mcols(readGrgList[[i]])$BC) } else{mcols(readGrgList[[i]])$BC = sampleNames[i]} mcols(readGrgList[[i]])$BC = as.factor(mcols(readGrgList[[i]])$BC) } diff --git a/R/prepareDataFromBam.R b/R/prepareDataFromBam.R index 419aa165..4df626ec 100755 --- a/R/prepareDataFromBam.R +++ b/R/prepareDataFromBam.R @@ -82,10 +82,10 @@ prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE, } # remove microexons of width 1bp from list readGrgList <- readGrgList[width(readGrgList) > 1] - numNoBCs = sum(mcols(readGrgList)$BC != "NA") + numNoBCs = sum(mcols(readGrgList)$BC == "NA") if(numNoBCs > 0){ - message("Removing ", , " reads that were not assigned barcodes. If this is unexpected check the barcode map input") - readGrgList = readGrgList[mcols(readGrgList)$BC != "NA"] + message("Removing ", numNoBCs, " reads that were not assigned barcodes. If this is unexpected check the barcode map input") + readGrgList = readGrgList[mcols(readGrgList)$BC == "NA"] } if(cleanReads){ #extract duplicated reads from flexiplex to clean From 8bbb0a182d8db4b77b4fd9923474b94f28f18954 Mon Sep 17 00:00:00 2001 From: Andre Date: Mon, 29 Apr 2024 16:49:28 +0800 Subject: [PATCH 105/189] importBambuOutput function --- R/bambu.R | 9 ++++++++- R/readWrite.R | 45 ++++++++++++++++++++++++++++++++++++++++++--- 2 files changed, 50 insertions(+), 4 deletions(-) diff --git a/R/bambu.R b/R/bambu.R index 2a2c51d8..cb462195 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -229,11 +229,18 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, # annotations) # if (returnDistTable) metadata(seOutput)$distTable = metadata(readClassDist)$distTable + df = DataFrame(sampleName = colnames(countsSe)) + if(demultiplexed){ + df = DataFrame(id = colnames(countsSe), + sampleName = gsub("_[^_]+$","", colnames(countsSe), perl = TRUE), + Barcode = gsub(".*_(?=[^_]*$)","", colnames(countsSe), perl = TRUE)) + } if(!is.null(spatial)){ colData(countsSe) <- DataFrame(read.table(gzfile(spatial), col.names = c("Barcode", "x_coordinate", "y_coordinate")) %>% filter(Barcode %in% colnames(countsSe)), row.names = colnames(countsSe)) } - + colData(countsSe) = df + colnames(countsSe) = df[,1] return(countsSe) } } diff --git a/R/readWrite.R b/R/readWrite.R index dee80fc3..e3b7179a 100644 --- a/R/readWrite.R +++ b/R/readWrite.R @@ -30,7 +30,9 @@ writeBambuOutput <- function(se, path, prefix = "") { "extended_annotations.gtf", sep = "") gtf <- writeToGTF(annotation = transcript_grList, file = transcript_gtffn) - + + utils::write.table(colData(se), file = paste0(outdir, "/sampleData.tsv"), + sep = "\t", quote = FALSE, row.names = FALSE, col.names = TRUE) for(d in names(assays(se))){ writeCountsOutput(se, varname=d, feature='transcript',outdir, prefix) @@ -39,12 +41,12 @@ writeBambuOutput <- function(se, path, prefix = "") { seGene <- transcriptToGeneExpression(se) writeCountsOutput(seGene, varname='counts', feature='gene',outdir, prefix) + utils::write.table(paste0(colnames(se), "-1"), file = paste0(outdir, "barcodes.tsv"), quote = FALSE, row.names = FALSE, col.names = FALSE) txANDGenes <- data.table(as.data.frame(rowData(se))[,c("TXNAME","GENEID")]) utils::write.table(txANDGenes, file = paste0(outdir, "txANDgenes.tsv"), sep = "\t", quote = FALSE, row.names = FALSE, col.names = FALSE) - utils::write.table(paste0(colnames(se), "-1"), file = paste0(outdir, "barcodes.tsv"), quote = FALSE, row.names = FALSE, col.names = FALSE) utils::write.table(names(seGene), file = paste0(outdir, "genes.tsv"), - sep = "\t", quote = FALSE, row.names = FALSE, col.names = FALSE) + sep = "\t", quote = FALSE, row.names = FALSE, col.names = FALSE) R.utils::gzip(paste0(outdir, "txANDgenes.tsv")) R.utils::gzip(paste0(outdir, "barcodes.tsv")) @@ -232,3 +234,40 @@ readFromGTF <- function(file, keep.extra.columns = NULL){ } return(grlist) } + +#' @title Read in Bambu results from writeBambuOutput() into se file +#' @param path the destination of the output files +#' (gtf, transcript counts, and gene counts) +#' @param prefixes the prefix of the output files +#' @details The function will read in the output from Bambu as a sumerized experiment object. +#' This SE object can be used for downstream processes. +#' @export +#' @examples +#' se <- importBambuResults(path = "/path/to/bambu/output/", +#' prefixes = c("rep1", "rep2") +#' )) +#' path <- tempdir() +#' writeBambuOutput(se, path) +importBambuResults <- function(path, prefixes = NA){ + annotations = prepareAnnotations(paste0(path, "/extended_annotations.gtf")) + counts = readMM(paste0(path, "/counts_transcript.mtx")) + CPM = readMM(paste0(path, "/CPM_transcript.mtx")) + fullLengthCounts = readMM(paste0(path, "/fullLengthCounts_transcript.mtx")) + uniqueCounts = readMM(paste0(path, "/uniqueCounts_transcript.mtx")) + incompatibleCounts = readMM(paste0(path, "/incompatibleCounts.mtx")) + barcodes = read.table(paste0(path, "/barcodes.tsv")) + geneIds = read.table(paste0(path, "/genes.tsv")) + txIds = read.table(paste0(path, "/txANDgenes.tsv")) + colData = read.table(paste0(path, "/sampleData.tsv"), header = TRUE) + rownames(incompatibleCounts) = geneIds[,1] + + countsSe <- SummarizedExperiment(assays = SimpleList(counts = counts, + CPM = CPM, + fullLengthCounts = fullLengthCounts, + uniqueCounts = uniqueCounts)) + metadata(countsSe)$incompatibleCounts <- incompatibleCounts + rowRanges(countsSe) <- annotations + colData(countsSe) = DataFrame(colData) + colnames(countsSe) = colData[,1] + return(countsSe) +} \ No newline at end of file From e90575570fa36e3348bda96e8deeed62b22e6d51 Mon Sep 17 00:00:00 2001 From: Andre Date: Tue, 30 Apr 2024 11:23:31 +0800 Subject: [PATCH 106/189] writeBambuOutput rights incompatibleCounts and can seperate samples --- R/readWrite.R | 46 +++++++++++++++++++++++++++++++++++----------- 1 file changed, 35 insertions(+), 11 deletions(-) diff --git a/R/readWrite.R b/R/readWrite.R index e3b7179a..7cc5b783 100644 --- a/R/readWrite.R +++ b/R/readWrite.R @@ -16,7 +16,7 @@ #' )) #' path <- tempdir() #' writeBambuOutput(se, path) -writeBambuOutput <- function(se, path, prefix = "") { +writeBambuOutput <- function(se, path, prefix = "", seperateSamples = FALSE) { if (missing(se) | missing(path)) { stop("Both summarizedExperiment object from bambu and the path for the output files are required.") @@ -35,23 +35,47 @@ writeBambuOutput <- function(se, path, prefix = "") { sep = "\t", quote = FALSE, row.names = FALSE, col.names = TRUE) for(d in names(assays(se))){ writeCountsOutput(se, varname=d, - feature='transcript',outdir, prefix) - print(d) + feature='transcript',outdir, prefix) + print(d) } + #write incompatible counts + estimates = metadata(se)$incompatibleCounts + estimatesfn <- paste(outdir, prefix, "incompatibleCounts.mtx", sep = "") + Matrix::writeMM(estimates, estimatesfn) seGene <- transcriptToGeneExpression(se) writeCountsOutput(seGene, varname='counts', feature='gene',outdir, prefix) - - utils::write.table(paste0(colnames(se), "-1"), file = paste0(outdir, "barcodes.tsv"), quote = FALSE, row.names = FALSE, col.names = FALSE) + #utils::write.table(paste0(colnames(se), "-1"), file = paste0(outdir, "barcodes.tsv"), quote = FALSE, row.names = FALSE, col.names = FALSE) + #R.utils::gzip(paste0(outdir, "barcodes.tsv")) txANDGenes <- data.table(as.data.frame(rowData(se))[,c("TXNAME","GENEID")]) utils::write.table(txANDGenes, file = paste0(outdir, "txANDgenes.tsv"), sep = "\t", quote = FALSE, row.names = FALSE, col.names = FALSE) utils::write.table(names(seGene), file = paste0(outdir, "genes.tsv"), sep = "\t", quote = FALSE, row.names = FALSE, col.names = FALSE) - R.utils::gzip(paste0(outdir, "txANDgenes.tsv")) - R.utils::gzip(paste0(outdir, "barcodes.tsv")) - R.utils::gzip(paste0(outdir, "genes.tsv")) - + #R.utils::gzip(paste0(outdir, "txANDgenes.tsv")) + #R.utils::gzip(paste0(outdir, "genes.tsv")) + + #If there are multiple samples (when demultiplexed), seperate each sample into its own directory + if(seperateSamples){ + fullSe = se + for(sampleName in unique(colData(fullSe)$sampleName)){ + dir.create(file.path(outdir, sampleName), showWarnings = FALSE) + se = fullSe[,colData(fullSe)$sampleName == sampleName] + metadata(se)$incompatibleCounts = metadata(se)$incompatibleCounts[,colData(fullSe)$sampleName == sampleName] + for(d in names(assays(se))){ + writeCountsOutput(se, varname=d, + feature='transcript',outdir=paste0(outdir, sampleName,"/"), prefix) + } + estimates = metadata(se)$incompatibleCounts + estimatesfn <- paste(outdir, "/", sampleName,"/", prefix, "incompatibleCounts.mtx", sep = "") + Matrix::writeMM(estimates, estimatesfn) + seGene <- transcriptToGeneExpression(se) + writeCountsOutput(seGene, varname='counts', feature='gene',paste0(outdir, sampleName,"/"), prefix) + utils::write.table(colData(se), file = paste0(outdir, "/", sampleName, "/sampleData.tsv"), + sep = "\t", quote = FALSE, row.names = FALSE, col.names = TRUE) + #utils::write.table(paste0(colnames(se), "-1"), file = paste0(outdir, "barcodes.tsv"), quote = FALSE, row.names = FALSE, col.names = FALSE) + } + } } } @@ -80,12 +104,12 @@ writeCountsOutput <- function(se, varname = "counts", if (feature == "transcript"){ estimatesfn <- paste(outdir, prefix, varname,"_",feature,".mtx", sep = "") Matrix::writeMM(estimates, estimatesfn) - R.utils::gzip(estimatesfn) + #R.utils::gzip(estimatesfn) } else{ estimatesfn <- paste(outdir, prefix, varname,"_",feature,".mtx", sep = "") Matrix::writeMM(estimates, estimatesfn) - R.utils::gzip(estimatesfn) + #R.utils::gzip(estimatesfn) } } } From c568679713ce880409a4256c5c742f43dbcc82f9 Mon Sep 17 00:00:00 2001 From: Andre Date: Thu, 2 May 2024 09:30:34 +0800 Subject: [PATCH 107/189] clean up warnings --- R/bambu-processReads.R | 11 ++++++----- R/bambu-quantify.R | 2 +- R/bambu.R | 32 +++++++++++++++++++++++++------- R/bambu_utilityFunctions.R | 20 +++++++++++++++++++- 4 files changed, 51 insertions(+), 14 deletions(-) diff --git a/R/bambu-processReads.R b/R/bambu-processReads.R index 08da3ed3..1da9ec9c 100644 --- a/R/bambu-processReads.R +++ b/R/bambu-processReads.R @@ -116,9 +116,10 @@ bambu.processReadsByFile <- function(bam.file, genomeSequence, annotations, verbose = FALSE, lowMemory = FALSE, trackReads = FALSE, fusionMode = FALSE, demultiplexed = FALSE, cleanReads = TRUE, dedupUMI = FALSE, index = 0) { readGrgList <- prepareDataFromBam(bam.file[[1]], verbose = verbose, yieldSize = yieldSize, use.names = trackReads, demultiplexed = demultiplexed, cleanReads = cleanReads, dedupUMI = dedupUMI) + print(paste0("Number of alignments/reads: ",length(readGrgList))) warnings = c() warnings = seqlevelCheckReadsAnnotation(readGrgList, annotations) - if(verbose & length(warnings) > 0) warning(paste(warnings,collapse = "\n")) + if(verbose & length(warnings) > 0) {warning(paste(warnings,collapse = "\n"))} #check seqlevels for consistency, drop ranges not present in genomeSequence refSeqLevels <- seqlevels(genomeSequence) if (!all(seqlevels(readGrgList) %in% refSeqLevels)) { @@ -129,14 +130,14 @@ bambu.processReadsByFile <- function(bam.file, genomeSequence, annotations, "reference genome sequence, annotations without reference genomic sequence ", "are dropped") warnings = c(warnings, warningText) - if(verbose) warning(warningText) + if(verbose){warning(warningText)} annotations <- keepSeqlevels(annotations, value = refSeqLevels, pruning.mode = "coarse") } warningText = paste0("not all chromosomes from reads present in reference ", "genome sequence, reads without reference chromosome sequence are dropped") warnings = c(warnings, warningText) - if(verbose) warning(warningText) + if(verbose){warning(warningText)} readGrgList <- keepSeqlevels(readGrgList, value = refSeqLevels, pruning.mode = "coarse") # reassign Ids after seqlevels are dropped @@ -151,14 +152,14 @@ bambu.processReadsByFile <- function(bam.file, genomeSequence, annotations, "genomic regions. These reads will be dropped. Check you are using the ", "same genome used for the alignment") warnings = c(warnings, warningText) - if(verbose) warning(warningText) + if(verbose){warning(warningText)} } ### add ### # reassign Ids after seqlevels are dropped mcols(readGrgList)$id <- seq_along(readGrgList) ### add ### - + print(paste0("Number of post-filter alignments/reads: ",length(readGrgList))) if(length(readGrgList) == 0) { stop("No reads left after filtering.") } diff --git a/R/bambu-quantify.R b/R/bambu-quantify.R index 8dbbfacb..4b125b8b 100644 --- a/R/bambu-quantify.R +++ b/R/bambu-quantify.R @@ -20,7 +20,7 @@ bambu.quantify <- function(readClassDt, countMatrix, incompatibleCountMatrix, tx fullLengthCounts = as(round(counts$fullLengthCounts,sig.digit), "sparseVector"), uniqueCounts = as(round(counts$uniqueCounts,sig.digit), "sparseVector")) end.ptm <- proc.time() - message("bambu.quantify ", round((end.ptm - start.ptm)[3] / 60, 3), " mins.") + if (verbose) message("bambu.quantify ", round((end.ptm - start.ptm)[3] / 60, 3), " mins.") return(seOutput) } diff --git a/R/bambu.R b/R/bambu.R index cb462195..4571459b 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -143,7 +143,8 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, sampleNames = NULL, cleanReads = TRUE, dedupUMI = FALSE) { if(is.null(annotations)) { annotations = GRangesList() } else annotations <- checkInputs(annotations, reads, - readClass.outputDir = rcOutDir, genomeSequence = genome, discovery = discovery) + readClass.outputDir = rcOutDir, genomeSequence = genome, discovery = discovery, + sampleNames = sampleNames, spatial = spatial) isoreParameters <- setIsoreParameters(isoreParameters = opt.discovery) #below line is to be compatible with earlier version of running bambu if(!is.null(isoreParameters$max.txNDR)) NDR = isoreParameters$max.txNDR @@ -167,9 +168,9 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, message("--- Start generating read class files ---") readClassList <- bambu.processReads(reads, annotations, genomeSequence = genome, - readClass.outputDir = rcOutDir, yieldSize, - bpParameters, stranded, verbose, - isoreParameters, trackReads = trackReads, fusionMode = fusionMode, + readClass.outputDir = rcOutDir, yieldSize = yieldSize, + bpParameters = bpParameters, stranded = stranded, verbose = verbose, + isoreParameters = isoreParameters, trackReads = trackReads, fusionMode = fusionMode, lowMemory = lowMemory, demultiplexed = demultiplexed, sampleNames = sampleNames, cleanReads = cleanReads, dedupUMI = dedupUMI) } @@ -235,9 +236,26 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, sampleName = gsub("_[^_]+$","", colnames(countsSe), perl = TRUE), Barcode = gsub(".*_(?=[^_]*$)","", colnames(countsSe), perl = TRUE)) } - if(!is.null(spatial)){ - colData(countsSe) <- DataFrame(read.table(gzfile(spatial), col.names = c("Barcode", "x_coordinate", "y_coordinate")) %>% - filter(Barcode %in% colnames(countsSe)), row.names = colnames(countsSe)) + if(!is.null(spatial)){ + df$x_coordinate = NA + df$y_coordinate = NA + #load in all whitelist info, is one file or a vector of paths? + if(length(spatial)==1){ + bc_coords = DataFrame(read.table(gzfile(spatial), col.names = c("Barcode", "x_coordinate", "y_coordinate"))) + bcMatch = match(df$Barcode, bc_coords$Barcode) + df$x_coordinate = bc_coords$x_coordinate[bcMatch] + df$y_coordinate = bc_coords$y_coordinate[bcMatch] + } else{ + spatial.unique = unique(spatial) + for(whitelist in spatial.unique){ + i = which(spatial.unique==whitelist) + bc_coords = DataFrame(read.table(gzfile(whitelist), col.names = c("Barcode", "x_coordinate", "y_coordinate"))) + bcSampleIndex = df$sampleName %in% sampleNames[i] + bcMatch = match(df$Barcode[bcSampleIndex], bc_coords$Barcode) + df$x_coordinate[bcSampleIndex] = bc_coords$x_coordinate[bcMatch] + df$y_coordinate[bcSampleIndex] = bc_coords$y_coordinate[bcMatch] + } + } } colData(countsSe) = df colnames(countsSe) = df[,1] diff --git a/R/bambu_utilityFunctions.R b/R/bambu_utilityFunctions.R index 284cc8e8..b7910293 100644 --- a/R/bambu_utilityFunctions.R +++ b/R/bambu_utilityFunctions.R @@ -74,7 +74,7 @@ updateParameters <- function(Parameters, Parameters.default) { #' @param readClass.outputDir path to readClass output directory #' @importFrom methods is #' @noRd -checkInputs <- function(annotations, reads, readClass.outputDir, genomeSequence, discovery){ +checkInputs <- function(annotations, reads, readClass.outputDir, genomeSequence, discovery, sampleNames, spatial){ # ===# Check annotation inputs #===# if (!is.null(annotations)) { if (is(annotations, "CompressedGRangesList")) { @@ -138,6 +138,24 @@ checkInputs <- function(annotations, reads, readClass.outputDir, genomeSequence, fuzzy, recommend to provide the path as a string variable to avoid use of Rsamtools for opening.") } + + #check single-cell and spatial inputs match + if(!is.null(sampleNames)){ + if(length(reads)!=length(sampleNames)){ + stop("There are not the same number of sampleNames as input files to reads. ", + "Make sure these two arguments are vectors of the same length") + } + } + + if(!is.null(spatial)){ + #if(!all(grepl(".tsv^", spatial))){stop("Not all paths for spatial are .tsv files")} + if(length(spatial)==1 & length(reads)>1){ + warning("Using the same whitelist and coordinates for all input samples") + } else if(length(reads)!=length(spatial)){ + stop("There are not the same number spatial whitelist paths as input files to reads. ", + "Make sure these two arguments are vectors of the same length") + } + } return(annotations) } From 0b47cb8a11e827e4ba9d02bcb2bcae2eef6e9cf3 Mon Sep 17 00:00:00 2001 From: Andre Date: Wed, 26 Jun 2024 13:55:10 +0800 Subject: [PATCH 108/189] Report all possible transripts if NDR = 1 --- R/bambu-extendAnnotations-utilityExtend.R | 10 +++++++--- 1 file changed, 7 insertions(+), 3 deletions(-) diff --git a/R/bambu-extendAnnotations-utilityExtend.R b/R/bambu-extendAnnotations-utilityExtend.R index b675f2c4..e11237d6 100644 --- a/R/bambu-extendAnnotations-utilityExtend.R +++ b/R/bambu-extendAnnotations-utilityExtend.R @@ -64,7 +64,8 @@ filterTranscripts <- function(combinedTranscripts, min.sampleNumber){ combinedTranscripts$NSampleTxScore >= min.sampleNumber) & ( combinedTranscripts$NSampleReadProp >= min.sampleNumber) } - combinedTranscripts = combinedTranscripts[filterSet,] + #combinedTranscripts = combinedTranscripts[filterSet,] + combinedTranscripts$maxTxScore[!filterSet] = 0 return(combinedTranscripts) } @@ -83,8 +84,10 @@ filterTranscriptsByAnnotation <- function(rowDataCombined, annotationGrangesList if (remove.subsetTx) { # (1) based on compatibility with annotations notCompatibleIds <- which(!grepl("compatible", rowDataCombined$readClassType) | rowDataCombined$readClassType == "equal:compatible") #keep equal for FDR calculation - exonRangesCombined <- exonRangesCombined[notCompatibleIds] - rowDataCombined <- rowDataCombined[notCompatibleIds,] + #exonRangesCombined <- exonRangesCombined[notCompatibleIds] + #rowDataCombined <- rowDataCombined[notCompatibleIds,] + rowDataCombined$maxTxScore[grepl("compatible", rowDataCombined$readClassType) & + rowDataCombined$readClassType != "equal:compatible"]=0 } #(2) remove transcripts below NDR threshold/identical junctions to annotations rowDataCombined = calculateNDROnTranscripts(rowDataCombined, @@ -178,6 +181,7 @@ calculateNDROnTranscripts <- function(combinedTranscripts, useTxScore = FALSE){ "for NDR precision stabilization.") message("NDR will be approximated as: (1 - Transcript Model Prediction Score)") } else combinedTranscripts$NDR = calculateNDR(combinedTranscripts$maxTxScore, equal) + combinedTranscripts$NDR[combinedTranscripts$maxTxScore==0] = 1 return(combinedTranscripts) } From fbe8ee3ddfe875be134baebe8c099c04cb71e975 Mon Sep 17 00:00:00 2001 From: Andre Date: Mon, 22 Jul 2024 11:29:24 +0800 Subject: [PATCH 109/189] fix bug when reading in barcode map from file --- R/prepareDataFromBam.R | 12 ++++++++---- 1 file changed, 8 insertions(+), 4 deletions(-) diff --git a/R/prepareDataFromBam.R b/R/prepareDataFromBam.R index 4df626ec..864f022c 100755 --- a/R/prepareDataFromBam.R +++ b/R/prepareDataFromBam.R @@ -46,10 +46,12 @@ prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE, mcols(readGrgList[[counter]])$UMI <- ifelse(!is.na(mcols(alignmentInfo)$UG), mcols(alignmentInfo)$UG, gsub(".*((?<=_)[GACT]*(?=#)).*", '\\1', names(readGrgList[[counter]]), perl = TRUE)) } else{ - mcols(readGrgList[[counter]])$BC = "NA" + mcols(readGrgList[[counter]])$BC = NA mcols(readGrgList[[counter]])$UMI = "NA" mcols(readGrgList[[counter]])$BC = readMap[,2][match(names(readGrgList[[counter]]),readMap[,1])] - mcols(readGrgList[[counter]])$UMI = readMap[,3][match(names(readGrgList[[counter]]),readMap[,1])] + if(ncol(readMap)>2){ + mcols(readGrgList[[counter]])$UMI = readMap[,3][match(names(readGrgList[[counter]]),readMap[,1])] + } } cells <- unique(c(cells, mcols(readGrgList[[counter]])$BC)) mcols(readGrgList[[counter]])$BC <- factor(mcols(readGrgList[[counter]])$BC, levels = cells) @@ -82,10 +84,12 @@ prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE, } # remove microexons of width 1bp from list readGrgList <- readGrgList[width(readGrgList) > 1] - numNoBCs = sum(mcols(readGrgList)$BC == "NA") + print(head(mcols(readGrgList))) + numNoBCs = sum(is.na(mcols(readGrgList)$BC)) + print(numNoBCs) if(numNoBCs > 0){ message("Removing ", numNoBCs, " reads that were not assigned barcodes. If this is unexpected check the barcode map input") - readGrgList = readGrgList[mcols(readGrgList)$BC == "NA"] + readGrgList = readGrgList[!is.na(mcols(readGrgList)$BC)] } if(cleanReads){ #extract duplicated reads from flexiplex to clean From 73b0b8d8c2f168b76aa90772aea5ab87ee8ed1e1 Mon Sep 17 00:00:00 2001 From: Andre Date: Thu, 1 Aug 2024 14:58:05 +0800 Subject: [PATCH 110/189] catch error when no drate is calculated due to low reads --- R/bambu-quantify_utilityFunctions.R | 1 + 1 file changed, 1 insertion(+) diff --git a/R/bambu-quantify_utilityFunctions.R b/R/bambu-quantify_utilityFunctions.R index dbcaae63..0751e4ae 100644 --- a/R/bambu-quantify_utilityFunctions.R +++ b/R/bambu-quantify_utilityFunctions.R @@ -281,6 +281,7 @@ modifyAvaluewithDegradation_rate <- function(tmp, d_rate, d_mode){ tmp[which(multi_align) , aval := ifelse(equal, 1 - sum(.SD[which(!equal)]$rcWidth*d_rate/1000), rcWidth*d_rate/1000), by = list(gene_sid,txid)] + if(is.na(d_rate)) d_rate = 0 if (d_rate == 0) { tmp[, par_status := all(!equal & multi_align), by = list(eqClassId, gene_sid)] From 9c2801be6524647c5d70b497d81fc55056ddbb16 Mon Sep 17 00:00:00 2001 From: Andre Date: Tue, 13 Aug 2024 12:03:03 +0800 Subject: [PATCH 111/189] return non em counts before quant step fix use of placeholder variable name --- R/bambu-quantify_utilityFunctions.R | 29 +++++++++++++++++++++++++++++ R/bambu.R | 7 +++++++ 2 files changed, 36 insertions(+) diff --git a/R/bambu-quantify_utilityFunctions.R b/R/bambu-quantify_utilityFunctions.R index 0751e4ae..872eb865 100644 --- a/R/bambu-quantify_utilityFunctions.R +++ b/R/bambu-quantify_utilityFunctions.R @@ -522,3 +522,32 @@ NULL library.dynam.unload("bambu", libpath) } +geneCountsFromQuantData <- function(quantData, annotations){ + x = quantData$readClassDt %>% group_by(eqClassId) %>% + summarise(nobs= nobs[1], + gene_sid = gene_sid[1], + eqClass.match = eqClass.match[1], + txid = txid[1]) %>% + filter(!is.na(eqClass.match)) + + #combine counts by gene + nobs = quantData$countMatrix[x$eqClass.match,] + nobs.gene = sparse.model.matrix(~ factor(x$gene_sid) - 1) + nobs = t(nobs.gene) %*% nobs + + #convert the relative gene index to the consistant gene id + rownames(nobs) = gsub("factor\\(x\\$gene_sid\\)", "", rownames(nobs)) + rownames(nobs) = x$txid[match(rownames(nobs), x$gene_sid)] + rownames(nobs) = mcols(annotations)$GENEID[as.numeric(rownames(nobs))] + genes = levels(factor(unique(mcols(annotations)$GENEID))) + rownames(quantData$incompatibleCountMatrix) = genes[as.numeric(rownames(quantData$incompatibleCountMatrix))] + + #combine the read class gene counts with incompatible counts + geneids = union(rownames(nobs), rownames(quantData$incompatibleCountMatrix)) + geneMat = sparseMatrix(length(geneids), ncol(nobs), x = 0) + rownames(geneMat) = geneids + geneMat[rownames(nobs),] = nobs + geneMat[rownames(quantData$incompatibleCountMatrix),] = geneMat[rownames(quantData$incompatibleCountMatrix),] + quantData2$incompatibleCountMatrix + + return(geneMat) +} \ No newline at end of file diff --git a/R/bambu.R b/R/bambu.R index 4571459b..0a343288 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -201,6 +201,13 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, quantData$readClassDt = quantData$readClassDt %>% group_by(eqClassId, gene_sid) %>% mutate(multi_align = length(unique(txid))>1) %>% ungroup() %>% mutate(aval = 1) %>% data.table() + + #return non-em counts + quantData$geneCounts = geneCountsFromQuantData(quantData, annotations) + x = quantData$readClassDt %>% filter(!multi_align & !is.na(eqClass.match)) + quantData$uniqueCounts = quantData$countMatrix[x$eqClass.match,] + rownames(quantData$uniqueCounts) = names(annotations)[x$txid] + if (!quant) return(quantData) } From 1176eca0cdf1a78b8e298c6d7f8ba2fd799da999 Mon Sep 17 00:00:00 2001 From: Andre Date: Wed, 21 Aug 2024 15:36:42 +0800 Subject: [PATCH 112/189] Fix the normal discovery impact cluster discovery --- R/bambu.R | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/R/bambu.R b/R/bambu.R index 5e2db7fc..39e17886 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -178,9 +178,9 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, if (!discovery & !assignDist & !quant) return(readClassList) if (discovery) { message("--- Start extending annotations ---") - annotations <- bambu.extendAnnotations(readClassList, annotations, NDR, + extendedAnnotations <- bambu.extendAnnotations(readClassList, annotations, NDR, isoreParameters, stranded, bpParameters, fusionMode, verbose) - metadata(annotations)$warnings = warnings + metadata(extendedAnnotations)$warnings = warnings #### split rcf into clusters if(!is.null(clustering)){ @@ -226,14 +226,14 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, annotations.clusters[[names(clustering)[i]]] <- bambu.extendAnnotations(list(rcf.filt), annotations, NDR, isoreParameters, stranded, bpParameters, fusionMode, verbose) } - print("test") if(length(rcfs.clusters)>0){ print("--- Merging all individual clusters ---") annotations.clusters[["merged"]] <- bambu.extendAnnotations(rcfs.clusters, annotations, NDR, isoreParameters, stranded, bpParameters, fusionMode, verbose) } - metadata(annotations)$clusters = annotations.clusters + metadata(extendedAnnotations)$clusters = annotations.clusters } + annotations = extendedAnnotations if (!quant & !assignDist) return(annotations) } From 1f471a307068478a83c2f0798bf31d03f46bdd68 Mon Sep 17 00:00:00 2001 From: Andre Date: Fri, 23 Aug 2024 14:58:16 +0800 Subject: [PATCH 113/189] Enable clusters to be assigned before EM tidy up typo fix --- R/bambu-quantify_utilityFunctions.R | 2 +- R/bambu.R | 42 ++++++++++++++++++++++------- 2 files changed, 34 insertions(+), 10 deletions(-) diff --git a/R/bambu-quantify_utilityFunctions.R b/R/bambu-quantify_utilityFunctions.R index 872eb865..2b54aee5 100644 --- a/R/bambu-quantify_utilityFunctions.R +++ b/R/bambu-quantify_utilityFunctions.R @@ -547,7 +547,7 @@ geneCountsFromQuantData <- function(quantData, annotations){ geneMat = sparseMatrix(length(geneids), ncol(nobs), x = 0) rownames(geneMat) = geneids geneMat[rownames(nobs),] = nobs - geneMat[rownames(quantData$incompatibleCountMatrix),] = geneMat[rownames(quantData$incompatibleCountMatrix),] + quantData2$incompatibleCountMatrix + geneMat[rownames(quantData$incompatibleCountMatrix),] = geneMat[rownames(quantData$incompatibleCountMatrix),] + quantData$incompatibleCountMatrix return(geneMat) } \ No newline at end of file diff --git a/R/bambu.R b/R/bambu.R index 0a343288..fee6f82e 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -140,7 +140,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, assignDist = TRUE, quant = TRUE, stranded = FALSE, ncore = 1, yieldSize = NULL, trackReads = FALSE, returnDistTable = FALSE, lowMemory = FALSE, fusionMode = FALSE, verbose = FALSE, demultiplexed = FALSE, spatial = NULL, quantData = NULL, - sampleNames = NULL, cleanReads = TRUE, dedupUMI = FALSE) { + sampleNames = NULL, cleanReads = TRUE, dedupUMI = FALSE, clusters = NULL) { if(is.null(annotations)) { annotations = GRangesList() } else annotations <- checkInputs(annotations, reads, readClass.outputDir = rcOutDir, genomeSequence = genome, discovery = discovery, @@ -206,7 +206,9 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, quantData$geneCounts = geneCountsFromQuantData(quantData, annotations) x = quantData$readClassDt %>% filter(!multi_align & !is.na(eqClass.match)) quantData$uniqueCounts = quantData$countMatrix[x$eqClass.match,] - rownames(quantData$uniqueCounts) = names(annotations)[x$txid] + uniqueCounts.tx = sparse.model.matrix(~ factor(x$txid) - 1) + quantData$uniqueCounts = t(uniqueCounts.tx) %*% quantData$uniqueCounts + rownames(quantData$uniqueCounts) = names(annotations)[match(as.numeric(levels(factor(x$txid))),mcols(annotations)$txid)] if (!quant) return(quantData) } @@ -218,17 +220,39 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, if(is.null(quantData)) stop("quantData must be provided or assignDist = TRUE") GENEIDs.i = as.numeric(factor(unique(mcols(annotations)$GENEID))) start.ptm <- proc.time() - countsSeCompressed <- bplapply(seq_len(ncol(quantData$countMatrix)), FUN = function(i){ - #print(i) - return(bambu.quantify(readClassDt = quantData$readClassDt, countMatrix = unname(quantData$countMatrix[,i]), - incompatibleCountMatrix = data.table(GENEID.i = as.numeric(rownames(quantData$incompatibleCountMatrix)), counts = quantData$incompatibleCountMatrix[,i]), + + #load in the barcode clustering from file if provided + iter = seq_len(ncol(quantData$countMatrix)) + if(!is.null(clusters)){ + if(!is.list(clusters)){ + clusterMap = read.table(clusters, + sep = ifelse(grepl(".tsv$",clusters), "\t", ","), header = FALSE) + clusters = splitAsList(clusterMap[,1], clusterMap[,2]) + rm(clusterMap) + } + iter = clusters + } + + countsSeCompressed <- bplapply(iter, FUN = function(i){ + countMatrix = unname(quantData$countMatrix[,i]) + if(!is.null(dim(countMatrix))){ + countMatrix = rowSums(countMatrix) + incompatibleCountMatrix = rowSums(quantData$incompatibleCountMatrix[,i]) + } + return(bambu.quantify(readClassDt = quantData$readClassDt, countMatrix = countMatrix, + incompatibleCountMatrix = data.table(GENEID.i = as.numeric(rownames(quantData$incompatibleCountMatrix)), counts = incompatibleCountMatrix), txid.index = mcols(annotations)$txid, GENEIDs = GENEIDs.i, isoreParameters = isoreParameters, emParameters = emParameters, trackReads = trackReads, returnDistTable = returnDistTable, verbose = verbose))}, BPPARAM = bpParameters) end.ptm <- proc.time() message("Total Time ", round((end.ptm - start.ptm)[3] / 60, 3), " mins.") - countsSeCompressed$colnames = colnames(quantData$countMatrix) + if(!is.null(clusters)){ + countsSeCompressed$colnames = names(clusters) + } else{ + countsSeCompressed$colnames = colnames(quantData$countMatrix) + } + countsSe <- combineCountSes(countsSeCompressed, annotations) #metadata(countsSe)$warnings = warnings @@ -238,12 +262,12 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, # if (returnDistTable) metadata(seOutput)$distTable = metadata(readClassDist)$distTable df = DataFrame(sampleName = colnames(countsSe)) - if(demultiplexed){ + if(demultiplexed & is.null(clusters)){ df = DataFrame(id = colnames(countsSe), sampleName = gsub("_[^_]+$","", colnames(countsSe), perl = TRUE), Barcode = gsub(".*_(?=[^_]*$)","", colnames(countsSe), perl = TRUE)) } - if(!is.null(spatial)){ + if(!is.null(spatial & is.null(clusters))){ df$x_coordinate = NA df$y_coordinate = NA #load in all whitelist info, is one file or a vector of paths? From 1f3994ad9a83ecb26b96fc8cebc35919acbc3009 Mon Sep 17 00:00:00 2001 From: Andre Date: Tue, 27 Aug 2024 10:17:49 +0800 Subject: [PATCH 114/189] Fix bug in denono --- R/bambu-extendAnnotations-utilityExtend.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/R/bambu-extendAnnotations-utilityExtend.R b/R/bambu-extendAnnotations-utilityExtend.R index e11237d6..df9ce393 100644 --- a/R/bambu-extendAnnotations-utilityExtend.R +++ b/R/bambu-extendAnnotations-utilityExtend.R @@ -111,7 +111,7 @@ filterTranscriptsByAnnotation <- function(rowDataCombined, annotationGrangesList exonRangesCombined <- exonRangesCombined[filterSet] rowDataCombined <- rowDataCombined[filterSet,] } - if(sum(filterSet==0) & length(annotationGrangesList)==0) stop( + if(sum(filterSet)==0 & length(annotationGrangesList)==0) stop( "WARNING - No annotations were provided. Please increase NDR threshold to use novel transcripts") if(sum(filterSet)==0) message("WARNING - No novel transcripts meet the given thresholds. Try a higher NDR.") # (3) combine novel transcripts with annotations From d795869da7ebbf68bad6ebf5fd297adf7ee914dd Mon Sep 17 00:00:00 2001 From: Andre Date: Tue, 27 Aug 2024 14:33:50 +0800 Subject: [PATCH 115/189] AssignDist step will now output uniqueCounts transcriptToGene will work on this se object --- R/bambu-quantify_utilityFunctions.R | 69 +++++++++++++-------- R/bambu.R | 96 ++++++++++++++--------------- R/bambu_utilityFunctions.R | 32 ++++++++++ R/transcriptToGeneExpression.R | 3 + 4 files changed, 123 insertions(+), 77 deletions(-) diff --git a/R/bambu-quantify_utilityFunctions.R b/R/bambu-quantify_utilityFunctions.R index 2b54aee5..d324ef5d 100644 --- a/R/bambu-quantify_utilityFunctions.R +++ b/R/bambu-quantify_utilityFunctions.R @@ -522,32 +522,49 @@ NULL library.dynam.unload("bambu", libpath) } -geneCountsFromQuantData <- function(quantData, annotations){ - x = quantData$readClassDt %>% group_by(eqClassId) %>% - summarise(nobs= nobs[1], - gene_sid = gene_sid[1], - eqClass.match = eqClass.match[1], - txid = txid[1]) %>% - filter(!is.na(eqClass.match)) - - #combine counts by gene - nobs = quantData$countMatrix[x$eqClass.match,] - nobs.gene = sparse.model.matrix(~ factor(x$gene_sid) - 1) - nobs = t(nobs.gene) %*% nobs - - #convert the relative gene index to the consistant gene id - rownames(nobs) = gsub("factor\\(x\\$gene_sid\\)", "", rownames(nobs)) - rownames(nobs) = x$txid[match(rownames(nobs), x$gene_sid)] - rownames(nobs) = mcols(annotations)$GENEID[as.numeric(rownames(nobs))] - genes = levels(factor(unique(mcols(annotations)$GENEID))) - rownames(quantData$incompatibleCountMatrix) = genes[as.numeric(rownames(quantData$incompatibleCountMatrix))] +generateUniqueCounts <- function(readClassDt, countMatrix, annotations){ + x = readClassDt %>% filter(!multi_align & !is.na(eqClass.match)) + uniqueCounts = countMatrix[x$eqClass.match,] + uniqueCounts.tx = sparse.model.matrix(~ factor(x$txid) - 1) + uniqueCounts = t(uniqueCounts.tx) %*% uniqueCounts + rownames(uniqueCounts) = names(annotations)[match(as.numeric(levels(factor(x$txid))),mcols(annotations)$txid)] + counts = sparseMatrix(length(annotations), ncol(uniqueCounts), x = 0) + rownames(counts) = names(annotations) + counts[rownames(uniqueCounts),] = uniqueCounts + return(counts) + + counts.total = colSums(countMatrix) + colSums(incompatibleCountMatrix) + counts.total[counts.total==0] = 1 + counts.CPM = counts/counts.total * 10^6 - #combine the read class gene counts with incompatible counts - geneids = union(rownames(nobs), rownames(quantData$incompatibleCountMatrix)) - geneMat = sparseMatrix(length(geneids), ncol(nobs), x = 0) - rownames(geneMat) = geneids - geneMat[rownames(nobs),] = nobs - geneMat[rownames(quantData$incompatibleCountMatrix),] = geneMat[rownames(quantData$incompatibleCountMatrix),] + quantData$incompatibleCountMatrix +} +generateIncompatibleCounts <- function(incompatibleCountMatrix, annotations){ + genes = levels(factor(unique(mcols(annotations)$GENEID))) + rownames(incompatibleCountMatrix) = genes[as.numeric(rownames(incompatibleCountMatrix))] + geneMat = sparseMatrix(length(genes), ncol(incompatibleCountMatrix), x = 0) + rownames(geneMat) = genes + geneMat[rownames(incompatibleCountMatrix),] = incompatibleCountMatrix return(geneMat) -} \ No newline at end of file +} + +generateNonUniqueCounts <- function(readClassDt, countMatrix, annotations){ + #fuse multi align RCs by gene + x = readClassDt %>% filter(multi_align & !is.na(eqClass.match)) + x = x %>% distinct(eqClassId, .keep_all = TRUE) + nonuniqueCounts = countMatrix[x$eqClass.match,] + nonuniqueCounts.gene = sparse.model.matrix(~ factor(x$gene_sid) - 1) + nonuniqueCounts = t(nonuniqueCounts.gene) %*% nonuniqueCounts + #covert ids into gene ids + geneids = as.numeric(levels(factor(x$gene_sid))) + geneids = x$txid[match(geneids, x$gene_sid)] + geneids = mcols(annotations)$GENEID[as.numeric(geneids)] + rownames(nonuniqueCounts) = geneids + #create matrix for all annotated genes + genes = levels(factor(unique(mcols(annotations)$GENEID))) + geneMat = sparseMatrix(length(genes), ncol(nonuniqueCounts), x = 0) + rownames(geneMat) = genes + geneMat[rownames(nonuniqueCounts),] = nonuniqueCounts + return(geneMat) +} + diff --git a/R/bambu.R b/R/bambu.R index fee6f82e..905e7917 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -187,34 +187,53 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, } if(assignDist){ - message("--- Start calculate equivilance classes ---") + message("--- Start calculating equivilance classes ---") if (is.character(readClassList)) readClassList <- readRDS(file = readClassList) if(is.list(readClassList)) readClassList = readClassList[[1]] metadata(readClassList)$readClassDist <- calculateDistTable(readClassList, annotations, isoreParameters, verbose) readClassList = splitReadClassFiles(readClassList) - quantData = list() - quantData$readClassDt <- genEquiRCs(metadata(readClassList)$readClassDist, annotations, verbose) - quantData$countMatrix = metadata(readClassList)$countMatrix - quantData$incompatibleCountMatrix = metadata(readClassList)$incompatibleCountMatrix - quantData$readClassDt$eqClass.match = match(quantData$readClassDt$eqClassById,metadata(readClassList)$eqClassById) - quantData$readClassDt <- simplifyNames(quantData$readClassDt) - quantData$readClassDt = quantData$readClassDt %>% group_by(eqClassId, gene_sid) %>% + readClassDt <- genEquiRCs(metadata(readClassList)$readClassDist, annotations, verbose) + readClassDt$eqClass.match = match(readClassDt$eqClassById,metadata(readClassList)$eqClassById) + readClassDt <- simplifyNames(readClassDt) + readClassDt = readClassDt %>% group_by(eqClassId, gene_sid) %>% mutate(multi_align = length(unique(txid))>1) %>% ungroup() %>% mutate(aval = 1) %>% data.table() #return non-em counts - quantData$geneCounts = geneCountsFromQuantData(quantData, annotations) - x = quantData$readClassDt %>% filter(!multi_align & !is.na(eqClass.match)) - quantData$uniqueCounts = quantData$countMatrix[x$eqClass.match,] - uniqueCounts.tx = sparse.model.matrix(~ factor(x$txid) - 1) - quantData$uniqueCounts = t(uniqueCounts.tx) %*% quantData$uniqueCounts - rownames(quantData$uniqueCounts) = names(annotations)[match(as.numeric(levels(factor(x$txid))),mcols(annotations)$txid)] - + ColData = generateColData(colnames(metadata(readClassList)$countMatrix), clusters, demultiplexed, spatial) + #code to generate genecounts from quantData + if(FALSE){ + quantData$geneCounts = geneCountsFromQuantData(quantData, annotations) + counts <- quantData$geneCounts + counts.total = colSums(counts) + counts.total[counts.total==0] = 1 + counts.CPM = counts/counts.total * 10^6 + exByGene <- reducedRangesByGenes(annotations) + RowNames <- rownames(quantData$geneCounts) + geneSe <- SummarizedExperiment( + assays = SimpleList(counts = counts, + CPM = counts.CPM), + rowRanges = exByGene[RowNames], + colData = ColData) + colnames(geneSe) = colnames(quantData$countMatrix) + } + quantData <- SummarizedExperiment(assays = SimpleList( + counts = generateUniqueCounts(readClassDt, metadata(readClassList)$countMatrix, annotations)), + rowRanges = annotations, + colData = ColData) + colnames(quantData) = ColData$id + metadata(quantData)$incompatibleCounts = generateIncompatibleCounts(metadata(readClassList)$incompatibleCountMatrix, annotations) + metadata(quantData)$nonuniqueCounts = generateNonUniqueCounts(readClassDt, metadata(readClassList)$countMatrix, annotations) + metadata(quantData)$readClassDt = readClassDt + metadata(quantData)$countMatrix = metadata(readClassList)$countMatrix + metadata(quantData)$incompatibleCountMatrix = metadata(readClassList)$incompatibleCountMatrix + if (!quant) return(quantData) + } if (quant) { - message("--- Start isoform quantification ---") + message("--- Start isoform EM quantification ---") if(length(annotations)==0) stop("No valid annotations, if running de novo please try less stringent parameters") if(is.null(quantData)) stop("quantData must be provided or assignDist = TRUE") @@ -222,7 +241,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, start.ptm <- proc.time() #load in the barcode clustering from file if provided - iter = seq_len(ncol(quantData$countMatrix)) + iter = seq_len(ncol(metadata(quantData)$countMatrix)) if(!is.null(clusters)){ if(!is.list(clusters)){ clusterMap = read.table(clusters, @@ -234,13 +253,14 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, } countsSeCompressed <- bplapply(iter, FUN = function(i){ - countMatrix = unname(quantData$countMatrix[,i]) + countMatrix = unname(metadata(quantData)$countMatrix[,i]) + incompatibleCountMatrix = unname(metadata(quantData)$incompatibleCountMatrix[,i]) if(!is.null(dim(countMatrix))){ countMatrix = rowSums(countMatrix) - incompatibleCountMatrix = rowSums(quantData$incompatibleCountMatrix[,i]) + incompatibleCountMatrix = rowSums(metadata(quantData)$incompatibleCountMatrix[,i]) } - return(bambu.quantify(readClassDt = quantData$readClassDt, countMatrix = countMatrix, - incompatibleCountMatrix = data.table(GENEID.i = as.numeric(rownames(quantData$incompatibleCountMatrix)), counts = incompatibleCountMatrix), + return(bambu.quantify(readClassDt = metadata(quantData)$readClassDt, countMatrix = countMatrix, + incompatibleCountMatrix = data.table(GENEID.i = as.numeric(rownames(metadata(quantData)$incompatibleCountMatrix)), counts = incompatibleCountMatrix), txid.index = mcols(annotations)$txid, GENEIDs = GENEIDs.i, isoreParameters = isoreParameters, emParameters = emParameters, trackReads = trackReads, returnDistTable = returnDistTable, verbose = verbose))}, @@ -250,7 +270,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, if(!is.null(clusters)){ countsSeCompressed$colnames = names(clusters) } else{ - countsSeCompressed$colnames = colnames(quantData$countMatrix) + countsSeCompressed$colnames = colnames(quantData) } countsSe <- combineCountSes(countsSeCompressed, annotations) @@ -261,35 +281,9 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, # annotations) # if (returnDistTable) metadata(seOutput)$distTable = metadata(readClassDist)$distTable - df = DataFrame(sampleName = colnames(countsSe)) - if(demultiplexed & is.null(clusters)){ - df = DataFrame(id = colnames(countsSe), - sampleName = gsub("_[^_]+$","", colnames(countsSe), perl = TRUE), - Barcode = gsub(".*_(?=[^_]*$)","", colnames(countsSe), perl = TRUE)) - } - if(!is.null(spatial & is.null(clusters))){ - df$x_coordinate = NA - df$y_coordinate = NA - #load in all whitelist info, is one file or a vector of paths? - if(length(spatial)==1){ - bc_coords = DataFrame(read.table(gzfile(spatial), col.names = c("Barcode", "x_coordinate", "y_coordinate"))) - bcMatch = match(df$Barcode, bc_coords$Barcode) - df$x_coordinate = bc_coords$x_coordinate[bcMatch] - df$y_coordinate = bc_coords$y_coordinate[bcMatch] - } else{ - spatial.unique = unique(spatial) - for(whitelist in spatial.unique){ - i = which(spatial.unique==whitelist) - bc_coords = DataFrame(read.table(gzfile(whitelist), col.names = c("Barcode", "x_coordinate", "y_coordinate"))) - bcSampleIndex = df$sampleName %in% sampleNames[i] - bcMatch = match(df$Barcode[bcSampleIndex], bc_coords$Barcode) - df$x_coordinate[bcSampleIndex] = bc_coords$x_coordinate[bcMatch] - df$y_coordinate[bcSampleIndex] = bc_coords$y_coordinate[bcMatch] - } - } - } - colData(countsSe) = df - colnames(countsSe) = df[,1] + ColData = generateColData(colnames(countsSe), clusters, demultiplexed, spatial) + colData(countsSe) = ColData + colnames(countsSe) = ColData[,1] return(countsSe) } } diff --git a/R/bambu_utilityFunctions.R b/R/bambu_utilityFunctions.R index b7910293..e495126a 100644 --- a/R/bambu_utilityFunctions.R +++ b/R/bambu_utilityFunctions.R @@ -271,6 +271,38 @@ combineCountSes <- function(countsSe, annotations){ return(countsSe) } +#' Generate the coldata for se options using colnames, and other option inputs +#' @noRd +generateColData <- function(sampleNames, clusters, demultiplexed, spatial){ + ColData = DataFrame(sampleName = sampleNames) + if(demultiplexed & is.null(clusters)){ + ColData = DataFrame(id = sampleNames, + sampleName = gsub("_[^_]+$","", sampleNames, perl = TRUE), + Barcode = gsub(".*_(?=[^_]*$)","", sampleNames, perl = TRUE)) + } + if(!is.null(spatial) & is.null(clusters)){ + ColData$x_coordinate = NA + ColData$y_coordinate = NA + if(length(spatial)==1){ + bc_coords = DataFrame(read.table(gzfile(spatial), col.names = c("Barcode", "x_coordinate", "y_coordinate"))) + bcMatch = match(ColData$Barcode, bc_coords$Barcode) + ColData$x_coordinate = bc_coords$x_coordinate[bcMatch] + ColData$y_coordinate = bc_coords$y_coordinate[bcMatch] + } else{ + spatial.unique = unique(spatial) + for(whitelist in spatial.unique){ + i = which(spatial.unique==whitelist) + bc_coords = DataFrame(read.table(gzfile(whitelist), col.names = c("Barcode", "x_coordinate", "y_coordinate"))) + bcSampleIndex = ColData$sampleName %in% sampleNames[i] + bcMatch = match(ColData$Barcode[bcSampleIndex], bc_coords$Barcode) + ColData$x_coordinate[bcSampleIndex] = bc_coords$x_coordinate[bcMatch] + ColData$y_coordinate[bcSampleIndex] = bc_coords$y_coordinate[bcMatch] + } + } + } + return(ColData) +} + # Quick wrapper function (https://stackoverflow.com/questions/13273833/merging-multiple-data-tables) #' @noRd merge_wrapper <- function(x,y){ diff --git a/R/transcriptToGeneExpression.R b/R/transcriptToGeneExpression.R index f517633a..83507853 100644 --- a/R/transcriptToGeneExpression.R +++ b/R/transcriptToGeneExpression.R @@ -17,6 +17,9 @@ transcriptToGeneExpression <- function(se) { counts = fac2sparse(rowData(se)$GENEID) %*% counts incompatibleCounts <- metadata(se)$incompatibleCounts + if("nonuniqueCounts" %in% names(metadata(se))){ + incompatibleCounts = incompatibleCounts + metadata(se)$nonuniqueCounts + } incompatibleCounts = incompatibleCounts[match(rownames(counts), rownames(incompatibleCounts)),] counts = counts + incompatibleCounts counts.total = colSums(counts) From efe30f6b2de0d371d03de50c422205bbcb993919 Mon Sep 17 00:00:00 2001 From: Andre Date: Tue, 27 Aug 2024 14:34:30 +0800 Subject: [PATCH 116/189] Remove old gene count code --- R/bambu.R | 16 ---------------- 1 file changed, 16 deletions(-) diff --git a/R/bambu.R b/R/bambu.R index 905e7917..1826a208 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -201,22 +201,6 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, #return non-em counts ColData = generateColData(colnames(metadata(readClassList)$countMatrix), clusters, demultiplexed, spatial) - #code to generate genecounts from quantData - if(FALSE){ - quantData$geneCounts = geneCountsFromQuantData(quantData, annotations) - counts <- quantData$geneCounts - counts.total = colSums(counts) - counts.total[counts.total==0] = 1 - counts.CPM = counts/counts.total * 10^6 - exByGene <- reducedRangesByGenes(annotations) - RowNames <- rownames(quantData$geneCounts) - geneSe <- SummarizedExperiment( - assays = SimpleList(counts = counts, - CPM = counts.CPM), - rowRanges = exByGene[RowNames], - colData = ColData) - colnames(geneSe) = colnames(quantData$countMatrix) - } quantData <- SummarizedExperiment(assays = SimpleList( counts = generateUniqueCounts(readClassDt, metadata(readClassList)$countMatrix, annotations)), rowRanges = annotations, From d43b253ace4e19fd088ccac08375bd823786bc31 Mon Sep 17 00:00:00 2001 From: Andre Date: Mon, 2 Sep 2024 10:02:18 +0800 Subject: [PATCH 117/189] Update low memory to process read classes together or seperately This makes lowmemory readclassconstruction base line --- R/bambu-assignDist.R | 77 +++++++++++ R/bambu-processReads.R | 199 ++++++++++++++++++++-------- R/bambu-quantify_utilityFunctions.R | 46 ------- R/bambu.R | 101 ++++++-------- R/prepareDataFromBam.R | 2 - 5 files changed, 264 insertions(+), 161 deletions(-) create mode 100644 R/bambu-assignDist.R diff --git a/R/bambu-assignDist.R b/R/bambu-assignDist.R new file mode 100644 index 00000000..88e74eca --- /dev/null +++ b/R/bambu-assignDist.R @@ -0,0 +1,77 @@ +#' Create equivilence classes and assign to transcripts +#' @inheritParams bambu +#' @import data.table +#' @noRd +assignReadClasstoTranscripts <- function(readClassList, annotations, isoreParameters, verbose, clusters, demultiplexed, spatial) { + metadata(readClassList)$readClassDist <- calculateDistTable(readClassList, annotations, isoreParameters, verbose) + readClassList = splitReadClassFiles(readClassList) + readClassDt <- genEquiRCs(metadata(readClassList)$readClassDist, annotations, verbose) + readClassDt$eqClass.match = match(readClassDt$eqClassById,metadata(readClassList)$eqClassById) + readClassDt <- simplifyNames(readClassDt) + readClassDt = readClassDt %>% group_by(eqClassId, gene_sid) %>% + mutate(multi_align = length(unique(txid))>1) %>% ungroup() %>% mutate(aval = 1) %>% + data.table() + + #return non-em counts + ColData = generateColData(colnames(metadata(readClassList)$countMatrix), clusters, demultiplexed, spatial) + quantData <- SummarizedExperiment(assays = SimpleList( + counts = generateUniqueCounts(readClassDt, metadata(readClassList)$countMatrix, annotations)), + rowRanges = annotations, + colData = ColData) + colnames(quantData) = ColData$id + metadata(quantData)$incompatibleCounts = generateIncompatibleCounts(metadata(readClassList)$incompatibleCountMatrix, annotations) + metadata(quantData)$nonuniqueCounts = generateNonUniqueCounts(readClassDt, metadata(readClassList)$countMatrix, annotations) + metadata(quantData)$readClassDt = readClassDt + metadata(quantData)$countMatrix = metadata(readClassList)$countMatrix + metadata(quantData)$incompatibleCountMatrix = metadata(readClassList)$incompatibleCountMatrix + + return(quantData) + +} + + +generateUniqueCounts <- function(readClassDt, countMatrix, annotations){ + x = readClassDt %>% filter(!multi_align & !is.na(eqClass.match)) + uniqueCounts = countMatrix[x$eqClass.match,] + uniqueCounts.tx = sparse.model.matrix(~ factor(x$txid) - 1) + uniqueCounts = t(uniqueCounts.tx) %*% uniqueCounts + rownames(uniqueCounts) = names(annotations)[match(as.numeric(levels(factor(x$txid))),mcols(annotations)$txid)] + counts = sparseMatrix(length(annotations), ncol(uniqueCounts), x = 0) + rownames(counts) = names(annotations) + counts[rownames(uniqueCounts),] = uniqueCounts + return(counts) + + counts.total = colSums(countMatrix) + colSums(incompatibleCountMatrix) + counts.total[counts.total==0] = 1 + counts.CPM = counts/counts.total * 10^6 + +} + +generateIncompatibleCounts <- function(incompatibleCountMatrix, annotations){ + genes = levels(factor(unique(mcols(annotations)$GENEID))) + rownames(incompatibleCountMatrix) = genes[as.numeric(rownames(incompatibleCountMatrix))] + geneMat = sparseMatrix(length(genes), ncol(incompatibleCountMatrix), x = 0) + rownames(geneMat) = genes + geneMat[rownames(incompatibleCountMatrix),] = incompatibleCountMatrix + return(geneMat) +} + +generateNonUniqueCounts <- function(readClassDt, countMatrix, annotations){ + #fuse multi align RCs by gene + x = readClassDt %>% filter(multi_align & !is.na(eqClass.match)) + x = x %>% distinct(eqClassId, .keep_all = TRUE) + nonuniqueCounts = countMatrix[x$eqClass.match,] + nonuniqueCounts.gene = sparse.model.matrix(~ factor(x$gene_sid) - 1) + nonuniqueCounts = t(nonuniqueCounts.gene) %*% nonuniqueCounts + #covert ids into gene ids + geneids = as.numeric(levels(factor(x$gene_sid))) + geneids = x$txid[match(geneids, x$gene_sid)] + geneids = mcols(annotations)$GENEID[as.numeric(geneids)] + rownames(nonuniqueCounts) = geneids + #create matrix for all annotated genes + genes = levels(factor(unique(mcols(annotations)$GENEID))) + geneMat = sparseMatrix(length(genes), ncol(nonuniqueCounts), x = 0) + rownames(geneMat) = genes + geneMat[rownames(nonuniqueCounts),] = nonuniqueCounts + return(geneMat) +} diff --git a/R/bambu-processReads.R b/R/bambu-processReads.R index 1da9ec9c..3d94b875 100644 --- a/R/bambu-processReads.R +++ b/R/bambu-processReads.R @@ -53,39 +53,55 @@ bambu.processReads <- function(reads, annotations, genomeSequence, defaultModels = isoreParameters[["defaultModels"]] returnModel = isoreParameters[["returnModel"]] min.exonOverlap = isoreParameters[["min.exonOverlap"]] + + if(lowMemory){ + readClassList <- bplapply(seq_along(reads), function(i) { + bambu.processReadsByFile(bam.file = reads[i], + genomeSequence = genomeSequence,annotations = annotations, + readClass.outputDir = readClass.outputDir, + stranded = stranded, min.readCount = min.readCount, + fitReadClassModel = fitReadClassModel, min.exonOverlap = min.exonOverlap, + defaultModels = defaultModels, returnModel = returnModel, verbose = verbose, + trackReads = trackReads, fusionMode = fusionMode, + demultiplexed = demultiplexed, cleanReads = cleanReads, dedupUMI = dedupUMI, index = i)}, + BPPARAM = bpParameters) + } else { + readGrgList <- bplapply(seq_along(reads), function(i) { + bambu.readsByFile(bam.file = reads[i], + genomeSequence = genomeSequence,annotations = annotations, + readClass.outputDir = readClass.outputDir, + stranded = stranded, min.readCount = min.readCount, + fitReadClassModel = fitReadClassModel, min.exonOverlap = min.exonOverlap, + defaultModels = defaultModels, returnModel = returnModel, verbose = verbose, + trackReads = trackReads, fusionMode = fusionMode, + demultiplexed = demultiplexed, cleanReads = cleanReads, dedupUMI = dedupUMI, index = i)}, + BPPARAM = bpParameters) - readGrgList <- bplapply(seq_along(reads), function(i) { - bambu.processReadsByFile(bam.file = reads[i], - genomeSequence = genomeSequence,annotations = annotations, - readClass.outputDir = readClass.outputDir, - stranded = stranded, min.readCount = min.readCount, - fitReadClassModel = fitReadClassModel, min.exonOverlap = min.exonOverlap, - defaultModels = defaultModels, returnModel = returnModel, verbose = verbose, - lowMemory = lowMemory, trackReads = trackReads, fusionMode = fusionMode, - demultiplexed = demultiplexed, cleanReads = cleanReads, dedupUMI = dedupUMI, index = i)}, - BPPARAM = bpParameters) - - sampleNames = as.numeric(as.factor(sampleNames)) - for(i in seq_along(readGrgList)){ - if(!isFALSE(demultiplexed)){ - mcols(readGrgList[[i]])$BC = paste0(names(reads)[i], '_', mcols(readGrgList[[i]])$BC) - } else{mcols(readGrgList[[i]])$BC = sampleNames[i]} - mcols(readGrgList[[i]])$BC = as.factor(mcols(readGrgList[[i]])$BC) - } - readGrgList = do.call(c, readGrgList) - mcols(readGrgList)$id <- seq_along(readGrgList) - if(!isFALSE(demultiplexed)){ - mcols(readGrgList)$sampleID = as.numeric(mcols(readGrgList)$BC) - } else {mcols(readGrgList)$sampleID = mcols(readGrgList)$BC} - readClassList <- constructReadClasses(readGrgList, genomeSequence = genomeSequence,annotations = annotations, - readClass.outputDir = readClass.outputDir, - stranded = stranded, min.readCount = min.readCount, - fitReadClassModel = fitReadClassModel, min.exonOverlap = min.exonOverlap, - defaultModels = defaultModels, returnModel = returnModel, verbose = verbose, - lowMemory = lowMemory, trackReads = trackReads, fusionMode = fusionMode) + sampleNames = as.numeric(as.factor(sampleNames)) + for(i in seq_along(readGrgList)){ + if(!isFALSE(demultiplexed)){ + mcols(readGrgList[[i]])$BC = paste0(names(reads)[i], '_', mcols(readGrgList[[i]])$BC) + } else{mcols(readGrgList[[i]])$BC = sampleNames[i]} + mcols(readGrgList[[i]])$BC = as.factor(mcols(readGrgList[[i]])$BC) + } + readGrgList = do.call(c, readGrgList) + mcols(readGrgList)$id <- seq_along(readGrgList) + if(!isFALSE(demultiplexed)){ + mcols(readGrgList)$sampleID = as.numeric(mcols(readGrgList)$BC) + } else {mcols(readGrgList)$sampleID = mcols(readGrgList)$BC} + readClassList <- constructReadClasses(readGrgList, genomeSequence = genomeSequence,annotations = annotations, + readClass.outputDir = readClass.outputDir, + stranded = stranded, min.readCount = min.readCount, + fitReadClassModel = fitReadClassModel, min.exonOverlap = min.exonOverlap, + defaultModels = defaultModels, returnModel = returnModel, verbose = verbose, + trackReads = trackReads, fusionMode = fusionMode) - metadata(readClassList)$samples = names(reads) - if(!isFALSE(demultiplexed))metadata(readClassList)$samples = levels(mcols(readGrgList)$BC) + metadata(readClassList)$samples = names(reads) + if(!isFALSE(demultiplexed))metadata(readClassList)$samples = levels(mcols(readGrgList)$BC) + readClassList = list(readClassList) + } + + # TODO return output # if (!is.null(readClass.outputDir)) { @@ -103,7 +119,7 @@ bambu.processReads <- function(reads, annotations, genomeSequence, # se <- readClassFile # } #TODO don't output list, current there because discovery needs it - return(list(readClassList)) + return(readClassList) } #' Preprocess bam files and save read class files @@ -113,10 +129,100 @@ bambu.processReads <- function(reads, annotations, genomeSequence, bambu.processReadsByFile <- function(bam.file, genomeSequence, annotations, readClass.outputDir = NULL, yieldSize = NULL, stranded = FALSE, min.readCount = 2, fitReadClassModel = TRUE, min.exonOverlap = 10, defaultModels = NULL, returnModel = FALSE, - verbose = FALSE, lowMemory = FALSE, trackReads = FALSE, fusionMode = FALSE, demultiplexed = FALSE, + verbose = FALSE, trackReads = FALSE, fusionMode = FALSE, demultiplexed = FALSE, + cleanReads = TRUE, dedupUMI = FALSE, index = 0) { + if(verbose) message(names(bam.file)[1]) + readGrgList <- prepareDataFromBam(bam.file[[1]], verbose = verbose, yieldSize = yieldSize, use.names = trackReads, demultiplexed = demultiplexed, cleanReads = cleanReads, dedupUMI = dedupUMI) + if(verbose) message(paste0("Number of alignments/reads: ",length(readGrgList))) + warnings = c() + warnings = seqlevelCheckReadsAnnotation(readGrgList, annotations) + if(verbose & length(warnings) > 0) warning(paste(warnings,collapse = "\n")) + #check seqlevels for consistency, drop ranges not present in genomeSequence + refSeqLevels <- seqlevels(genomeSequence) + if (!all(seqlevels(readGrgList) %in% refSeqLevels)) { + refSeqLevels <- intersect(refSeqLevels, seqlevels(readGrgList)) + if (!all(seqlevels(annotations) %in% refSeqLevels)&(!(length(annotations)==0))) { + refSeqLevels <- intersect(refSeqLevels, seqlevels(annotations)) + warningText = paste0("not all chromosomes from annotations present in ", + "reference genome sequence, annotations without reference genomic sequence ", + "are dropped") + warnings = c(warnings, warningText) + if(verbose) warning(warningText) + annotations <- keepSeqlevels(annotations, value = refSeqLevels, + pruning.mode = "coarse") + } + warningText = paste0("not all chromosomes from reads present in reference ", + "genome sequence, reads without reference chromosome sequence are dropped") + warnings = c(warnings, warningText) + if(verbose) warning(warningText) + readGrgList <- keepSeqlevels(readGrgList, value = refSeqLevels, + pruning.mode = "coarse") + # reassign Ids after seqlevels are dropped + mcols(readGrgList)$id <- seq_along(readGrgList) + } + #removes reads that are outside genome coordinates + badReads = which(max(end(ranges(readGrgList)))>= + seqlengths(genomeSequence)[as.character(getChrFromGrList(readGrgList))]) + if(length(badReads) > 0 ){ + readGrgList = readGrgList[-badReads] + warningText = paste0(length(badReads), " reads are mapped outside the provided ", + "genomic regions. These reads will be dropped. Check you are using the ", + "same genome used for the alignment") + warnings = c(warnings, warningText) + if(verbose) warning(warningText) + } + if(length(readGrgList) == 0) { + stop("No reads left after filtering.") + } + mcols(readGrgList)$id <- seq_along(readGrgList) + + sampleName = names(bam.file)[1] + if(!isFALSE(demultiplexed)){ + mcols(readGrgList)$BC = paste0(sampleName, '_', mcols(readGrgList)$BC) + } else{mcols(readGrgList)$BC = sampleName} + mcols(readGrgList)$BC = as.factor(mcols(readGrgList)$BC) + if(!isFALSE(demultiplexed)){ + mcols(readGrgList)$sampleID = as.numeric(mcols(readGrgList)$BC) + } else {mcols(readGrgList)$sampleID = mcols(readGrgList)$BC} + + # construct read classes for each chromosome seperately + se <- lowMemoryConstructReadClasses(readGrgList, genomeSequence, + annotations, stranded, verbose,bam.file) + + + metadata(se)$warnings = warnings + if(trackReads){ + metadata(se)$readNames = names(readGrgList) + metadata(se)$readId = mcols(readGrgList)$id + } + refSeqLevels <- seqlevels(genomeSequence) + GenomeInfoDb::seqlevels(se) <- refSeqLevels + # create SE object with reconstructed readClasses + se <- scoreReadClasses(se, genomeSequence, annotations, + defaultModels = defaultModels, + fit = fitReadClassModel, + returnModel = returnModel, + min.readCount = min.readCount, + min.exonOverlap = min.exonOverlap, + fusionMode = fusionMode, + verbose = verbose) + + metadata(se)$samples = names(bam.file)[1] + if(!isFALSE(demultiplexed))metadata(se)$samples = levels(mcols(readGrgList)$BC) + return(se) +} + +#' Preprocess bam files and save read class files +#' @inheritParams bambu +#' @importFrom GenomeInfoDb seqlevels seqlevels<- keepSeqlevels +#' @noRd +bambu.readsByFile <- function(bam.file, genomeSequence, annotations, + readClass.outputDir = NULL, yieldSize = NULL, stranded = FALSE, min.readCount = 2, + fitReadClassModel = TRUE, min.exonOverlap = 10, defaultModels = NULL, returnModel = FALSE, + verbose = FALSE, trackReads = FALSE, fusionMode = FALSE, demultiplexed = FALSE, cleanReads = TRUE, dedupUMI = FALSE, index = 0) { readGrgList <- prepareDataFromBam(bam.file[[1]], verbose = verbose, yieldSize = yieldSize, use.names = trackReads, demultiplexed = demultiplexed, cleanReads = cleanReads, dedupUMI = dedupUMI) - print(paste0("Number of alignments/reads: ",length(readGrgList))) + if(verbose) message("Number of alignments/reads: ",length(readGrgList))) warnings = c() warnings = seqlevelCheckReadsAnnotation(readGrgList, annotations) if(verbose & length(warnings) > 0) {warning(paste(warnings,collapse = "\n"))} @@ -159,7 +265,7 @@ bambu.processReadsByFile <- function(bam.file, genomeSequence, annotations, # reassign Ids after seqlevels are dropped mcols(readGrgList)$id <- seq_along(readGrgList) ### add ### - print(paste0("Number of post-filter alignments/reads: ",length(readGrgList))) + if(verbose) message("Number of post-filter alignments/reads: ",length(readGrgList))) if(length(readGrgList) == 0) { stop("No reads left after filtering.") } @@ -183,28 +289,11 @@ bambu.processReadsByFile <- function(bam.file, genomeSequence, annotations, constructReadClasses <- function(readGrgList, genomeSequence, annotations, readClass.outputDir = NULL, stranded = FALSE, min.readCount = 2, fitReadClassModel = TRUE, min.exonOverlap = 10, defaultModels = NULL, returnModel = FALSE, - verbose = FALSE, lowMemory = FALSE, trackReads = FALSE, fusionMode = FALSE){ + verbose = FALSE, trackReads = FALSE, fusionMode = FALSE){ warnings = c() ###TODO # construct read classes for each chromosome seperately - if(lowMemory) {se <- lowMemoryConstructReadClasses(readGrgList, genomeSequence, - annotations, stranded, verbose,"TODO") - } else { - unlisted_junctions <- unlistIntrons(readGrgList, use.ids = TRUE) - if(length(unlisted_junctions)==0){ - warningText = paste0("No aligned spliced reads detected!", - "Bambu expects spliced reads. If this is intended, ", - "see Documentation on how to handle single-exon ", - "transcripts") - warnings = c(warnings, warningText) - if (verbose) warning(warningText) - } - uniqueJunctions <- isore.constructJunctionTables(unlisted_junctions, - annotations,genomeSequence, stranded = stranded, verbose = verbose) - # create SE object with reconstructed readClasses - se <- isore.constructReadClasses(readGrgList, unlisted_junctions, - uniqueJunctions, runName = "TODO", - annotations, stranded, verbose) - } + se <- lowMemoryConstructReadClasses(readGrgList, genomeSequence, + annotations, stranded, verbose,"TODO") metadata(se)$warnings = warnings if(trackReads){ diff --git a/R/bambu-quantify_utilityFunctions.R b/R/bambu-quantify_utilityFunctions.R index d324ef5d..0751e4ae 100644 --- a/R/bambu-quantify_utilityFunctions.R +++ b/R/bambu-quantify_utilityFunctions.R @@ -522,49 +522,3 @@ NULL library.dynam.unload("bambu", libpath) } -generateUniqueCounts <- function(readClassDt, countMatrix, annotations){ - x = readClassDt %>% filter(!multi_align & !is.na(eqClass.match)) - uniqueCounts = countMatrix[x$eqClass.match,] - uniqueCounts.tx = sparse.model.matrix(~ factor(x$txid) - 1) - uniqueCounts = t(uniqueCounts.tx) %*% uniqueCounts - rownames(uniqueCounts) = names(annotations)[match(as.numeric(levels(factor(x$txid))),mcols(annotations)$txid)] - counts = sparseMatrix(length(annotations), ncol(uniqueCounts), x = 0) - rownames(counts) = names(annotations) - counts[rownames(uniqueCounts),] = uniqueCounts - return(counts) - - counts.total = colSums(countMatrix) + colSums(incompatibleCountMatrix) - counts.total[counts.total==0] = 1 - counts.CPM = counts/counts.total * 10^6 - -} - -generateIncompatibleCounts <- function(incompatibleCountMatrix, annotations){ - genes = levels(factor(unique(mcols(annotations)$GENEID))) - rownames(incompatibleCountMatrix) = genes[as.numeric(rownames(incompatibleCountMatrix))] - geneMat = sparseMatrix(length(genes), ncol(incompatibleCountMatrix), x = 0) - rownames(geneMat) = genes - geneMat[rownames(incompatibleCountMatrix),] = incompatibleCountMatrix - return(geneMat) -} - -generateNonUniqueCounts <- function(readClassDt, countMatrix, annotations){ - #fuse multi align RCs by gene - x = readClassDt %>% filter(multi_align & !is.na(eqClass.match)) - x = x %>% distinct(eqClassId, .keep_all = TRUE) - nonuniqueCounts = countMatrix[x$eqClass.match,] - nonuniqueCounts.gene = sparse.model.matrix(~ factor(x$gene_sid) - 1) - nonuniqueCounts = t(nonuniqueCounts.gene) %*% nonuniqueCounts - #covert ids into gene ids - geneids = as.numeric(levels(factor(x$gene_sid))) - geneids = x$txid[match(geneids, x$gene_sid)] - geneids = mcols(annotations)$GENEID[as.numeric(geneids)] - rownames(nonuniqueCounts) = geneids - #create matrix for all annotated genes - genes = levels(factor(unique(mcols(annotations)$GENEID))) - geneMat = sparseMatrix(length(genes), ncol(nonuniqueCounts), x = 0) - rownames(geneMat) = genes - geneMat[rownames(nonuniqueCounts),] = nonuniqueCounts - return(geneMat) -} - diff --git a/R/bambu.R b/R/bambu.R index 1826a208..7e0d0c72 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -189,82 +189,67 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, if(assignDist){ message("--- Start calculating equivilance classes ---") if (is.character(readClassList)) readClassList <- readRDS(file = readClassList) - if(is.list(readClassList)) readClassList = readClassList[[1]] - metadata(readClassList)$readClassDist <- calculateDistTable(readClassList, annotations, isoreParameters, verbose) - readClassList = splitReadClassFiles(readClassList) - readClassDt <- genEquiRCs(metadata(readClassList)$readClassDist, annotations, verbose) - readClassDt$eqClass.match = match(readClassDt$eqClassById,metadata(readClassList)$eqClassById) - readClassDt <- simplifyNames(readClassDt) - readClassDt = readClassDt %>% group_by(eqClassId, gene_sid) %>% - mutate(multi_align = length(unique(txid))>1) %>% ungroup() %>% mutate(aval = 1) %>% - data.table() - - #return non-em counts - ColData = generateColData(colnames(metadata(readClassList)$countMatrix), clusters, demultiplexed, spatial) - quantData <- SummarizedExperiment(assays = SimpleList( - counts = generateUniqueCounts(readClassDt, metadata(readClassList)$countMatrix, annotations)), - rowRanges = annotations, - colData = ColData) - colnames(quantData) = ColData$id - metadata(quantData)$incompatibleCounts = generateIncompatibleCounts(metadata(readClassList)$incompatibleCountMatrix, annotations) - metadata(quantData)$nonuniqueCounts = generateNonUniqueCounts(readClassDt, metadata(readClassList)$countMatrix, annotations) - metadata(quantData)$readClassDt = readClassDt - metadata(quantData)$countMatrix = metadata(readClassList)$countMatrix - metadata(quantData)$incompatibleCountMatrix = metadata(readClassList)$incompatibleCountMatrix - - if (!quant) return(quantData) - + #if(is.list(readClassList)) readClassList = readClassList[[1]] + quantDatas = bplapply(readClassList, FUN = assignReadClasstoTranscripts, + annotations = annotations, isoreParameters = isoreParameters, verbose = verbose, + clusters = clusters, demultiplexed = demultiplexed, spatial = spatial, + BPPARAM = bpParameters) + if (!quant) return(quantDatas) } if (quant) { message("--- Start isoform EM quantification ---") if(length(annotations)==0) stop("No valid annotations, if running de novo please try less stringent parameters") - if(is.null(quantData)) stop("quantData must be provided or assignDist = TRUE") + if(is.null(quantDatas)) stop("quantData must be provided or assignDist = TRUE") GENEIDs.i = as.numeric(factor(unique(mcols(annotations)$GENEID))) start.ptm <- proc.time() - - #load in the barcode clustering from file if provided - iter = seq_len(ncol(metadata(quantData)$countMatrix)) - if(!is.null(clusters)){ - if(!is.list(clusters)){ - clusterMap = read.table(clusters, - sep = ifelse(grepl(".tsv$",clusters), "\t", ","), header = FALSE) - clusters = splitAsList(clusterMap[,1], clusterMap[,2]) - rm(clusterMap) + countsSeCompressed.all = NULL + ColNames = c() + for(quantData in quantDatas){ + #load in the barcode clustering from file if provided + iter = seq_len(ncol(metadata(quantData)$countMatrix)) + if(!is.null(clusters)){ + if(!is.list(clusters)){ + clusterMap = read.table(clusters, + sep = ifelse(grepl(".tsv$",clusters), "\t", ","), header = FALSE) + clusters = splitAsList(clusterMap[,1], clusterMap[,2]) + rm(clusterMap) + } + iter = clusters } - iter = clusters - } - countsSeCompressed <- bplapply(iter, FUN = function(i){ - countMatrix = unname(metadata(quantData)$countMatrix[,i]) - incompatibleCountMatrix = unname(metadata(quantData)$incompatibleCountMatrix[,i]) - if(!is.null(dim(countMatrix))){ - countMatrix = rowSums(countMatrix) - incompatibleCountMatrix = rowSums(metadata(quantData)$incompatibleCountMatrix[,i]) + countsSeCompressed <- bplapply(iter, FUN = function(i){ + countMatrix = unname(metadata(quantData)$countMatrix[,i]) + incompatibleCountMatrix = unname(metadata(quantData)$incompatibleCountMatrix[,i]) + if(!is.null(dim(countMatrix))){ + countMatrix = rowSums(countMatrix) + incompatibleCountMatrix = rowSums(metadata(quantData)$incompatibleCountMatrix[,i]) + } + return(bambu.quantify(readClassDt = metadata(quantData)$readClassDt, countMatrix = countMatrix, + incompatibleCountMatrix = data.table(GENEID.i = as.numeric(rownames(metadata(quantData)$incompatibleCountMatrix)), counts = incompatibleCountMatrix), + txid.index = mcols(annotations)$txid, GENEIDs = GENEIDs.i, isoreParameters = isoreParameters, + emParameters = emParameters, trackReads = trackReads, + returnDistTable = returnDistTable, verbose = verbose))}, + BPPARAM = bpParameters) + end.ptm <- proc.time() + message("Total Time ", round((end.ptm - start.ptm)[3] / 60, 3), " mins.") + if(!is.null(clusters)){ + ColNames = c(ColNames, names(clusters)) + } else{ + ColNames = c(ColNames, colnames(quantData)) } - return(bambu.quantify(readClassDt = metadata(quantData)$readClassDt, countMatrix = countMatrix, - incompatibleCountMatrix = data.table(GENEID.i = as.numeric(rownames(metadata(quantData)$incompatibleCountMatrix)), counts = incompatibleCountMatrix), - txid.index = mcols(annotations)$txid, GENEIDs = GENEIDs.i, isoreParameters = isoreParameters, - emParameters = emParameters, trackReads = trackReads, - returnDistTable = returnDistTable, verbose = verbose))}, - BPPARAM = bpParameters) - end.ptm <- proc.time() - message("Total Time ", round((end.ptm - start.ptm)[3] / 60, 3), " mins.") - if(!is.null(clusters)){ - countsSeCompressed$colnames = names(clusters) - } else{ - countsSeCompressed$colnames = colnames(quantData) + countsSeCompressed.all = c(countsSeCompressed.all, countsSeCompressed) } - - countsSe <- combineCountSes(countsSeCompressed, annotations) + countsSeCompressed.all$colnames = ColNames + #return(countsSeCompressed.all) + countsSe <- combineCountSes(countsSeCompressed.all, annotations) #metadata(countsSe)$warnings = warnings # if (trackReads) metadata(seOutput)$readToTranscriptMap = # generateReadToTranscriptMap(readClass, metadata(readClassDist)$distTable, # annotations) # if (returnDistTable) metadata(seOutput)$distTable = metadata(readClassDist)$distTable - ColData = generateColData(colnames(countsSe), clusters, demultiplexed, spatial) colData(countsSe) = ColData colnames(countsSe) = ColData[,1] diff --git a/R/prepareDataFromBam.R b/R/prepareDataFromBam.R index 864f022c..2c90f491 100755 --- a/R/prepareDataFromBam.R +++ b/R/prepareDataFromBam.R @@ -84,9 +84,7 @@ prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE, } # remove microexons of width 1bp from list readGrgList <- readGrgList[width(readGrgList) > 1] - print(head(mcols(readGrgList))) numNoBCs = sum(is.na(mcols(readGrgList)$BC)) - print(numNoBCs) if(numNoBCs > 0){ message("Removing ", numNoBCs, " reads that were not assigned barcodes. If this is unexpected check the barcode map input") readGrgList = readGrgList[!is.na(mcols(readGrgList)$BC)] From 716370c3b67c5d92ff649ba6405ade3068940020 Mon Sep 17 00:00:00 2001 From: Andre Date: Mon, 2 Sep 2024 13:31:57 +0800 Subject: [PATCH 118/189] Can now provide multiple clusterings per quant input --- R/bambu.R | 11 ++++++----- 1 file changed, 6 insertions(+), 5 deletions(-) diff --git a/R/bambu.R b/R/bambu.R index 7e0d0c72..0f3abb6c 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -206,17 +206,18 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, start.ptm <- proc.time() countsSeCompressed.all = NULL ColNames = c() - for(quantData in quantDatas){ + for(i in seq_along(quantDatas)){ + quantData = quantDatas[[i]] #load in the barcode clustering from file if provided iter = seq_len(ncol(metadata(quantData)$countMatrix)) if(!is.null(clusters)){ if(!is.list(clusters)){ - clusterMap = read.table(clusters, - sep = ifelse(grepl(".tsv$",clusters), "\t", ","), header = FALSE) - clusters = splitAsList(clusterMap[,1], clusterMap[,2]) + clusterMap = read.table(clusters[[i]], + sep = ifelse(grepl(".tsv$",clusters[[i]]), "\t", ","), header = FALSE) + clustering = splitAsList(clusterMap[,1], clusterMap[,2]) rm(clusterMap) } - iter = clusters + iter = clustering } countsSeCompressed <- bplapply(iter, FUN = function(i){ From 8fb23e0703a37252205100aa26c7b29d49e49470 Mon Sep 17 00:00:00 2001 From: Andre Date: Mon, 2 Sep 2024 16:30:34 +0800 Subject: [PATCH 119/189] tidy up --- R/bambu-assignDist.R | 4 ++-- R/bambu-processReads.R | 4 ++-- R/bambu.R | 4 ++-- 3 files changed, 6 insertions(+), 6 deletions(-) diff --git a/R/bambu-assignDist.R b/R/bambu-assignDist.R index 88e74eca..6a5b15fe 100644 --- a/R/bambu-assignDist.R +++ b/R/bambu-assignDist.R @@ -2,7 +2,7 @@ #' @inheritParams bambu #' @import data.table #' @noRd -assignReadClasstoTranscripts <- function(readClassList, annotations, isoreParameters, verbose, clusters, demultiplexed, spatial) { +assignReadClasstoTranscripts <- function(readClassList, annotations, isoreParameters, verbose, demultiplexed, spatial) { metadata(readClassList)$readClassDist <- calculateDistTable(readClassList, annotations, isoreParameters, verbose) readClassList = splitReadClassFiles(readClassList) readClassDt <- genEquiRCs(metadata(readClassList)$readClassDist, annotations, verbose) @@ -13,7 +13,7 @@ assignReadClasstoTranscripts <- function(readClassList, annotations, isoreParame data.table() #return non-em counts - ColData = generateColData(colnames(metadata(readClassList)$countMatrix), clusters, demultiplexed, spatial) + ColData = generateColData(colnames(metadata(readClassList)$countMatrix), clusters = NULL, demultiplexed, spatial) quantData <- SummarizedExperiment(assays = SimpleList( counts = generateUniqueCounts(readClassDt, metadata(readClassList)$countMatrix, annotations)), rowRanges = annotations, diff --git a/R/bambu-processReads.R b/R/bambu-processReads.R index 3d94b875..8fb43bfa 100644 --- a/R/bambu-processReads.R +++ b/R/bambu-processReads.R @@ -222,7 +222,7 @@ bambu.readsByFile <- function(bam.file, genomeSequence, annotations, verbose = FALSE, trackReads = FALSE, fusionMode = FALSE, demultiplexed = FALSE, cleanReads = TRUE, dedupUMI = FALSE, index = 0) { readGrgList <- prepareDataFromBam(bam.file[[1]], verbose = verbose, yieldSize = yieldSize, use.names = trackReads, demultiplexed = demultiplexed, cleanReads = cleanReads, dedupUMI = dedupUMI) - if(verbose) message("Number of alignments/reads: ",length(readGrgList))) + if(verbose) message("Number of alignments/reads: ",length(readGrgList)) warnings = c() warnings = seqlevelCheckReadsAnnotation(readGrgList, annotations) if(verbose & length(warnings) > 0) {warning(paste(warnings,collapse = "\n"))} @@ -265,7 +265,7 @@ bambu.readsByFile <- function(bam.file, genomeSequence, annotations, # reassign Ids after seqlevels are dropped mcols(readGrgList)$id <- seq_along(readGrgList) ### add ### - if(verbose) message("Number of post-filter alignments/reads: ",length(readGrgList))) + if(verbose) message("Number of post-filter alignments/reads: ",length(readGrgList)) if(length(readGrgList) == 0) { stop("No reads left after filtering.") } diff --git a/R/bambu.R b/R/bambu.R index 0f3abb6c..d576e6b8 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -191,8 +191,8 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, if (is.character(readClassList)) readClassList <- readRDS(file = readClassList) #if(is.list(readClassList)) readClassList = readClassList[[1]] quantDatas = bplapply(readClassList, FUN = assignReadClasstoTranscripts, - annotations = annotations, isoreParameters = isoreParameters, verbose = verbose, - clusters = clusters, demultiplexed = demultiplexed, spatial = spatial, + annotations = annotations, isoreParameters = isoreParameters, verbose = verbose, + demultiplexed = demultiplexed, spatial = spatial, BPPARAM = bpParameters) if (!quant) return(quantDatas) } From 55177e22146966e528e82a2a3e841c3ec8161d71 Mon Sep 17 00:00:00 2001 From: Andre Date: Mon, 2 Sep 2024 19:33:50 +0800 Subject: [PATCH 120/189] clean up warnings --- ...-processReads_utilityConstructReadClasses.R | 18 ++++++++++++------ R/prepareDataFromBam.R | 8 ++++---- 2 files changed, 16 insertions(+), 10 deletions(-) diff --git a/R/bambu-processReads_utilityConstructReadClasses.R b/R/bambu-processReads_utilityConstructReadClasses.R index 1972dab5..1f4094e2 100644 --- a/R/bambu-processReads_utilityConstructReadClasses.R +++ b/R/bambu-processReads_utilityConstructReadClasses.R @@ -462,11 +462,13 @@ assignGeneIdsByReference <- function(grl, annotations, min.exonOverlap = 10, geneIds[filteredMultiHits$queryHits] <- filteredMultiHits$geneid } else { - filteredMultiHits <- filteredMultiHits %>% - group_by(queryHits) %>% summarise(subjectHits = subjectHits[which.max(intersectWidth)], - intersectWidth = max(intersectWidth)) - geneIds[filteredMultiHits$queryHits] <- - names(geneRanges)[filteredMultiHits$subjectHits] + if(nrow(filteredMultiHits) > 0){ + filteredMultiHits <- filteredMultiHits %>% + group_by(queryHits) %>% summarise(subjectHits = subjectHits[which.max(intersectWidth)], + intersectWidth = max(intersectWidth)) + geneIds[filteredMultiHits$queryHits] <- + names(geneRanges)[filteredMultiHits$subjectHits] + } } } return(geneIds) @@ -581,7 +583,11 @@ assignGeneIdsNonAssigned = function(geneTxMap, exonTxMap, geneExonMap, dplyr::select(newGeneId, newExonId) %>% distinct() } # combined gene ids - refGeneTxMapMins = refGeneTxMap %>% group_by(newTxId) %>% filter(n() > 1) %>% filter(newGeneId == min(newGeneId)) %>% ungroup() + refGeneTxMap.tmp = refGeneTxMap %>% group_by(newTxId) %>% filter(n() > 1) + if(nrow(refGeneTxMap.tmp) == 0){refGeneTxMapMins = refGeneTxMap[0,] + } else{ + refGeneTxMapMins = refGeneTxMap.tmp %>% filter(newGeneId == min(newGeneId)) %>% ungroup() + } refGeneTxMapNotMins = refGeneTxMap %>% group_by(newTxId) %>% filter(newGeneId != min(newGeneId)) %>% ungroup() geneGeneMap <- left_join(refGeneTxMapMins, dplyr::rename(refGeneTxMapNotMins, newGeneId.merge=newGeneId), by = "newTxId") %>% diff --git a/R/prepareDataFromBam.R b/R/prepareDataFromBam.R index 2c90f491..35bedc13 100755 --- a/R/prepareDataFromBam.R +++ b/R/prepareDataFromBam.R @@ -59,10 +59,10 @@ prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE, mcols(readGrgList[[counter]])$UMI <- factor(mcols(readGrgList[[counter]])$UMI, levels = umi) } if(cleanReads){ - softClip5Prime <-pmax(0,as.numeric(gsub('^(\\d*)[S].*','\\1',GenomicAlignments::cigar(alignmentInfo))), na.rm=T) - softClip3Prime <-pmax(0,as.numeric(gsub('.*\\D(\\d*)[S]$','\\1',GenomicAlignments::cigar(alignmentInfo))), na.rm=T) - hardClip5Prime <-pmax(0,as.numeric(gsub('^(\\d*)[H].*','\\1',GenomicAlignments::cigar(alignmentInfo))), na.rm=T) - hardClip3Prime <-pmax(0,as.numeric(gsub('.*\\D(\\d*)[H]$','\\1',GenomicAlignments::cigar(alignmentInfo))), na.rm=T) + softClip5Prime <-suppressWarnings(pmax(0,as.numeric(gsub('^(\\d*)[S].*','\\1',GenomicAlignments::cigar(alignmentInfo))), na.rm=T)) + softClip3Prime <-suppressWarnings(pmax(0,as.numeric(gsub('.*\\D(\\d*)[S]$','\\1',GenomicAlignments::cigar(alignmentInfo))), na.rm=T)) + hardClip5Prime <-suppressWarnings(pmax(0,as.numeric(gsub('^(\\d*)[H].*','\\1',GenomicAlignments::cigar(alignmentInfo))), na.rm=T)) + hardClip3Prime <-suppressWarnings(pmax(0,as.numeric(gsub('.*\\D(\\d*)[H]$','\\1',GenomicAlignments::cigar(alignmentInfo))), na.rm=T)) mcols(readGrgList[[counter]])$clip5Prime = pmax(softClip5Prime, hardClip5Prime) mcols(readGrgList[[counter]])$clip3Prime = pmax(softClip3Prime, hardClip3Prime) rev = as.vector(strand(alignmentInfo) == '-') From c64d66725934460da98b55103f14511bfd7c8c85 Mon Sep 17 00:00:00 2001 From: Andre Date: Tue, 3 Sep 2024 16:33:38 +0800 Subject: [PATCH 121/189] Make sure column names are present when providing clusters --- R/bambu.R | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/R/bambu.R b/R/bambu.R index d576e6b8..eae39349 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -216,8 +216,9 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, sep = ifelse(grepl(".tsv$",clusters[[i]]), "\t", ","), header = FALSE) clustering = splitAsList(clusterMap[,1], clusterMap[,2]) rm(clusterMap) + iter = clustering } - iter = clustering + iter = clusters[[i]] } countsSeCompressed <- bplapply(iter, FUN = function(i){ @@ -236,7 +237,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, end.ptm <- proc.time() message("Total Time ", round((end.ptm - start.ptm)[3] / 60, 3), " mins.") if(!is.null(clusters)){ - ColNames = c(ColNames, names(clusters)) + ColNames = c(ColNames, names(clusters[i])) } else{ ColNames = c(ColNames, colnames(quantData)) } From 87dc7942abc26e957972a9f19080570a0d0f7540 Mon Sep 17 00:00:00 2001 From: Andre Date: Wed, 4 Sep 2024 14:40:38 +0800 Subject: [PATCH 122/189] fix colData bug missing names --- R/bambu.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/R/bambu.R b/R/bambu.R index eae39349..66d87e0d 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -237,7 +237,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, end.ptm <- proc.time() message("Total Time ", round((end.ptm - start.ptm)[3] / 60, 3), " mins.") if(!is.null(clusters)){ - ColNames = c(ColNames, names(clusters[i])) + ColNames = c(ColNames, names(iter)) } else{ ColNames = c(ColNames, colnames(quantData)) } From 8931903838a074c24850c8cec3ddf831391b7438 Mon Sep 17 00:00:00 2001 From: Andre Date: Wed, 4 Sep 2024 16:14:41 +0800 Subject: [PATCH 123/189] Track sample names into quantData --- R/bambu-assignDist.R | 2 +- R/bambu-processReads.R | 2 ++ 2 files changed, 3 insertions(+), 1 deletion(-) diff --git a/R/bambu-assignDist.R b/R/bambu-assignDist.R index 6a5b15fe..052622ce 100644 --- a/R/bambu-assignDist.R +++ b/R/bambu-assignDist.R @@ -24,7 +24,7 @@ assignReadClasstoTranscripts <- function(readClassList, annotations, isoreParame metadata(quantData)$readClassDt = readClassDt metadata(quantData)$countMatrix = metadata(readClassList)$countMatrix metadata(quantData)$incompatibleCountMatrix = metadata(readClassList)$incompatibleCountMatrix - + metadata(quantData)$sampleNames = metadata(readClassList)$sampleNames return(quantData) } diff --git a/R/bambu-processReads.R b/R/bambu-processReads.R index 8fb43bfa..24d79459 100644 --- a/R/bambu-processReads.R +++ b/R/bambu-processReads.R @@ -97,6 +97,7 @@ bambu.processReads <- function(reads, annotations, genomeSequence, trackReads = trackReads, fusionMode = fusionMode) metadata(readClassList)$samples = names(reads) + metadata(readClassList)$sampleNames = names(reads) if(!isFALSE(demultiplexed))metadata(readClassList)$samples = levels(mcols(readGrgList)$BC) readClassList = list(readClassList) } @@ -208,6 +209,7 @@ bambu.processReadsByFile <- function(bam.file, genomeSequence, annotations, verbose = verbose) metadata(se)$samples = names(bam.file)[1] + metadata(readClassList)$sampleNames = names(bam.file)[1] if(!isFALSE(demultiplexed))metadata(se)$samples = levels(mcols(readGrgList)$BC) return(se) } From 76799124c419fdf1d1e8c703a62e8b1771a8a00a Mon Sep 17 00:00:00 2001 From: Andre Date: Wed, 4 Sep 2024 16:18:02 +0800 Subject: [PATCH 124/189] Fix clustering to work with different input combinations remove print --- R/bambu.R | 18 +++++++++++++----- 1 file changed, 13 insertions(+), 5 deletions(-) diff --git a/R/bambu.R b/R/bambu.R index 66d87e0d..d5af46f1 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -212,15 +212,23 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, iter = seq_len(ncol(metadata(quantData)$countMatrix)) if(!is.null(clusters)){ if(!is.list(clusters)){ - clusterMap = read.table(clusters[[i]], - sep = ifelse(grepl(".tsv$",clusters[[i]]), "\t", ","), header = FALSE) - clustering = splitAsList(clusterMap[,1], clusterMap[,2]) + clusterMaps = NULL + for(j in seq_along(metadata(quantData)$sampleNames)){ #load in a file per sample name provided + clusterMap = read.table(clusters[[j]], + sep = ifelse(grepl(".tsv$",clusters[[j]]), "\t", ","), header = FALSE) + clusterMap[,1] = paste0(metadata(quantData)$sampleNames[j],"_",clusterMap[,1]) + clusterMaps = rbind(clusterMaps, clusterMap) + } + clustering = splitAsList(clusterMaps[,1], clusterMaps[,2]) + rm(clusterMaps) rm(clusterMap) iter = clustering + + } else{ #if clusters is a list + if(length(quantDatas)>1){iter = clusters[[i]] #lowMemory mode + }else(iter = do.call(c,clusters)) } - iter = clusters[[i]] } - countsSeCompressed <- bplapply(iter, FUN = function(i){ countMatrix = unname(metadata(quantData)$countMatrix[,i]) incompatibleCountMatrix = unname(metadata(quantData)$incompatibleCountMatrix[,i]) From 2e30fc4f443820aa6e2755747ff5e220d4cfc744 Mon Sep 17 00:00:00 2001 From: Andre Date: Wed, 4 Sep 2024 16:24:33 +0800 Subject: [PATCH 125/189] bug fix missing sampleNames --- R/bambu-processReads.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/R/bambu-processReads.R b/R/bambu-processReads.R index 24d79459..c8a0571b 100644 --- a/R/bambu-processReads.R +++ b/R/bambu-processReads.R @@ -209,7 +209,7 @@ bambu.processReadsByFile <- function(bam.file, genomeSequence, annotations, verbose = verbose) metadata(se)$samples = names(bam.file)[1] - metadata(readClassList)$sampleNames = names(bam.file)[1] + metadata(se)$sampleNames = names(bam.file)[1] if(!isFALSE(demultiplexed))metadata(se)$samples = levels(mcols(readGrgList)$BC) return(se) } From 0fd3f9e23619f01e57c373a6cc78b5780cba1d41 Mon Sep 17 00:00:00 2001 From: Andre Date: Wed, 4 Sep 2024 17:01:35 +0800 Subject: [PATCH 126/189] make sure EM counts are labeled as such --- R/bambu_utilityFunctions.R | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/R/bambu_utilityFunctions.R b/R/bambu_utilityFunctions.R index e495126a..65313318 100644 --- a/R/bambu_utilityFunctions.R +++ b/R/bambu_utilityFunctions.R @@ -262,9 +262,9 @@ combineCountSes <- function(countsSe, annotations){ return(countsMat) }) names(countsDataMat) = countsData - countsSe <- SummarizedExperiment(assays = SimpleList(counts = countsDataMat$counts, - CPM = countsDataMat$CPM, - fullLengthCounts = countsDataMat$fullLengthCounts, + countsSe <- SummarizedExperiment(assays = SimpleList(EM_counts = countsDataMat$counts, + EM_CPM = countsDataMat$CPM, + EM_fullLengthCounts = countsDataMat$fullLengthCounts, uniqueCounts = countsDataMat$uniqueCounts)) metadata(countsSe)$incompatibleCounts <- countsDataMat$incompatibleCounts rowRanges(countsSe) <- annotations From e6736bffdf243a570283951f1c148d77ed9fa049 Mon Sep 17 00:00:00 2001 From: Andre Date: Wed, 4 Sep 2024 17:17:51 +0800 Subject: [PATCH 127/189] undo EM counts naming --- R/bambu_utilityFunctions.R | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/R/bambu_utilityFunctions.R b/R/bambu_utilityFunctions.R index 65313318..e495126a 100644 --- a/R/bambu_utilityFunctions.R +++ b/R/bambu_utilityFunctions.R @@ -262,9 +262,9 @@ combineCountSes <- function(countsSe, annotations){ return(countsMat) }) names(countsDataMat) = countsData - countsSe <- SummarizedExperiment(assays = SimpleList(EM_counts = countsDataMat$counts, - EM_CPM = countsDataMat$CPM, - EM_fullLengthCounts = countsDataMat$fullLengthCounts, + countsSe <- SummarizedExperiment(assays = SimpleList(counts = countsDataMat$counts, + CPM = countsDataMat$CPM, + fullLengthCounts = countsDataMat$fullLengthCounts, uniqueCounts = countsDataMat$uniqueCounts)) metadata(countsSe)$incompatibleCounts <- countsDataMat$incompatibleCounts rowRanges(countsSe) <- annotations From fe42c0bcb9df0b2a836b31283cdf1b0834432e37 Mon Sep 17 00:00:00 2001 From: Andre Date: Wed, 4 Sep 2024 17:28:25 +0800 Subject: [PATCH 128/189] name sampleData with prefix --- R/readWrite.R | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/R/readWrite.R b/R/readWrite.R index 7cc5b783..48d79abf 100644 --- a/R/readWrite.R +++ b/R/readWrite.R @@ -31,7 +31,7 @@ writeBambuOutput <- function(se, path, prefix = "", seperateSamples = FALSE) { gtf <- writeToGTF(annotation = transcript_grList, file = transcript_gtffn) - utils::write.table(colData(se), file = paste0(outdir, "/sampleData.tsv"), + utils::write.table(colData(se), file = paste0(outdir, "/", prefix, "sampleData.tsv"), sep = "\t", quote = FALSE, row.names = FALSE, col.names = TRUE) for(d in names(assays(se))){ writeCountsOutput(se, varname=d, @@ -71,7 +71,7 @@ writeBambuOutput <- function(se, path, prefix = "", seperateSamples = FALSE) { Matrix::writeMM(estimates, estimatesfn) seGene <- transcriptToGeneExpression(se) writeCountsOutput(seGene, varname='counts', feature='gene',paste0(outdir, sampleName,"/"), prefix) - utils::write.table(colData(se), file = paste0(outdir, "/", sampleName, "/sampleData.tsv"), + utils::write.table(colData(se), file = paste0(outdir, "/", sampleName, "/", prefix, "sampleData.tsv"), sep = "\t", quote = FALSE, row.names = FALSE, col.names = TRUE) #utils::write.table(paste0(colnames(se), "-1"), file = paste0(outdir, "barcodes.tsv"), quote = FALSE, row.names = FALSE, col.names = FALSE) } From f5b5e1024d479199662ea234c6c7b4f5beb46f10 Mon Sep 17 00:00:00 2001 From: Andre Date: Fri, 20 Sep 2024 13:20:17 +0800 Subject: [PATCH 129/189] catch error when 0 or 1 genes have counts same error --- R/bambu-assignDist.R | 10 ++++++++-- 1 file changed, 8 insertions(+), 2 deletions(-) diff --git a/R/bambu-assignDist.R b/R/bambu-assignDist.R index 052622ce..abd334ea 100644 --- a/R/bambu-assignDist.R +++ b/R/bambu-assignDist.R @@ -19,7 +19,11 @@ assignReadClasstoTranscripts <- function(readClassList, annotations, isoreParame rowRanges = annotations, colData = ColData) colnames(quantData) = ColData$id - metadata(quantData)$incompatibleCounts = generateIncompatibleCounts(metadata(readClassList)$incompatibleCountMatrix, annotations) + if(sum(metadata(readClassList)$incompatibleCountMatrix)==0){ + metadata(quantData)$incompatibleCounts = NULL + } else{ + metadata(quantData)$incompatibleCounts = generateIncompatibleCounts(metadata(readClassList)$incompatibleCountMatrix, annotations) + } metadata(quantData)$nonuniqueCounts = generateNonUniqueCounts(readClassDt, metadata(readClassList)$countMatrix, annotations) metadata(quantData)$readClassDt = readClassDt metadata(quantData)$countMatrix = metadata(readClassList)$countMatrix @@ -60,9 +64,11 @@ generateNonUniqueCounts <- function(readClassDt, countMatrix, annotations){ #fuse multi align RCs by gene x = readClassDt %>% filter(multi_align & !is.na(eqClass.match)) x = x %>% distinct(eqClassId, .keep_all = TRUE) - nonuniqueCounts = countMatrix[x$eqClass.match,] + nonuniqueCounts = countMatrix[x$eqClass.match,, drop = FALSE] + if(nrow(x)>1){ nonuniqueCounts.gene = sparse.model.matrix(~ factor(x$gene_sid) - 1) nonuniqueCounts = t(nonuniqueCounts.gene) %*% nonuniqueCounts + } #covert ids into gene ids geneids = as.numeric(levels(factor(x$gene_sid))) geneids = x$txid[match(geneids, x$gene_sid)] From e9ecc7bdfeafad09fd2143e592bc282f8ea6f384 Mon Sep 17 00:00:00 2001 From: Andre Date: Fri, 4 Oct 2024 15:45:35 +0800 Subject: [PATCH 130/189] pass fusionmode to contruct read classes --- R/bambu-processReads.R | 11 ++++++++--- 1 file changed, 8 insertions(+), 3 deletions(-) diff --git a/R/bambu-processReads.R b/R/bambu-processReads.R index c8a0571b..8486a84e 100644 --- a/R/bambu-processReads.R +++ b/R/bambu-processReads.R @@ -295,7 +295,7 @@ constructReadClasses <- function(readGrgList, genomeSequence, annotations, warnings = c() ###TODO # construct read classes for each chromosome seperately se <- lowMemoryConstructReadClasses(readGrgList, genomeSequence, - annotations, stranded, verbose,"TODO") + annotations, stranded, verbose,"TODO", fusionMode) metadata(se)$warnings = warnings if(trackReads){ @@ -318,8 +318,13 @@ constructReadClasses <- function(readGrgList, genomeSequence, annotations, } lowMemoryConstructReadClasses <- function(readGrgList, genomeSequence, - annotations, stranded, verbose,bam.file){ - readGrgList = split(readGrgList, getChrFromGrList(readGrgList)) + annotations, stranded, verbose,bam.file, fusionMode = FALSE){ + if(fusionMode){ + readGrgList = list(readGrgList) + names(readGrgList) = c("fusion") + } else{ + readGrgList = split(readGrgList, getChrFromGrList(readGrgList)) + } se = lapply(names(readGrgList),FUN = function(i){ if(length(readGrgList[[i]]) == 0) return(NULL) # create error and strand corrected junction tables From 773d88cd51e10ec478edfbd21983196773d977fd Mon Sep 17 00:00:00 2001 From: Andre Date: Mon, 21 Oct 2024 11:21:52 +0800 Subject: [PATCH 131/189] Dont filter out reads that align up to the last nucleotide - fusions --- R/bambu-processReads.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/R/bambu-processReads.R b/R/bambu-processReads.R index 8486a84e..d64b2c68 100644 --- a/R/bambu-processReads.R +++ b/R/bambu-processReads.R @@ -162,7 +162,7 @@ bambu.processReadsByFile <- function(bam.file, genomeSequence, annotations, mcols(readGrgList)$id <- seq_along(readGrgList) } #removes reads that are outside genome coordinates - badReads = which(max(end(ranges(readGrgList)))>= + badReads = which(max(end(ranges(readGrgList)))> seqlengths(genomeSequence)[as.character(getChrFromGrList(readGrgList))]) if(length(badReads) > 0 ){ readGrgList = readGrgList[-badReads] From d181c8e45854e37dcc85735b13ed1cc1555b87bf Mon Sep 17 00:00:00 2001 From: Andre Date: Fri, 25 Oct 2024 11:14:02 +0800 Subject: [PATCH 132/189] Now will only combine SE read classes if min.txScore.singleExon < 1 --- R/bambu-extendAnnotations-utilityCombine.R | 18 +++++++++--------- 1 file changed, 9 insertions(+), 9 deletions(-) diff --git a/R/bambu-extendAnnotations-utilityCombine.R b/R/bambu-extendAnnotations-utilityCombine.R index 58ec1dfa..1bb7b8c8 100644 --- a/R/bambu-extendAnnotations-utilityCombine.R +++ b/R/bambu-extendAnnotations-utilityCombine.R @@ -21,15 +21,15 @@ isore.combineTranscriptCandidates <- function(readClassList, min.txScore.multiExon, min.txScore.singleExon, verbose) %>% data.table() message("finished combineSplicedTranscriptModels") combinedSplicedTranscripts[,confidenceType := "highConfidenceJunctionReads"] - return(combinedSplicedTranscripts) - # combinedUnsplicedTranscripts <- - # combineUnsplicedTranscriptModels(readClassList, bpParameters, - # stranded, min.readCount, min.readFractionByGene, - # min.txScore.multiExon, min.txScore.singleExon, verbose) %>% data.table() - # combinedUnsplicedTranscripts[, confidenceType := "unsplicedNew"] - # combinedTranscripts <- as_tibble(rbindlist(list(combinedSplicedTranscripts, - # combinedUnsplicedTranscripts), fill = TRUE)) - # return(combinedTranscripts) + if (min.txScore.singleExon < 1) {return(combinedSplicedTranscripts)} + combinedUnsplicedTranscripts <- + combineUnsplicedTranscriptModels(readClassList, bpParameters, + stranded, min.readCount, min.readFractionByGene, + min.txScore.multiExon, min.txScore.singleExon, verbose) %>% data.table() + combinedUnsplicedTranscripts[, confidenceType := "unsplicedNew"] + combinedTranscripts <- as_tibble(rbindlist(list(combinedSplicedTranscripts, + combinedUnsplicedTranscripts), fill = TRUE)) + return(combinedTranscripts) } From 77cae135bb57a6addd302c15d929c47cbb59a02a Mon Sep 17 00:00:00 2001 From: Andre Date: Fri, 25 Oct 2024 14:21:26 +0800 Subject: [PATCH 133/189] Update release history --- README.md | 11 +++++++++++ 1 file changed, 11 insertions(+) diff --git a/README.md b/README.md index d5b3b4da..c0aa3cd0 100755 --- a/README.md +++ b/README.md @@ -547,6 +547,17 @@ warnings - A list containing the warnings produced by each sample ### Release History +**bambu v3.3.0** + +Release date: 2023-October-25 + +Minor changes: + +- Fix crash cause by de novo mode +- Restore fusion mode functionality and added documentation +- Fixed bug in plot function +- Update release history + **bambu v3.2.5** Release date: 2023-July-07 From 9f888891db84595befca4f622099cd6dc3819411 Mon Sep 17 00:00:00 2001 From: Andre Date: Mon, 28 Oct 2024 10:18:49 +0800 Subject: [PATCH 134/189] Fix merge Combine the change to unspliced read mutating with the inclusion of sample id Fix bug during extendAnno where wrong variable was provided when determining the number of novel genes --- R/bambu-extendAnnotations-utilityExtend.R | 2 +- R/bambu-processReads_utilityConstructReadClasses.R | 8 +++----- 2 files changed, 4 insertions(+), 6 deletions(-) diff --git a/R/bambu-extendAnnotations-utilityExtend.R b/R/bambu-extendAnnotations-utilityExtend.R index 615ab3a8..cbdddcb6 100644 --- a/R/bambu-extendAnnotations-utilityExtend.R +++ b/R/bambu-extendAnnotations-utilityExtend.R @@ -44,7 +44,7 @@ isore.extendAnnotations <- function(combinedTranscripts, annotationGrangesList, rowDataCombined, annotationGrangesList, exonRangesCombined, prefix, remove.subsetTx, min.readFractionByEqClass, baselineFDR, NDR, defaultModels, verbose) message(paste0("Novel transcripts detected: ", sum(mcols(extendedAnnotationRanges)$novelTranscript))) - message(paste0("Novel genes detected: ", length(unique(mcols(se)$GENEID[mcols(se)$novelGene])))) + message(paste0("Novel genes detected: ", length(unique(mcols(extendedAnnotationRanges)$GENEID[mcols(extendedAnnotationRanges)$novelGene])))) message(paste0("Low confidence transcripts excluded: ", length(metadata(extendedAnnotationRanges)$lowConfidenceTranscripts))) return(extendedAnnotationRanges) } else { diff --git a/R/bambu-processReads_utilityConstructReadClasses.R b/R/bambu-processReads_utilityConstructReadClasses.R index 6717c7af..fec9adbf 100644 --- a/R/bambu-processReads_utilityConstructReadClasses.R +++ b/R/bambu-processReads_utilityConstructReadClasses.R @@ -251,13 +251,11 @@ constructUnsplicedReadClasses <- function(reads.singleExon, annotations, mutate(id = mcols(reads.singleExon)$id, sampleID = mcols(reads.singleExon)$sampleID) %>% group_by(seqnames,start,end,strand) %>% - mutate(n=n(), id = list(id)) %>% # change summarise to mutate as summarise will reorder the table + mutate(counts=n(), id = list(id), sampleID = list(sampleID)) %>% ungroup() %>% - summarise(counts=n(), id = list(id), sampleID = list(sampleID)) %>% as.data.frame() - mcols(reads.singleExon)$counts <- counts$n - mcols(reads.singleExon)$id <- counts$id - reads.singleExon = unique(reads.singleExon) + reads.singleExon = GRanges(counts) + reads.singleExon = unique(reads.singleExon) rcUnsplicedAnnotation <- getUnsplicedReadClassByReference( granges = reads.singleExon, grangesReference = referenceExons, From e133c43fba9e7de2478fec98100c3a5e4a01c499 Mon Sep 17 00:00:00 2001 From: Andre Date: Mon, 28 Oct 2024 10:46:49 +0800 Subject: [PATCH 135/189] Refactor quantData input parameter and colData when not multiplexed --- R/bambu.R | 28 ++++++++++++++-------------- R/bambu_utilityFunctions.R | 2 +- 2 files changed, 15 insertions(+), 15 deletions(-) diff --git a/R/bambu.R b/R/bambu.R index 31a08174..68e6ae4a 100644 --- a/R/bambu.R +++ b/R/bambu.R @@ -192,11 +192,11 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, message("--- Start calculating equivilance classes ---") if (is.character(readClassList)) readClassList <- readRDS(file = readClassList) #if(is.list(readClassList)) readClassList = readClassList[[1]] - quantDatas = bplapply(readClassList, FUN = assignReadClasstoTranscripts, + quantData = bplapply(readClassList, FUN = assignReadClasstoTranscripts, annotations = annotations, isoreParameters = isoreParameters, verbose = verbose, demultiplexed = demultiplexed, spatial = spatial, BPPARAM = bpParameters) - if (!quant) return(quantDatas) + if (!quant) return(quantData) } if (quant) { @@ -207,22 +207,22 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, defaultModels2 = isoreParameters[["defaultModels"]]) if(length(annotations)==0) stop("No valid annotations, if running de novo please try less stringent parameters") - if(is.null(quantDatas)) stop("quantData must be provided or assignDist = TRUE") + if(is.null(quantData)) stop("quantData must be provided or assignDist = TRUE") GENEIDs.i = as.numeric(factor(unique(mcols(annotations)$GENEID))) start.ptm <- proc.time() countsSeCompressed.all = NULL ColNames = c() - for(i in seq_along(quantDatas)){ - quantData = quantDatas[[i]] + for(i in seq_along(quantData)){ + quantData_i = quantData[[i]] #load in the barcode clustering from file if provided - iter = seq_len(ncol(metadata(quantData)$countMatrix)) + iter = seq_len(ncol(metadata(quantData_i)$countMatrix)) if(!is.null(clusters)){ if(!is.list(clusters)){ clusterMaps = NULL - for(j in seq_along(metadata(quantData)$sampleNames)){ #load in a file per sample name provided + for(j in seq_along(metadata(quantData_i)$sampleNames)){ #load in a file per sample name provided clusterMap = read.table(clusters[[j]], sep = ifelse(grepl(".tsv$",clusters[[j]]), "\t", ","), header = FALSE) - clusterMap[,1] = paste0(metadata(quantData)$sampleNames[j],"_",clusterMap[,1]) + clusterMap[,1] = paste0(metadata(quantData_i)$sampleNames[j],"_",clusterMap[,1]) clusterMaps = rbind(clusterMaps, clusterMap) } clustering = splitAsList(clusterMaps[,1], clusterMaps[,2]) @@ -236,14 +236,14 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, } } countsSeCompressed <- bplapply(iter, FUN = function(i){ - countMatrix = unname(metadata(quantData)$countMatrix[,i]) - incompatibleCountMatrix = unname(metadata(quantData)$incompatibleCountMatrix[,i]) + countMatrix = unname(metadata(quantData_i)$countMatrix[,i]) + incompatibleCountMatrix = unname(metadata(quantData_i)$incompatibleCountMatrix[,i]) if(!is.null(dim(countMatrix))){ countMatrix = rowSums(countMatrix) - incompatibleCountMatrix = rowSums(metadata(quantData)$incompatibleCountMatrix[,i]) + incompatibleCountMatrix = rowSums(metadata(quantData_i)$incompatibleCountMatrix[,i]) } - return(bambu.quantify(readClassDt = metadata(quantData)$readClassDt, countMatrix = countMatrix, - incompatibleCountMatrix = data.table(GENEID.i = as.numeric(rownames(metadata(quantData)$incompatibleCountMatrix)), counts = incompatibleCountMatrix), + return(bambu.quantify(readClassDt = metadata(quantData_i)$readClassDt, countMatrix = countMatrix, + incompatibleCountMatrix = data.table(GENEID.i = as.numeric(rownames(metadata(quantData_i)$incompatibleCountMatrix)), counts = incompatibleCountMatrix), txid.index = mcols(annotations)$txid, GENEIDs = GENEIDs.i, isoreParameters = isoreParameters, emParameters = emParameters, trackReads = trackReads, returnDistTable = returnDistTable, verbose = verbose))}, @@ -253,7 +253,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL, if(!is.null(clusters)){ ColNames = c(ColNames, names(iter)) } else{ - ColNames = c(ColNames, colnames(quantData)) + ColNames = c(ColNames, colnames(quantData_i)) } countsSeCompressed.all = c(countsSeCompressed.all, countsSeCompressed) } diff --git a/R/bambu_utilityFunctions.R b/R/bambu_utilityFunctions.R index 1c3051c2..932a7bcb 100644 --- a/R/bambu_utilityFunctions.R +++ b/R/bambu_utilityFunctions.R @@ -274,7 +274,7 @@ combineCountSes <- function(countsSe, annotations){ #' Generate the coldata for se options using colnames, and other option inputs #' @noRd generateColData <- function(sampleNames, clusters, demultiplexed, spatial){ - ColData = DataFrame(sampleName = sampleNames) + ColData = DataFrame(id = sampleNames) if(demultiplexed & is.null(clusters)){ ColData = DataFrame(id = sampleNames, sampleName = gsub("_[^_]+$","", sampleNames, perl = TRUE), From 23e02121ef778c8be3bc39a6ca7ca5f9ab40d54d Mon Sep 17 00:00:00 2001 From: Chen Ying Date: Mon, 28 Oct 2024 10:54:54 +0800 Subject: [PATCH 136/189] update actions versions --- .github/workflows/check-bioc.yml | 18 +++++++++--------- .github/workflows/lint.yaml | 2 +- .github/workflows/pr-commands.yaml | 4 ++-- .github/workflows/test-coverage.yaml | 2 +- 4 files changed, 13 insertions(+), 13 deletions(-) diff --git a/.github/workflows/check-bioc.yml b/.github/workflows/check-bioc.yml index 5927ff7e..6263b116 100644 --- a/.github/workflows/check-bioc.yml +++ b/.github/workflows/check-bioc.yml @@ -40,7 +40,7 @@ env: run_covr: 'false' run_pkgdown: 'false' has_RUnit: 'false' - cache-version: 'cache-v3' + cache-version: 'cache-v4' run_docker: 'false' jobs: @@ -54,9 +54,9 @@ jobs: fail-fast: false matrix: config: - - { os: ubuntu-latest, r: '4.3', bioc: '3.18', cont: "bioconductor/bioconductor_docker:RELEASE_3_18", rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest" } - - { os: macOS-latest, r: '4.3', bioc: '3.18'} - ##- { os: windows-latest, r: '4.3', bioc: '3.18'} + - { os: ubuntu-latest, r: '4.4', bioc: '3.19', cont: "bioconductor/bioconductor_docker:RELEASE_3_19", rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest" } + - { os: macOS-latest, r: '4.4', bioc: '3.19'} + - { os: windows-latest, r: '4.4', bioc: '3.19'} ## Check https://github.com/r-lib/actions/tree/master/examples ## for examples using the http-user-agent env: @@ -81,7 +81,7 @@ jobs: ## https://github.com/r-lib/actions/blob/master/examples/check-standard.yaml ## If they update their steps, we will also need to update ours. - name: Checkout Repository - uses: actions/checkout@v3 + uses: actions/checkout@v4 ## R is already included in the Bioconductor docker images - name: Setup R from r-lib @@ -104,7 +104,7 @@ jobs: - name: Restore R package cache if: "!contains(github.event.head_commit.message, '/nocache') && runner.os != 'Linux'" - uses: actions/cache@v3 + uses: actions/cache@v4 with: path: ${{ env.R_LIBS_USER }} key: ${{ env.cache-version }}-${{ runner.os }}-biocversion-RELEASE-r-4.3-${{ hashFiles('.github/depends.Rds') }} @@ -112,7 +112,7 @@ jobs: - name: Cache R packages on Linux if: "!contains(github.event.head_commit.message, '/nocache') && runner.os == 'Linux' " - uses: actions/cache@v3 + uses: actions/cache@v4 with: path: /home/runner/work/_temp/Library key: ${{ env.cache-version }}-${{ runner.os }}-biocversion-devel-r-4.3-${{ hashFiles('.github/depends.Rds') }} @@ -337,9 +337,9 @@ jobs: - name: Upload check results if: failure() - uses: actions/upload-artifact@v2 + uses: actions/upload-artifact@v4 with: - name: ${{ runner.os }}-biocversion-RELEASE-r-4.3-results + name: ${{ runner.os }}-biocversion-RELEASE-r-4.4-results path: check - uses: docker/build-push-action@v1 diff --git a/.github/workflows/lint.yaml b/.github/workflows/lint.yaml index 9daaa663..aa29e0f1 100644 --- a/.github/workflows/lint.yaml +++ b/.github/workflows/lint.yaml @@ -15,7 +15,7 @@ jobs: env: GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }} steps: - - uses: actions/checkout@v2 + - uses: actions/checkout@v4 - uses: r-lib/actions/setup-r@v2 with: diff --git a/.github/workflows/pr-commands.yaml b/.github/workflows/pr-commands.yaml index 98ca228b..35d14666 100644 --- a/.github/workflows/pr-commands.yaml +++ b/.github/workflows/pr-commands.yaml @@ -14,7 +14,7 @@ jobs: env: GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }} steps: - - uses: actions/checkout@v2 + - uses: actions/checkout@v4 - uses: r-lib/actions/pr-fetch@v2 with: @@ -49,7 +49,7 @@ jobs: env: GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }} steps: - - uses: actions/checkout@v2 + - uses: actions/checkout@v4 - uses: r-lib/actions/pr-fetch@v2 with: diff --git a/.github/workflows/test-coverage.yaml b/.github/workflows/test-coverage.yaml index a1b6e36e..58383454 100644 --- a/.github/workflows/test-coverage.yaml +++ b/.github/workflows/test-coverage.yaml @@ -16,7 +16,7 @@ jobs: GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }} steps: - - uses: actions/checkout@v3 + - uses: actions/checkout@v4 - uses: r-lib/actions/setup-r@v2 with: From c537224d88420db370b781bde6593409c334fe18 Mon Sep 17 00:00:00 2001 From: Andre Date: Mon, 28 Oct 2024 11:15:32 +0800 Subject: [PATCH 137/189] Restore seperateSamples argument in writeBambuOutput lost in merge --- R/readWrite.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/R/readWrite.R b/R/readWrite.R index f867093b..9574a63d 100644 --- a/R/readWrite.R +++ b/R/readWrite.R @@ -17,7 +17,7 @@ #' path <- tempdir() #' writeBambuOutput(se, path) writeBambuOutput <- function(se, path, prefix = "", outputExtendedAnno = TRUE, - outputAll = TRUE, outputBambuModels = TRUE, outputNovelOnly = TRUE) { + outputAll = TRUE, outputBambuModels = TRUE, outputNovelOnly = TRUE, seperateSamples = FALSE) { if (missing(se) | missing(path)) { stop("Both summarizedExperiment object from bambu and the path for the output files are required.") From 0024c5fc7ba96cc8b499b733030d93e4a1da0d73 Mon Sep 17 00:00:00 2001 From: Andre Date: Mon, 28 Oct 2024 13:17:29 +0800 Subject: [PATCH 138/189] Put gtf file extension at the end of writeBambuOutput --- R/readWrite.R | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/R/readWrite.R b/R/readWrite.R index 9574a63d..81dfa80e 100644 --- a/R/readWrite.R +++ b/R/readWrite.R @@ -28,7 +28,7 @@ writeBambuOutput <- function(se, path, prefix = "", outputExtendedAnno = TRUE, transcript_grList <- rowRanges(se) transcript_gtffn <- paste(outdir, prefix, - "extended_annotations.gtf", sep = "") + "extended_annotations", sep = "") gtf <- writeAnnotationsToGTF(annotation = transcript_grList, file = transcript_gtffn, outputExtendedAnno = TRUE, outputAll = TRUE, outputBambuModels = TRUE, outputNovelOnly = TRUE) @@ -231,24 +231,24 @@ writeToGTF <- function(annotation, file, geneIDs = NULL) { writeAnnotationsToGTF <- function(annotation, file, geneIDs = NULL, outputExtendedAnno = TRUE, outputAll = TRUE, outputBambuModels = TRUE, outputNovelOnly = TRUE){ if(outputExtendedAnno){ - writeToGTF(annotation, paste0(file, "_extendedAnnotations"), geneIDs) + writeToGTF(annotation, paste0(file, "_extendedAnnotations.gtf"), geneIDs) } if(outputAll){ annotationAll = setNDR(annotation, 1) if(length(annotationAll) == length(annotation)) message("The current NDR threshold already outputs all transcript models. This may result in reduced precision for th extendedAnnotations and supportedTranscriptModels gtfs") - writeToGTF(annotationAll, paste0(file, "_allTranscriptModels"), geneIDs) + writeToGTF(annotationAll, paste0(file, "_allTranscriptModels.gtf"), geneIDs) } #todo - have this write bambu start and ends for annotated transcripts if(outputBambuModels){ annotationBambu = annotation[!is.na(mcols(annotation)$readCount)] - writeToGTF(annotationBambu, paste0(file, "_supportedTranscriptModels"), geneIDs) + writeToGTF(annotationBambu, paste0(file, "_supportedTranscriptModels.gtf"), geneIDs) } if(outputNovelOnly){ annotationNovel = annotation[mcols(annotation)$novelTranscript] - writeToGTF(annotationBambu, paste0(file, "_novelTranscripts"), geneIDs) + writeToGTF(annotationBambu, paste0(file, "_novelTranscripts.gtf"), geneIDs) } } From 51f382eec0457826dbeeafa4575c9728128acb4e Mon Sep 17 00:00:00 2001 From: Andre Date: Mon, 28 Oct 2024 13:49:25 +0800 Subject: [PATCH 139/189] Add the flags in writeBambuOutput to control which gtfs are written --- R/readWrite.R | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/R/readWrite.R b/R/readWrite.R index 81dfa80e..711221d6 100644 --- a/R/readWrite.R +++ b/R/readWrite.R @@ -30,8 +30,8 @@ writeBambuOutput <- function(se, path, prefix = "", outputExtendedAnno = TRUE, transcript_gtffn <- paste(outdir, prefix, "extended_annotations", sep = "") gtf <- writeAnnotationsToGTF(annotation = transcript_grList, - file = transcript_gtffn, outputExtendedAnno = TRUE, - outputAll = TRUE, outputBambuModels = TRUE, outputNovelOnly = TRUE) + file = transcript_gtffn, outputExtendedAnno = outputExtendedAnno, + outputAll = outputAll, outputBambuModels = outputBambuModels, outputNovelOnly = outputNovelOnly) utils::write.table(colData(se), file = paste0(outdir, "/", prefix, "sampleData.tsv"), sep = "\t", quote = FALSE, row.names = FALSE, col.names = TRUE) From d10f86a642027085c414f75d697b50905b873242 Mon Sep 17 00:00:00 2001 From: Andre Date: Mon, 28 Oct 2024 17:05:48 +0800 Subject: [PATCH 140/189] Update release history --- README.md | 24 ++++++++++++++++++++++++ 1 file changed, 24 insertions(+) diff --git a/README.md b/README.md index c0aa3cd0..258f4970 100755 --- a/README.md +++ b/README.md @@ -549,6 +549,30 @@ warnings - A list containing the warnings produced by each sample **bambu v3.3.0** +Release date: 2024-October-28 + +- Subset transcripts and those above the NDR threshold are placed into the metadata of the annotations in $subsetTranscripts and $lowConfidenceTranscripts respectively (when filtered out by default). +- adds the setNDR function +- outputs the NDR, txScore and txScore.noFit as attributes to the gtf file and these are also read in with prepareAnnotations. +- Added setNDR as part of quant, which means that users can provide their extendedAnnotations alongside an NDR threshold when running bambu and it will automatically adjust the NDR used for quant. This means users do not need to manually filter the NDR value themselves. +- NDR and other stats are now copied over to equal transcripts even if above the NDR threshold (previously only happened for those below the NDR threshold) +- Read class to transcript assignment is now its own step instead of being done with quant. This is turned on and off with assignDist. +- Added demultiplexed argument +- Added spatial argument +- Added sampleNames argument +- Added cleanReads argument +- Added dedupUMI argument +- Added clsuters argument +- Updated lowMemory. The previous lowMemory mode is now always on. The new lowMemory mode is the current implementation, otherwise it will read in all bam files and process them together. +- Added importBambuResults +- writeBambuOutput now outputs all information needed to import Bambu results from text files +- Count outputs are all now in sparse matrix format + +Minor changes: +- Warnings will no longer occur if there are seqlevels in the readGrgList that are not in the annotations or genome. This was done by setting seqlevels of the reads to only those in the reads. Warning was constantly occuring because all the scaffolds used in alignment were in the bam files, even if no reads from these scaffolds existed. + +**bambu v3.2.6** + Release date: 2023-October-25 Minor changes: From 38cb0527f7a9076f9bf716e2c1991edeaae23385 Mon Sep 17 00:00:00 2001 From: Andre Date: Tue, 29 Oct 2024 13:44:25 +0800 Subject: [PATCH 141/189] Update xgboost models and include code to redo it --- R/bambu-extendAnnotations-utilityCombine.R | 2 - ...processReads_utilityCreateJunctionTables.R | 4 +- ...cessReads_utilityJunctionErrorCorrection.R | 3 +- R/sysdata.rda | Bin 316013 -> 304427 bytes data-raw/DATASET.R | 25 +++++------- data-raw/update_xgboost_models.R | 36 ++++++++++++++++++ inst/extdata/defaultModels.rds | Bin 603 -> 2391 bytes inst/extdata/read_class_ME.model | Bin 171386 -> 175994 bytes inst/extdata/read_class_SE.model | Bin 157274 -> 156482 bytes .../extdata/spliceSitePredictionEnd.end.model | Bin 0 -> 109970 bytes .../spliceSitePredictionEnd.start.model | Bin 0 -> 113786 bytes .../spliceSitePredictionStart.end.model | Bin 0 -> 111626 bytes .../spliceSitePredictionStart.start.model | Bin 0 -> 100898 bytes inst/extdata/standardJunctionModels_temp.txt | Bin 204774 -> 0 bytes 14 files changed, 49 insertions(+), 21 deletions(-) create mode 100644 data-raw/update_xgboost_models.R create mode 100644 inst/extdata/spliceSitePredictionEnd.end.model create mode 100644 inst/extdata/spliceSitePredictionEnd.start.model create mode 100644 inst/extdata/spliceSitePredictionStart.end.model create mode 100644 inst/extdata/spliceSitePredictionStart.start.model delete mode 100644 inst/extdata/standardJunctionModels_temp.txt diff --git a/R/bambu-extendAnnotations-utilityCombine.R b/R/bambu-extendAnnotations-utilityCombine.R index 1bb7b8c8..dc58b69e 100644 --- a/R/bambu-extendAnnotations-utilityCombine.R +++ b/R/bambu-extendAnnotations-utilityCombine.R @@ -14,12 +14,10 @@ isore.combineTranscriptCandidates <- function(readClassList, stranded, ## stranded used for unspliced reduce min.readCount , min.readFractionByGene, min.txScore.multiExon, min.txScore.singleExon, bpParameters ,verbose){ - message("starting combineSplicedTranscriptModels") combinedSplicedTranscripts <- combineSplicedTranscriptModels(readClassList, bpParameters, min.readCount, min.readFractionByGene, min.txScore.multiExon, min.txScore.singleExon, verbose) %>% data.table() - message("finished combineSplicedTranscriptModels") combinedSplicedTranscripts[,confidenceType := "highConfidenceJunctionReads"] if (min.txScore.singleExon < 1) {return(combinedSplicedTranscripts)} combinedUnsplicedTranscripts <- diff --git a/R/bambu-processReads_utilityCreateJunctionTables.R b/R/bambu-processReads_utilityCreateJunctionTables.R index 1c3b4dd0..44fefe69 100644 --- a/R/bambu-processReads_utilityCreateJunctionTables.R +++ b/R/bambu-processReads_utilityCreateJunctionTables.R @@ -9,7 +9,7 @@ #' @importFrom dplyr tibble %>% mutate select #' @noRd isore.constructJunctionTables <- function(unlisted_junctions, annotations, - genomeSequence, stranded = FALSE, verbose = FALSE) { + genomeSequence, stranded = FALSE, verbose = FALSE, returnModel = FALSE) { start.ptm <- proc.time() if(length(unlisted_junctions)==0) return(NULL) #summarise junction counts and strand for all reads @@ -35,7 +35,7 @@ isore.constructJunctionTables <- function(unlisted_junctions, annotations, junctionEndName, startScore, endScore, id, annotatedJunction, annotatedStart, annotatedEnd) # correct junction coordinates using logistic regression classifier - uniqueJunctions <- junctionErrorCorrection(uniqueJunctions, verbose) + uniqueJunctions <- junctionErrorCorrection(uniqueJunctions, verbose, returnModel) return(uniqueJunctions) } diff --git a/R/bambu-processReads_utilityJunctionErrorCorrection.R b/R/bambu-processReads_utilityJunctionErrorCorrection.R index c2683cdc..9b09b50c 100644 --- a/R/bambu-processReads_utilityJunctionErrorCorrection.R +++ b/R/bambu-processReads_utilityJunctionErrorCorrection.R @@ -2,7 +2,7 @@ #' @param uniqueJunctions uniqueJunctions #' @param verbose verbose #' @noRd -junctionErrorCorrection <- function(uniqueJunctions, verbose) { +junctionErrorCorrection <- function(uniqueJunctions, verbose, returnModel = TRUE) { start.ptm <- proc.time() if (sum(uniqueJunctions$annotatedJunction) > 5000 & sum(!uniqueJunctions$annotatedJunction) > 4000) { @@ -37,6 +37,7 @@ junctionErrorCorrection <- function(uniqueJunctions, verbose) { if (verbose) message("Finished correcting junction based on set of high confidence ", "junctions in ", round((end.ptm - start.ptm)[3] / 60, 1), " mins.") + if(returnModel) {metadata(uniqueJunctions)$junctionModel = junctionModel} return(uniqueJunctions) } diff --git a/R/sysdata.rda b/R/sysdata.rda index 1cbb949f7cb7814c3546b6b1fe22ba77e266b0bb..687f76bdede24705258d7595080b4557aba07d57 100755 GIT binary patch literal 304427 zcmagF2UJr*+b){WyC9*3B3(d0N&# z7y@SjlmcYo*>GkWCR{i)0FgQGp2H*W 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zGE|)6&DGDyCzJ~Uhv+IZAM);s_0k#Pn&qcK@f|<6^$=OoggpPEz8H>(IAk!KLx5{`}8e%n7}joNgwSS$c&`HO}+?4+i)SCIA2c diff --git a/data-raw/DATASET.R b/data-raw/DATASET.R index df6b4616..f62d05ec 100755 --- a/data-raw/DATASET.R +++ b/data-raw/DATASET.R @@ -102,24 +102,17 @@ seCombinedGeneExpected <- transcriptToGeneExpression(seCombined) seCombinedExtendedGeneExpected <- transcriptToGeneExpression(seCombinedExtended) -## prior models to use for scoreReadClass() -#se = readRDS("SGNex_HepG2_directRNA_replicate5_run1_genome.rds") -#defaultModels = trainBambu(se) -xgb.save(defaultModels$transcriptModelME, "./inst/extdata/read_class_ME.model") -xgb.save(defaultModels$transcriptModelSE, "./inst/extdata/read_class_SE.model") -defaultModels$transcriptModelME = NULL -defaultModels$transcriptModelSE = NULL -#saveRDS(defaultModels, "./inst/extdata/defaultModels.rds") -defaultModels = readRDS(system.file("extdata", "defaultModels.rds", - package = "bambu")) +## prior models to use for scoreReadClass() and junctions() +##to train new ones see update_xgboost_models.R +defaultModels = list() defaultModels$transcriptModelME = xgb.load("./inst/extdata/read_class_ME.model") -defaultModels$transcriptModelSE = xgb.load("./inst/extdata/read_class_SE.model") +defaultModels$transcriptModelSE = xgb.load("./inst/extdata/read_class_SE.model") -# How to get pre trained junction model standardJunctionModels_temp -# added "saveRDS(junctionModel, "./inst/extdata/standardJunctionModels_temp.txt")" to junctionErrorCorrection -# ran Bambu with GNex_HepG2_directRNA_replicate5_run1_genome -standardJunctionModels_temp = readRDS(system.file( - "extdata", "standardJunctionModels_temp.txt", package = "bambu")) +standardJunctionModels_temp = list() +standardJunctionModels_temp$spliceSitePredictionStart.start = xgb.load("./inst/extdata/spliceSitePredictionStart.start.model") +standardJunctionModels_temp$spliceSitePredictionStart.end = xgb.load("./inst/extdata/spliceSitePredictionStart.end.model") +standardJunctionModels_temp$spliceSitePredictionEnd.start = xgb.load("./inst/extdata/spliceSitePredictionEnd.start.model") +standardJunctionModels_temp$spliceSitePredictionEnd.end = xgb.load("./inst/extdata/spliceSitePredictionEnd.end.model") usethis::use_data(data1, data2, data3, data4, data5, estOutput_woBC, diff --git a/data-raw/update_xgboost_models.R b/data-raw/update_xgboost_models.R new file mode 100644 index 00000000..fa4c5851 --- /dev/null +++ b/data-raw/update_xgboost_models.R @@ -0,0 +1,36 @@ +#download the bam file and make sure you set your own paths for the reference annotations +#change to bambu directory so that outputs are correct + +#aws s3 cp --no-sign-request s3://sg-nex-data/data/sequencing_data_ont/bam/genome/SGNex_HepG2_directRNA_replicate5_run1/SGNex_HepG2_directRNA_replicate5_run1.bam + + +devtools::load_all("bambu") +annotations = readRDS("Homo_sapiens.GRCh38.91.sorted.rds") +fa.file = "hg38_sequins_SIRV_ERCCs_longSIRVs.fa" +sample = "SGNex_HepG2_directRNA_replicate5_run1.bam" + +#Get transcript discovery model +rcf <- bambu(reads = sample, annotations = annotations, genome = fa.file, discovery = FALSE, assignDist = FALSE, quant = FALSE, verbose = TRUE) + +defaultModels = trainBambu(rcf[[1]]) +xgb.save(defaultModels$transcriptModelME, "./inst/extdata/read_class_ME.model") +xgb.save(defaultModels$transcriptModelSE, "./inst/extdata/read_class_SE.model") +defaultModels$transcriptModelME = NULL +defaultModels$transcriptModelSE = NULL +saveRDS(defaultModels, "./inst/extdata/defaultModels.rds") + + +#Get junction model +readGrgList = prepareDataFromBam(sample, verbose = TRUE) +genomeSequence <- checkInputSequence(fa.file) +mcols(readGrgList)$id <- seq_along(readGrgList) +unlisted_junctions <- unlistIntrons(readGrgList, use.ids = TRUE) +uniqueJunctions <- isore.constructJunctionTables(unlisted_junctions, + annotations,genomeSequence, + stranded = FALSE, verbose = TRUE, + returnModel = TRUE) +junctionModel = 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From c1ab8afe9fec2fd16b525298960cf20f9d21120d Mon Sep 17 00:00:00 2001
From: Andre 
Date: Tue, 29 Oct 2024 14:25:20 +0800
Subject: [PATCH 142/189] Update quant test data due to assigndist changes

---
 R/bambu-quantify.R                  | 32 ++++++++++++++---------------
 R/bambu-quantify_utilityFunctions.R |  1 +
 data-raw/DATASET.R                  | 17 +++++++++------
 3 files changed, 28 insertions(+), 22 deletions(-)

diff --git a/R/bambu-quantify.R b/R/bambu-quantify.R
index 4b125b8b..d996c189 100644
--- a/R/bambu-quantify.R
+++ b/R/bambu-quantify.R
@@ -31,25 +31,25 @@ bambu.quantify <- function(readClassDt, countMatrix, incompatibleCountMatrix, tx
 bambu.quantDT <- function(readClassDt = readClassDt, 
                           emParameters = list(degradationBias = TRUE, maxiter = 10000, conv = 10^(-2),
                                               minvalue = 10^(-8)), ncore = 1, verbose = FALSE) {
-  rcPreOut <- addAval(readClassDt, emParameters, verbose)
-  readClassDt <- rcPreOut[[1]]
-  outIni <- initialiseOutput(readClassDt)
-  readClassDt <- filterTxRc(readClassDt) 
-  readClassDt <- assignGroups(readClassDt)
-  inputRcDt <- getInputList(readClassDt)
-  readClassDt <- split(readClassDt, by = "gene_grp_id")
-  start.ptm <- proc.time()
-  outEst <- abundance_quantification(inputRcDt, readClassDt,
+    rcPreOut <- addAval(readClassDt, emParameters, verbose)
+    readClassDt <- rcPreOut[[1]]
+    outIni <- initialiseOutput(readClassDt)
+    readClassDt <- filterTxRc(readClassDt) 
+    readClassDt <- assignGroups(readClassDt)
+    inputRcDt <- getInputList(readClassDt)
+    readClassDt <- split(readClassDt, by = "gene_grp_id")
+    start.ptm <- proc.time()
+    outEst <- abundance_quantification(inputRcDt, readClassDt,
                                      maxiter = emParameters[["maxiter"]],
                                      conv = emParameters[["conv"]], minvalue = emParameters[["minvalue"]])
-  end.ptm <- proc.time()
-  if (verbose) message("Finished EM estimation in ",
-                       round((end.ptm - start.ptm)[3] / 60, 1), " mins.")
-  outEst <- modifyQuantOut(outEst,outIni)
-  theta_est <- rbind(rcPreOut[[2]],outEst)
-  theta_est <- removeDuplicates(theta_est)
     end.ptm <- proc.time()
-   return(theta_est)
+    if (verbose) message("Finished EM estimation in ",
+                        round((end.ptm - start.ptm)[3] / 60, 1), " mins.")
+    outEst <- modifyQuantOut(outEst,outIni)
+    theta_est <- rbind(rcPreOut[[2]],outEst)
+    theta_est <- removeDuplicates(theta_est)
+    end.ptm <- proc.time()
+    return(theta_est)
 }
 
 
diff --git a/R/bambu-quantify_utilityFunctions.R b/R/bambu-quantify_utilityFunctions.R
index 0751e4ae..98fd0b21 100644
--- a/R/bambu-quantify_utilityFunctions.R
+++ b/R/bambu-quantify_utilityFunctions.R
@@ -205,6 +205,7 @@ addAval <- function(readClassDt, emParameters, verbose){
                                                     d_rateOut[1], d_mode = d_mode)
   }else{
     d_rateOut <- rep(NA,2)
+    readClassDt$aval = 1
   }
   end.ptm <- proc.time()
   if (verbose) message("Finished estimate degradation bias in ",
diff --git a/data-raw/DATASET.R b/data-raw/DATASET.R
index f62d05ec..161f6540 100755
--- a/data-raw/DATASET.R
+++ b/data-raw/DATASET.R
@@ -23,7 +23,8 @@ data1 <- data.table(
     txlen = c(546,546,2356,2356),
     rcWidth = c(300,540,1800,2300),
     minRC = rep(1,4),
-    GENEID = 1
+    gene_sid = 1,
+    multi_align = c(FALSE, FALSE, FALSE, FALSE)
 )
 
 data2 <- data.table(
@@ -35,7 +36,8 @@ data2 <- data.table(
     txlen = c(546,546,2356,2356, 546,2356),
     rcWidth = c(300,540,1800,2300, 200, 200),
     minRC = rep(1,6),
-    GENEID = 2
+    gene_sid = 2,
+    multi_align = c(FALSE, FALSE, FALSE, FALSE, TRUE, TRUE)
 )
 
 data3 <- data.table(
@@ -47,7 +49,8 @@ data3 <- data.table(
     txlen = c(546,546,2356,2356,2356, 546,2356),
     rcWidth = c(540,540,540,1800,2300, 200, 200),
     minRC = c(NA,NA,1,1,1,NA,1),
-    GENEID = 3
+    gene_sid = 3,
+    multi_align = c(TRUE, TRUE, TRUE, FALSE, FALSE, TRUE, TRUE)
 )
 
 data4 <- data.table(
@@ -59,7 +62,8 @@ data4 <- data.table(
     txlen = c(546,546,2356,2356,2356, 546,2356),
     rcWidth = c(540,540,540,1800,2300, 200, 200),
     minRC = c(NA,NA,1,1,1,NA,1),
-    GENEID = 4
+    gene_sid = 4,
+    multi_align = c(TRUE, TRUE, TRUE, FALSE, FALSE, TRUE, TRUE)
 )
 
 data5 <- data.table(
@@ -71,7 +75,8 @@ data5 <- data.table(
     txlen = c(546,546,2356,2356, 546,2356),
     rcWidth = c(1700,2200,1800,2300, 2000, 2000),
     minRC = rep(1,6),
-    GENEID = 5
+    gene_sid = 5,
+    multi_align = c(FALSE, FALSE, FALSE, FALSE, TRUE, TRUE)
 )
 
 
@@ -104,7 +109,7 @@ seCombinedExtendedGeneExpected <- transcriptToGeneExpression(seCombinedExtended)
 
 ## prior models to use for scoreReadClass() and junctions()
 ##to train new ones see update_xgboost_models.R
-defaultModels = list()
+defaultModels = readRDS("./inst/extdata/defaultModels.rds")
 defaultModels$transcriptModelME = xgb.load("./inst/extdata/read_class_ME.model")
 defaultModels$transcriptModelSE = xgb.load("./inst/extdata/read_class_SE.model")  
 

From 5515c435ed5e97b7cb44ed7fbaec79c9992b98b4 Mon Sep 17 00:00:00 2001
From: Andre 
Date: Tue, 29 Oct 2024 14:51:57 +0800
Subject: [PATCH 143/189] Update remaining test data

---
 R/bambu.R                                     |   2 +-
 R/sysdata.rda                                 | Bin 304427 -> 304319 bytes
 data-raw/DATASET.R                            |   4 ++--
 ...rectRNA_replicate5_run1_chr9_1_1000000.rds | Bin 5320 -> 6392 bytes
 ...rectRNA_replicate5_run1_chr9_1_1000000.rds | Bin 4592 -> 4112 bytes
 ...rectRNA_replicate5_run1_chr9_1_1000000.rds | Bin 5148 -> 5608 bytes
 ...rectRNA_replicate5_run1_chr9_1_1000000.rds | Bin 5220 -> 5608 bytes
 ...rectRNA_replicate5_run1_chr9_1_1000000.rds | Bin 4332 -> 4492 bytes
 8 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/R/bambu.R b/R/bambu.R
index 68e6ae4a..e1569db2 100644
--- a/R/bambu.R
+++ b/R/bambu.R
@@ -190,7 +190,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL,
   
     if(assignDist){
         message("--- Start calculating equivilance classes ---")
-        if (is.character(readClassList)) readClassList <- readRDS(file = readClassList)
+        if (is.character(readClassList)) readClassList <- list(readRDS(file = readClassList))
         #if(is.list(readClassList)) readClassList = readClassList[[1]]
         quantData = bplapply(readClassList, FUN = assignReadClasstoTranscripts, 
             annotations = annotations, isoreParameters = isoreParameters, verbose = verbose, 
diff --git a/R/sysdata.rda b/R/sysdata.rda
index 687f76bdede24705258d7595080b4557aba07d57..e7699bb44b5d411f6107d08946741ace57d841c4 100755
GIT binary patch
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diff --git a/data-raw/DATASET.R b/data-raw/DATASET.R
index 161f6540..fc95dd12 100755
--- a/data-raw/DATASET.R
+++ b/data-raw/DATASET.R
@@ -229,9 +229,9 @@ saveRDS(readGrgList, file = "./inst/extdata/readGrgList_SGNex_A549_directRNA_rep
 
 annotations <- readRDS(system.file("extdata", "annotationGranges_txdbGrch38_91_chr9_1_1000000.rds", package = "bambu"))
 genomeSequence <- system.file("extdata", "Homo_sapiens.GRCh38.dna_sm.primary_assembly_chr9_1_1000000.fa", package = "bambu")
-se <- bambu(reads = test.bam, annotations = annotations, genome = genomeSequence, discovery = FALSE, quant = FALSE)[[1]]
+se <- bambu(reads = test.bam, annotations = annotations, genome = genomeSequence, discovery = FALSE, assignDist = FALSE, quant = FALSE)[[1]]
 saveRDS(se, file = "./inst/extdata/seReadClassUnstranded_SGNex_A549_directRNA_replicate5_run1_chr9_1_1000000.rds", compress = "xz")
-se <- bambu(reads = test.bam, annotations = annotations, genome = genomeSequence, stranded = TRUE, discovery = FALSE, quant = FALSE)[[1]]
+se <- bambu(reads = test.bam, annotations = annotations, genome = genomeSequence, stranded = TRUE, assignDist = FALSE, discovery = FALSE, quant = FALSE)[[1]]
 saveRDS(se, file = "./inst/extdata/seReadClassStranded_SGNex_A549_directRNA_replicate5_run1_chr9_1_1000000.rds", compress = "xz")
 
 se <- bambu(reads = test.bam, annotations = annotations, genome = genomeSequence)
diff --git a/inst/extdata/seOutputCombinedExtended_SGNex_A549_directRNA_replicate5_run1_chr9_1_1000000.rds b/inst/extdata/seOutputCombinedExtended_SGNex_A549_directRNA_replicate5_run1_chr9_1_1000000.rds
index d6254f4abf5549ae720a0841b5c84b58e5b94198..bb99b8427deb5ea438141b9143cb2622619e9f28 100644
GIT binary patch
literal 6392
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diff --git a/inst/extdata/seReadClassUnstranded_SGNex_A549_directRNA_replicate5_run1_chr9_1_1000000.rds b/inst/extdata/seReadClassUnstranded_SGNex_A549_directRNA_replicate5_run1_chr9_1_1000000.rds
index 9cc59afb4aaa57113138542b0b6e94e6222d1154..83a9af7583fe29164b1baba4f5034d94bd2cbc01 100644
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From 75a49f7dda5480d6af04e734b8c98bea6d08353d Mon Sep 17 00:00:00 2001
From: Andre 
Date: Tue, 29 Oct 2024 14:59:55 +0800
Subject: [PATCH 144/189] Update version message

---
 R/bambu.R | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/R/bambu.R b/R/bambu.R
index e1569db2..60b11674 100644
--- a/R/bambu.R
+++ b/R/bambu.R
@@ -141,7 +141,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL,
     trackReads = FALSE, returnDistTable = FALSE, lowMemory = FALSE, 
     fusionMode = FALSE, verbose = FALSE, demultiplexed = FALSE, spatial = NULL, quantData = NULL,
     sampleNames = NULL, cleanReads = TRUE, dedupUMI = FALSE, clusters = NULL) {
-    message(paste0("Running Bambu-v", "3.2.4"))
+    message(paste0("Running Bambu-v", "3.3.0"))
     if(is.null(annotations)) { annotations = GRangesList()
     } else annotations <- checkInputs(annotations, reads,
             readClass.outputDir = rcOutDir, genomeSequence = genome, discovery = discovery, 

From f2d2d835aa794c80832a1ce3b97e6b30eb954410 Mon Sep 17 00:00:00 2001
From: Andre 
Date: Tue, 29 Oct 2024 15:24:15 +0800
Subject: [PATCH 145/189] Add in preset modes

---
 R/bambu.R | 22 ++++++++++++++++++++--
 1 file changed, 20 insertions(+), 2 deletions(-)

diff --git a/R/bambu.R b/R/bambu.R
index 60b11674..cd9e3a66 100644
--- a/R/bambu.R
+++ b/R/bambu.R
@@ -136,12 +136,30 @@
 #'     genome = fa.file,  discovery = TRUE, quant = TRUE)
 #' @export
 bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL,
-    opt.discovery = NULL, opt.em = NULL, rcOutDir = NULL, discovery = TRUE, 
+    mode = NULL, opt.discovery = NULL, opt.em = NULL, rcOutDir = NULL, discovery = TRUE, 
     assignDist = TRUE, quant = TRUE, stranded = FALSE,  ncore = 1, yieldSize = NULL,  
     trackReads = FALSE, returnDistTable = FALSE, lowMemory = FALSE, 
     fusionMode = FALSE, verbose = FALSE, demultiplexed = FALSE, spatial = NULL, quantData = NULL,
-    sampleNames = NULL, cleanReads = TRUE, dedupUMI = FALSE, clusters = NULL) {
+    sampleNames = NULL, cleanReads = FALSE, dedupUMI = FALSE, clusters = NULL) {
     message(paste0("Running Bambu-v", "3.3.0"))
+    if(mode == "bulk"){
+        lowMemory = TRUE
+    }
+    if(mode == "multiplexed"){
+        if(is.null(demultiplex)) demultiplex = TRUE,
+        cleanReads = TRUE,
+        opt.em = list(degradationBias = FALSE),
+        quant = FALSE
+    }
+    if(mode == "fusion"){
+        NDR = 1,
+        fusionMode = TRUE
+    }
+    if(mode == "debug"){
+        verbose = TRUE,
+        trackReads = TRUE,
+        returnDistTable = TRUE
+    }
     if(is.null(annotations)) { annotations = GRangesList()
     } else annotations <- checkInputs(annotations, reads,
             readClass.outputDir = rcOutDir, genomeSequence = genome, discovery = discovery, 

From 09dcb4db1d094a385357f88bb368e4e0471a905b Mon Sep 17 00:00:00 2001
From: Andre 
Date: Tue, 29 Oct 2024 15:25:27 +0800
Subject: [PATCH 146/189] remove commas

---
 R/bambu.R | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/R/bambu.R b/R/bambu.R
index cd9e3a66..34d9a166 100644
--- a/R/bambu.R
+++ b/R/bambu.R
@@ -146,18 +146,18 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL,
         lowMemory = TRUE
     }
     if(mode == "multiplexed"){
-        if(is.null(demultiplex)) demultiplex = TRUE,
-        cleanReads = TRUE,
-        opt.em = list(degradationBias = FALSE),
+        if(is.null(demultiplex)) demultiplex = TRUE
+        cleanReads = TRUE
+        opt.em = list(degradationBias = FALSE)
         quant = FALSE
     }
     if(mode == "fusion"){
-        NDR = 1,
+        NDR = 1
         fusionMode = TRUE
     }
     if(mode == "debug"){
-        verbose = TRUE,
-        trackReads = TRUE,
+        verbose = TRUE
+        trackReads = TRUE
         returnDistTable = TRUE
     }
     if(is.null(annotations)) { annotations = GRangesList()

From c55383dd8268f3fa8024ad8bcd01c582448fc3b3 Mon Sep 17 00:00:00 2001
From: Andre 
Date: Tue, 29 Oct 2024 17:02:30 +0800
Subject: [PATCH 147/189] Fix mode

---
 R/bambu.R | 36 +++++++++++++++++++-----------------
 1 file changed, 19 insertions(+), 17 deletions(-)

diff --git a/R/bambu.R b/R/bambu.R
index 34d9a166..df4fe6cb 100644
--- a/R/bambu.R
+++ b/R/bambu.R
@@ -142,23 +142,25 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL,
     fusionMode = FALSE, verbose = FALSE, demultiplexed = FALSE, spatial = NULL, quantData = NULL,
     sampleNames = NULL, cleanReads = FALSE, dedupUMI = FALSE, clusters = NULL) {
     message(paste0("Running Bambu-v", "3.3.0"))
-    if(mode == "bulk"){
-        lowMemory = TRUE
-    }
-    if(mode == "multiplexed"){
-        if(is.null(demultiplex)) demultiplex = TRUE
-        cleanReads = TRUE
-        opt.em = list(degradationBias = FALSE)
-        quant = FALSE
-    }
-    if(mode == "fusion"){
-        NDR = 1
-        fusionMode = TRUE
-    }
-    if(mode == "debug"){
-        verbose = TRUE
-        trackReads = TRUE
-        returnDistTable = TRUE
+    if(!is.null(mode)){
+        if(mode == "bulk"){
+            lowMemory = TRUE
+        }
+        if(mode == "multiplexed"){
+            if(is.null(demultiplex)) demultiplex = TRUE
+            cleanReads = TRUE
+            opt.em = list(degradationBias = FALSE)
+            quant = FALSE
+        }
+        if(mode == "fusion"){
+            NDR = 1
+            fusionMode = TRUE
+        }
+        if(mode == "debug"){
+            verbose = TRUE
+            trackReads = TRUE
+            returnDistTable = TRUE
+        }
     }
     if(is.null(annotations)) { annotations = GRangesList()
     } else annotations <- checkInputs(annotations, reads,

From 99d3148b700e0cf8e3fbf9cb1165b26e990676a1 Mon Sep 17 00:00:00 2001
From: Andre 
Date: Mon, 4 Nov 2024 17:05:02 +0800
Subject: [PATCH 148/189] Fix reccomendNDR

small change
---
 R/bambu-extendAnnotations-utilityExtend.R | 14 +++++++++-----
 1 file changed, 9 insertions(+), 5 deletions(-)

diff --git a/R/bambu-extendAnnotations-utilityExtend.R b/R/bambu-extendAnnotations-utilityExtend.R
index cbdddcb6..2615ff24 100644
--- a/R/bambu-extendAnnotations-utilityExtend.R
+++ b/R/bambu-extendAnnotations-utilityExtend.R
@@ -68,7 +68,8 @@ filterTranscripts <- function(combinedTranscripts, min.sampleNumber){
         combinedTranscripts$NSampleReadProp >= min.sampleNumber)
   }
   #combinedTranscripts = combinedTranscripts[filterSet,]
-  combinedTranscripts$maxTxScore[!filterSet] = 0
+  combinedTranscripts$maxTxScore[!filterSet] = -1
+  combinedTranscripts$maxTxScore.noFit[!filterSet] = -1
   return(combinedTranscripts)
 }
 
@@ -97,7 +98,9 @@ filterTranscriptsByAnnotation <- function(rowDataCombined, annotationGrangesList
         rowDataCombined[!notCompatibleIds,], 
         exonRangesCombined[!notCompatibleIds])
     rowDataCombined$maxTxScore[grepl("compatible", rowDataCombined$readClassType) &
-        rowDataCombined$readClassType != "equal:compatible"]=0
+        rowDataCombined$readClassType != "equal:compatible"]=-1
+    rowDataCombined$maxTxScore.noFit[grepl("compatible", rowDataCombined$readClassType) &
+        rowDataCombined$readClassType != "equal:compatible"]=-1
   }
   #(2) remove transcripts below NDR threshold/identical junctions to annotations
   rowDataCombined = calculateNDROnTranscripts(rowDataCombined, 
@@ -153,16 +156,17 @@ filterTranscriptsByAnnotation <- function(rowDataCombined, annotationGrangesList
 #' @noRd
 recommendNDR <- function(combinedTranscripts, baselineFDR = 0.1, NDR = NULL, defaultModels = defaultModels, verbose = FALSE){
     if(verbose) message("-- Predicting annotation completeness to determine NDR threshold --")
+    combinedTranscripts = combinedTranscripts[combinedTranscripts$maxTxScore.noFit >=0, ] #ignore filtered out read classes
     equal = combinedTranscripts$readClassType == "equal:compatible"
     equal[is.na(equal)] = FALSE
-
     #add envirnment so poly() works
     attr(defaultModels$lmNDR[["terms"]], ".Environment") <- new.env(parent = parent.env(globalenv()))
     baseline = predict(defaultModels$lmNDR, newdata=data.frame(NDR=baselineFDR))
     attr(defaultModels$lmNDR[["terms"]], ".Environment") = c()
 
-    NDRscores = calculateNDR(combinedTranscripts$maxTxScore.noFit, equal)
     score = combinedTranscripts$maxTxScore.noFit
+    score[is.na(score)] = 0
+    NDRscores = calculateNDR(score, equal)
     NDR.rec = predict(lm(NDRscores~poly(score,3,raw=TRUE)), newdata=data.frame(score=baseline))
     NDR.rec = round(NDR.rec,3)
     if(verbose) message("Recommended NDR for baseline FDR of ", baselineFDR, " = ", NDR.rec)
@@ -219,7 +223,7 @@ calculateNDROnTranscripts <- function(combinedTranscripts, useTxScore = FALSE){
             "for NDR precision stabilization.")
           message("NDR will be approximated as: (1 - Transcript Model Prediction Score)")
     } else combinedTranscripts$NDR = calculateNDR(combinedTranscripts$maxTxScore, equal)
-    combinedTranscripts$NDR[combinedTranscripts$maxTxScore==0] = 1
+    combinedTranscripts$NDR[combinedTranscripts$maxTxScore==-1] = 1
     return(combinedTranscripts)
 }
 

From a605fe732ffa399051cdbf052c896c838978e77b Mon Sep 17 00:00:00 2001
From: Andre 
Date: Tue, 5 Nov 2024 09:38:59 +0800
Subject: [PATCH 149/189] Fix quantification when running bulk

---
 R/bambu-processReads.R | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/R/bambu-processReads.R b/R/bambu-processReads.R
index d64b2c68..6bce2b9c 100644
--- a/R/bambu-processReads.R
+++ b/R/bambu-processReads.R
@@ -83,12 +83,12 @@ bambu.processReads <- function(reads, annotations, genomeSequence,
                 mcols(readGrgList[[i]])$BC = paste0(names(reads)[i], '_', mcols(readGrgList[[i]])$BC)
             } else{mcols(readGrgList[[i]])$BC = sampleNames[i]}
             mcols(readGrgList[[i]])$BC = as.factor(mcols(readGrgList[[i]])$BC)
+            if(!isFALSE(demultiplexed)){ 
+                mcols(readGrgList[[i]])$sampleID = as.numeric(mcols(readGrgList[[i]])$BC)
+            } else {mcols(readGrgList[[i]])$sampleID = i}
         }
         readGrgList = do.call(c, readGrgList)    
         mcols(readGrgList)$id <- seq_along(readGrgList) 
-        if(!isFALSE(demultiplexed)){ 
-            mcols(readGrgList)$sampleID = as.numeric(mcols(readGrgList)$BC)
-        } else {mcols(readGrgList)$sampleID = mcols(readGrgList)$BC}
         readClassList <- constructReadClasses(readGrgList, genomeSequence = genomeSequence,annotations = annotations,
             readClass.outputDir = readClass.outputDir,
             stranded = stranded, min.readCount = min.readCount, 
@@ -184,7 +184,7 @@ bambu.processReadsByFile <- function(bam.file, genomeSequence, annotations,
     mcols(readGrgList)$BC = as.factor(mcols(readGrgList)$BC)
     if(!isFALSE(demultiplexed)){ 
         mcols(readGrgList)$sampleID = as.numeric(mcols(readGrgList)$BC)
-    } else {mcols(readGrgList)$sampleID = mcols(readGrgList)$BC}
+    } else {mcols(readGrgList)$sampleID = index}
         
     # construct read classes for each chromosome seperately 
     se <- lowMemoryConstructReadClasses(readGrgList, genomeSequence, 

From 7a62db7ef0af5b270f10babb790f9914d19564c7 Mon Sep 17 00:00:00 2001
From: Andre 
Date: Tue, 5 Nov 2024 10:20:58 +0800
Subject: [PATCH 150/189] restore returnDistTable

---
 R/bambu-assignDist.R | 5 ++++-
 R/bambu.R            | 2 +-
 2 files changed, 5 insertions(+), 2 deletions(-)

diff --git a/R/bambu-assignDist.R b/R/bambu-assignDist.R
index abd334ea..00e49ac9 100644
--- a/R/bambu-assignDist.R
+++ b/R/bambu-assignDist.R
@@ -2,7 +2,7 @@
 #' @inheritParams bambu
 #' @import data.table
 #' @noRd
-assignReadClasstoTranscripts <- function(readClassList, annotations, isoreParameters, verbose, demultiplexed, spatial) {
+assignReadClasstoTranscripts <- function(readClassList, annotations, isoreParameters, verbose, demultiplexed, spatial, returnDistTable = FALSE) {
     metadata(readClassList)$readClassDist <- calculateDistTable(readClassList, annotations, isoreParameters, verbose)
     readClassList = splitReadClassFiles(readClassList)
     readClassDt <- genEquiRCs(metadata(readClassList)$readClassDist, annotations, verbose) 
@@ -26,6 +26,9 @@ assignReadClasstoTranscripts <- function(readClassList, annotations, isoreParame
     }
     metadata(quantData)$nonuniqueCounts = generateNonUniqueCounts(readClassDt, metadata(readClassList)$countMatrix, annotations)
     metadata(quantData)$readClassDt = readClassDt
+    if(returnDistTable){
+        metadata(quantData)$distTable = metadata(readClassList)$readClassDist
+    }
     metadata(quantData)$countMatrix = metadata(readClassList)$countMatrix
     metadata(quantData)$incompatibleCountMatrix  = metadata(readClassList)$incompatibleCountMatrix 
     metadata(quantData)$sampleNames = metadata(readClassList)$sampleNames 
diff --git a/R/bambu.R b/R/bambu.R
index df4fe6cb..00529e0c 100644
--- a/R/bambu.R
+++ b/R/bambu.R
@@ -214,7 +214,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL,
         #if(is.list(readClassList)) readClassList = readClassList[[1]]
         quantData = bplapply(readClassList, FUN = assignReadClasstoTranscripts, 
             annotations = annotations, isoreParameters = isoreParameters, verbose = verbose, 
-            demultiplexed = demultiplexed, spatial = spatial,
+            demultiplexed = demultiplexed, spatial = spatial, returnDistTable = returnDistTable,
             BPPARAM = bpParameters)                 
         if (!quant) return(quantData)
     }

From 10fd9052d9b648ad20e992f84138f8d4abd2d551 Mon Sep 17 00:00:00 2001
From: Andre 
Date: Tue, 5 Nov 2024 11:03:00 +0800
Subject: [PATCH 151/189] Return default degbias to on

---
 R/bambu_utilityFunctions.R | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/R/bambu_utilityFunctions.R b/R/bambu_utilityFunctions.R
index 932a7bcb..782b951e 100644
--- a/R/bambu_utilityFunctions.R
+++ b/R/bambu_utilityFunctions.R
@@ -46,7 +46,7 @@ setIsoreParameters <- function(isoreParameters){
 #' setEmParameters
 #' @noRd
 setEmParameters <- function(emParameters){
-    emParameters.default <- list(degradationBias = FALSE, maxiter = 10000, 
+    emParameters.default <- list(degradationBias = TRUE, maxiter = 10000, 
         conv = 10^(-2), minvalue = 10^(-8), sig.digit = 5)
     emParameters <- updateParameters(emParameters, emParameters.default)
     return(emParameters)

From df6b4b329eb6310c1bc3e195a6a26475dfe3b4e4 Mon Sep 17 00:00:00 2001
From: Andre 
Date: Mon, 11 Nov 2024 13:09:03 +0800
Subject: [PATCH 152/189] Restore trackreads

---
 R/bambu-assignDist.R                | 15 +++++++++++----
 R/bambu-quantify_utilityFunctions.R | 11 ++++++++++-
 R/bambu.R                           |  9 +++------
 3 files changed, 24 insertions(+), 11 deletions(-)

diff --git a/R/bambu-assignDist.R b/R/bambu-assignDist.R
index 00e49ac9..b82a07ad 100644
--- a/R/bambu-assignDist.R
+++ b/R/bambu-assignDist.R
@@ -2,7 +2,9 @@
 #' @inheritParams bambu
 #' @import data.table
 #' @noRd
-assignReadClasstoTranscripts <- function(readClassList, annotations, isoreParameters, verbose, demultiplexed, spatial, returnDistTable = FALSE) {
+assignReadClasstoTranscripts <- function(readClassList, annotations, isoreParameters, 
+                                        verbose, demultiplexed, spatial, 
+                                        returnDistTable = FALSE, trackReads = TRUE) {
     metadata(readClassList)$readClassDist <- calculateDistTable(readClassList, annotations, isoreParameters, verbose)
     readClassList = splitReadClassFiles(readClassList)
     readClassDt <- genEquiRCs(metadata(readClassList)$readClassDist, annotations, verbose) 
@@ -26,12 +28,17 @@ assignReadClasstoTranscripts <- function(readClassList, annotations, isoreParame
     }
     metadata(quantData)$nonuniqueCounts = generateNonUniqueCounts(readClassDt, metadata(readClassList)$countMatrix, annotations)
     metadata(quantData)$readClassDt = readClassDt
-    if(returnDistTable){
-        metadata(quantData)$distTable = metadata(readClassList)$readClassDist
-    }
     metadata(quantData)$countMatrix = metadata(readClassList)$countMatrix
     metadata(quantData)$incompatibleCountMatrix  = metadata(readClassList)$incompatibleCountMatrix 
     metadata(quantData)$sampleNames = metadata(readClassList)$sampleNames 
+    if(returnDistTable){
+        metadata(quantData)$distTable = metadata(readClassList)$readClassDist
+    }
+    if (trackReads){
+        metadata(quantData)$readToTranscriptMap = 
+            generateReadToTranscriptMap(readClassList, metadata(readClassList)$readClassDist, 
+                                  annotations)
+    } 
     return(quantData)     
 
 }
diff --git a/R/bambu-quantify_utilityFunctions.R b/R/bambu-quantify_utilityFunctions.R
index 98fd0b21..0bb8c85d 100644
--- a/R/bambu-quantify_utilityFunctions.R
+++ b/R/bambu-quantify_utilityFunctions.R
@@ -68,7 +68,7 @@ genEquiRCsBasedOnObservedReads <- function(readClass){
                           width(unlisted_rowranges[unlisted_rowranges$exon_rank == 1,]),
                         totalWidth = sum(width(rowRanges(readClass))))
   distTable <- data.table(as.data.frame(metadata(readClass)$distTable))[!grepl("unidentified", annotationTxId), .(readClassId, 
-                                                                                                                  annotationTxId, readCount, GENEID, dist,equal,txid)]
+                                                                                                                  annotationTxId, readCount, GENEID, dist,equal, compatible, txid)]
   distTable <- rcWidth[distTable, on = "readClassId"]
   # filter out multiple geneIDs mapped to the same readClass using rowData(se)
   compatibleData <- as.data.table(as.data.frame(rowData(readClass)),
@@ -464,25 +464,34 @@ generateReadToTranscriptMap <- function(readClass, distTable, annotations){
   if(!is.null(metadata(readClass)$readNames)) { 
     read_id = metadata(readClass)$readNames}
   else { read_id = metadata(readClass)$readId}
+  print(1)
   #unpack and reverse the read class to read id relationship
   readOrder = order(unlist(rowData(readClass)$readIds))
   lens = lengths(rowData(readClass)$readIds)
   rcIndex = seq_along(readClass)
   readToRC = rep(rcIndex, lens)[readOrder]
   read_id = read_id[(match(unlist(rowData(readClass)$readIds)[readOrder], metadata(readClass)$readId))]
+  print(2)
   #get annotation indexs
+  distTable = metadata(distTable)$distTable
+    print(head(distTable))
   distTable$annotationTxId = match(distTable$annotationTxId, names(annotations))
+  print(2.1)
+  print(head(distTable))
   #match read classes with transcripts
   readClass_id = rownames(readClass)[readToRC]
   distTable$exClassById = NULL
+  print(3)
   equalMatches = as_tibble(distTable) %>%
     filter(equal) %>% 
     group_by(readClassId) %>% summarise(annotationTxIds = list(annotationTxId))
   equalMatches = equalMatches$annotationTxIds[match(readClass_id, equalMatches$readClassId)]
+  print(4)
   compatibleMatches =  as_tibble(distTable) %>% 
     filter(!equal & compatible) %>% 
     group_by(readClassId) %>% summarise(annotationTxIds = list(annotationTxId))
   compatibleMatches = compatibleMatches$annotationTxIds[match(readClass_id, compatibleMatches$readClassId)]
+  print(5)
   readToTranscriptMap = tibble(readId=read_id, equalMatches = equalMatches, compatibleMatches = compatibleMatches)
   return(readToTranscriptMap)
 }
diff --git a/R/bambu.R b/R/bambu.R
index 00529e0c..fb4bfe25 100644
--- a/R/bambu.R
+++ b/R/bambu.R
@@ -215,6 +215,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL,
         quantData = bplapply(readClassList, FUN = assignReadClasstoTranscripts, 
             annotations = annotations, isoreParameters = isoreParameters, verbose = verbose, 
             demultiplexed = demultiplexed, spatial = spatial, returnDistTable = returnDistTable,
+            trackReads = trackReads,
             BPPARAM = bpParameters)                 
         if (!quant) return(quantData)
     }
@@ -277,15 +278,11 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL,
             }
             countsSeCompressed.all = c(countsSeCompressed.all, countsSeCompressed)
         }
-        countsSeCompressed.all$colnames = ColNames
-         #return(countsSeCompressed.all)                
+        countsSeCompressed.all$colnames = ColNames            
         countsSe <- combineCountSes(countsSeCompressed.all, annotations)
 
         #metadata(countsSe)$warnings = warnings
-        # if (trackReads) metadata(seOutput)$readToTranscriptMap = 
-        #     generateReadToTranscriptMap(readClass, metadata(readClassDist)$distTable, 
-        #                              annotations)
-        # if (returnDistTable) metadata(seOutput)$distTable = metadata(readClassDist)$distTable
+
         ColData = generateColData(colnames(countsSe), clusters, demultiplexed, spatial)
         colData(countsSe) = ColData
         colnames(countsSe) = ColData[,1]

From 5d0af93dda313d499bf59c54f7b12f62dd9e9d29 Mon Sep 17 00:00:00 2001
From: Andre 
Date: Mon, 11 Nov 2024 13:09:17 +0800
Subject: [PATCH 153/189] Add in descriptions for new arguments

---
 README.md | 25 ++++++++++++++++++++++++-
 1 file changed, 24 insertions(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 258f4970..80f6c08d 100755
--- a/README.md
+++ b/README.md
@@ -476,7 +476,30 @@ se <- bambu(reads = fusionAligned.bam, annotations = fusionAnnotations, genome =
 | discovery | A logical variable indicating whether annotations are to be extended for quantification, defaults to TRUE. |
 | quant | A logical variable indicating whether quantification will be performed, defaults to TRUE. |
 | verbose | A logical variable indicating whether processing messages will be printed. |
-| lowMemory | Reads will be processed by chromosomes instead of all together when lowMemory is specified. This option provides an efficient way to process big samples. |
+| lowMemory | A logical variable indicating if each input bam file will be processed seperately (TRUE) or all are read in and processed together (FALSE), defaults to TRUE |
+| mode | A string that will set other input arguments ['bulk', 'multiplexed', 'fusion', 'debug']
+bulk - lowMemory = TRUE
+multiplexed -
+            demultiplex = TRUE
+            cleanReads = TRUE
+            opt.em = list(degradationBias = FALSE)
+            quant = FALSE
+
+fusion
+            NDR = 1
+            fusionMode = TRUE
+debug
+            verbose = TRUE
+            trackReads = TRUE
+            returnDistTable = TRUE |
+| demultiplexed | A logical variable indicating whether the input bam file is demultiplexed. The barcode and umi either need to be present in the read name or the $BC and $UG tags, defaults to FALSE. Alternatively a path to a csv file can be provided where column 1 is read names, column 2 is barcodes, and column 3 is UMI. |
+| spatial | A path to the barcode whitelist containing X and Y coordinates, defaults to null. |
+| assignDist | A logical variable indicating whether read class to transcript assignment will be performed, defaults to TRUE. |
+| quantData | Advanced use only. A list of se outputs from the assignDist step. Used only to run quantification |
+| sampleNames | A vector of strings representing the sample name associated with each input bam. bam files with the same sample name will be combined |
+| cleanReads | A logical variable indicating whether only the first sequenced alignment in a read should be kept. This helps to remove chimeric reads, but will remove alignments from fusion genes, defaults to FALSE. |
+| dedupUMI | A logical variable indicating whether UMI deduplication is performed. The longest read per UMI will be used and the rest discarded, defaults to FALSE.|
+| clusters | Either a list containing the barcodes for each cluster, or a path to a csv file containg the barcode to cluster mapping. When provided, clusters will be used during discovery and EM quant steps, defaults to null. |
 
 ### setNDR() arguments
 |argument|description|

From 0b455ef3370eb99ff4ec15f2932bd52c5554a2c4 Mon Sep 17 00:00:00 2001
From: Andre 
Date: Mon, 11 Nov 2024 14:48:36 +0800
Subject: [PATCH 154/189] Clean up cluster discovery

---
 R/bambu-extendAnnotations-utilityExtend.R | 52 +++++++++++++++++++++
 R/bambu.R                                 | 55 +++--------------------
 2 files changed, 57 insertions(+), 50 deletions(-)

diff --git a/R/bambu-extendAnnotations-utilityExtend.R b/R/bambu-extendAnnotations-utilityExtend.R
index 5f0665a8..14257109 100644
--- a/R/bambu-extendAnnotations-utilityExtend.R
+++ b/R/bambu-extendAnnotations-utilityExtend.R
@@ -873,4 +873,56 @@ setNDR = function(extendedAnnotations, NDR = NULL, includeRef = FALSE, prefix =
   metadata(extendedAnnotations)$NDRthreshold = NDR
 
   return(extendedAnnotations)
+}
+
+isore.extendAnnotations.clusters <- function(readClassList, annotations, clusters, NDR, isoreParameters, stranded, bpParameters, fusionMode, verbose = FALSE){
+    message("--- Start extending annotations for clusters ---")
+    #if clustering is a csv, create a list with the barcodes for each cluster
+    #csv must have two cols with heading barcode, cluster
+    if(!is.list(clusters)){
+        clusters = read.csv(clusters)
+        clusters = clusters %>% group_by(cluster) %>% summarise(barcodes = list(barcode))
+        clusters = clusters$cluster
+        clusters = clusters$barcodes
+        names(clusters) = clusters
+    }
+    annotations.clusters = list()
+    rcfs.clusters = list()
+    clusters.rc = splitReadClassFilesByRC(readClassList[[1]])
+    txScores = c()
+    for(i in seq_along(clusters)){
+        print(names(clusters)[i])
+        ###TODO need to account for the sample name here which is added to the barcode
+        index = match(clusters[[i]],gsub('demultiplexed','',metadata(readClassList[[1]])$samples)) 
+        index = index[!is.na(index)]
+        print(length(index))
+        if(length(index)<20) next
+        rcf.counts = clusters.rc[,index]
+        rcf.filt = readClassList[[1]][rowSums(rcf.counts)>0,]
+        rowData(rcf.filt)$readCount = rowSums(rcf.counts)[rowSums(rcf.counts)>0]
+        countsTBL = calculateGeneProportion(counts=mcols(rcf.filt)$readCount,
+                                            geneIds=mcols(rcf.filt)$GENEID)
+        rowData(rcf.filt)$geneReadProp = countsTBL$geneReadProp
+        rowData(rcf.filt)$geneReadCount = countsTBL$geneReadCount
+        rowData(rcf.filt)$startSD = 0
+        rowData(rcf.filt)$endSD = 0
+        rowData(rcf.filt)$readCount.posStrand = 0
+        thresholdIndex = which(rowData(rcf.filt)$readCount>=isoreParameters$min.readCount)
+        model = trainBambu(rcf.filt, verbose = verbose, min.readCount = isoreParameters$min.readCount)
+        txScore = getTranscriptScore(rowData(rcf.filt)[thresholdIndex,], model,
+                                defaultModels)
+        rowData(rcf.filt)$txScore = rep(NA,nrow(rcf.filt))
+        rowData(rcf.filt)$txScore[thresholdIndex] = txScore
+        #txScores = cbind(txScores, rowData(rcf.filt)$txScore)
+        rcfs.clusters[[names(clusters)[i]]] = rcf.filt
+        annotations.clusters[[names(clusters)[i]]] <- bambu.extendAnnotations(list(rcf.filt), annotations, NDR,
+                                isoreParameters, stranded, bpParameters, fusionMode, verbose)
+    }
+    if(length(rcfs.clusters)>0){
+        print("--- Merging all individual clusters ---")
+        annotations.clusters[["merged"]] <- bambu.extendAnnotations(rcfs.clusters, annotations, NDR,
+            isoreParameters, stranded, bpParameters, fusionMode, verbose)
+    }
+      
+    return(annotations.clusters)
 }
\ No newline at end of file
diff --git a/R/bambu.R b/R/bambu.R
index ef854aef..66314721 100644
--- a/R/bambu.R
+++ b/R/bambu.R
@@ -205,59 +205,14 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL,
                                             isoreParameters, stranded, bpParameters, fusionMode, verbose)
         metadata(extendedAnnotations)$warnings = warnings
         
-        #### split rcf into clusters
+        #### cluster based transcript discovery
         if(!is.null(clusters)){
-            message("--- Start extending annotations for clusters ---")
-            #if clustering is a csv, create a list with the barcodes for each cluster
-            #csv must have two cols with heading barcode, cluster
-            if(!is.list(clusters)){
-                clusters = read.csv(clusters)
-                clusters = clusters %>% group_by(cluster) %>% summarise(barcodes = list(barcode))
-                clusters = clusters$cluster
-                clusters = clusters$barcodes
-                names(clusters) = clusters
-            }
-            annotations.clusters = list()
-            rcfs.clusters = list()
-            clusters.rc = splitReadClassFilesByRC(readClassList[[1]])
-            txScores = c()
-            for(i in seq_along(clusters)){
-                print(names(clusters)[i])
-                ###TODO need to account for the sample name here which is added to the barcode
-                index = match(clusters[[i]],gsub('demultiplexed','',metadata(rcf[[1]])$samples)) 
-                index = index[!is.na(index)]
-                print(length(index))
-                if(length(index)<20) next
-                rcf.counts = clusters.rc[,index]
-                rcf.filt = readClassList[[1]][rowSums(rcf.counts)>0,]
-                rowData(rcf.filt)$readCount = rowSums(rcf.counts)[rowSums(rcf.counts)>0]
-                countsTBL = calculateGeneProportion(counts=mcols(rcf.filt)$readCount,
-                                                    geneIds=mcols(rcf.filt)$GENEID)
-                rowData(rcf.filt)$geneReadProp = countsTBL$geneReadProp
-                rowData(rcf.filt)$geneReadCount = countsTBL$geneReadCount
-                rowData(rcf.filt)$startSD = 0
-                rowData(rcf.filt)$endSD = 0
-                rowData(rcf.filt)$readCount.posStrand = 0
-                thresholdIndex = which(rowData(rcf.filt)$readCount>=2)
-                model = trainBambu(rcf.filt, verbose = TRUE, min.readCount = 2)
-                txScore = getTranscriptScore(rowData(rcf.filt)[thresholdIndex,], model,
-                                        defaultModels)
-                rowData(rcf.filt)$txScore = rep(NA,nrow(rcf.filt))
-                rowData(rcf.filt)$txScore[thresholdIndex] = txScore
-                #txScores = cbind(txScores, rowData(rcf.filt)$txScore)
-                rcfs.clusters[[names(clusters)[i]]] = rcf.filt
-                annotations.clusters[[names(clusters)[i]]] <- bambu.extendAnnotations(list(rcf.filt), annotations, NDR,
-                                        isoreParameters, stranded, bpParameters, fusionMode, verbose)
-            }
-            if(length(rcfs.clusters)>0){
-                print("--- Merging all individual clusters ---")
-                annotations.clusters[["merged"]] <- bambu.extendAnnotations(rcfs.clusters, annotations, NDR,
-                    isoreParameters, stranded, bpParameters, fusionMode, verbose)
-            }
-            metadata(extendedAnnotations)$clusters = annotations.clusters
+            annotations.clusters = isore.extendAnnotations.clusters(readClassList, annotations, clusters, NDR, 
+                isoreParameters, stranded, bpParameters, fusionMode, verbose = FALSE)  
+                metadata(extendedAnnotations)$clusters = annotations.clusters    
         }
         annotations = extendedAnnotations
-
+        
         if (!quant & !assignDist) return(annotations)
     }
   

From 11a8d8b0b2be4db409d5bb593582e6c3d1f4d55d Mon Sep 17 00:00:00 2001
From: Andre 
Date: Fri, 22 Nov 2024 18:00:34 +0800
Subject: [PATCH 155/189] Fix issue with lowMem and multiple samples

---
 R/bambu-processReads.R | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/R/bambu-processReads.R b/R/bambu-processReads.R
index 06c83eb9..29555b23 100644
--- a/R/bambu-processReads.R
+++ b/R/bambu-processReads.R
@@ -63,7 +63,7 @@ bambu.processReads <- function(reads, annotations, genomeSequence,
             fitReadClassModel = fitReadClassModel, min.exonOverlap = min.exonOverlap, 
             defaultModels = defaultModels, returnModel = returnModel, verbose = verbose, 
             trackReads = trackReads, fusionMode = fusionMode, 
-            demultiplexed = demultiplexed, cleanReads = cleanReads, dedupUMI = dedupUMI, index = i, barcodesToFilter = barcodesToFilter)},
+            demultiplexed = demultiplexed, cleanReads = cleanReads, dedupUMI = dedupUMI, index = 1, barcodesToFilter = barcodesToFilter)},
             BPPARAM = bpParameters)
     } else {
         readGrgList <- bplapply(seq_along(reads), function(i) {

From f8053cf25dfd40a193f25b56f5354d1e684d58bb Mon Sep 17 00:00:00 2001
From: Andre 
Date: Wed, 4 Dec 2024 10:54:39 +0800
Subject: [PATCH 156/189] Fix formatting in docu

---
 README.md | 16 +---------------
 1 file changed, 1 insertion(+), 15 deletions(-)

diff --git a/README.md b/README.md
index 80f6c08d..f03e31cf 100755
--- a/README.md
+++ b/README.md
@@ -477,21 +477,7 @@ se <- bambu(reads = fusionAligned.bam, annotations = fusionAnnotations, genome =
 | quant | A logical variable indicating whether quantification will be performed, defaults to TRUE. |
 | verbose | A logical variable indicating whether processing messages will be printed. |
 | lowMemory | A logical variable indicating if each input bam file will be processed seperately (TRUE) or all are read in and processed together (FALSE), defaults to TRUE |
-| mode | A string that will set other input arguments ['bulk', 'multiplexed', 'fusion', 'debug']
-bulk - lowMemory = TRUE
-multiplexed -
-            demultiplex = TRUE
-            cleanReads = TRUE
-            opt.em = list(degradationBias = FALSE)
-            quant = FALSE
-
-fusion
-            NDR = 1
-            fusionMode = TRUE
-debug
-            verbose = TRUE
-            trackReads = TRUE
-            returnDistTable = TRUE |
+| mode | A string that will set other input arguments ['bulk', 'multiplexed', 'fusion', 'debug']
     bulk - 
        lowMemory = TRUE
    multiplexed - 
        demultiplex = TRUE
        cleanReads = TRUE
        opt.em = list(degradationBias = FALSE)
        quant = FALSE
    fusion - 
        NDR = 1
        fusionMode = TRUE
    debug -
        verbose = TRUE
        trackReads = TRUE
        returnDistTable = TRUE |
 | demultiplexed | A logical variable indicating whether the input bam file is demultiplexed. The barcode and umi either need to be present in the read name or the $BC and $UG tags, defaults to FALSE. Alternatively a path to a csv file can be provided where column 1 is read names, column 2 is barcodes, and column 3 is UMI. |
 | spatial | A path to the barcode whitelist containing X and Y coordinates, defaults to null. |
 | assignDist | A logical variable indicating whether read class to transcript assignment will be performed, defaults to TRUE. |

From 1ac5e4b3103c26e0c31a354f015093d9f6758de8 Mon Sep 17 00:00:00 2001
From: Andre 
Date: Thu, 5 Dec 2024 10:43:18 +0800
Subject: [PATCH 157/189] returnDistTable now works when quant = TRUE

---
 R/bambu.R | 12 +++++++++---
 1 file changed, 9 insertions(+), 3 deletions(-)

diff --git a/R/bambu.R b/R/bambu.R
index 66314721..8205f72b 100644
--- a/R/bambu.R
+++ b/R/bambu.R
@@ -260,7 +260,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL,
                     iter = clustering
 
                 } else{ #if clusters is a list
-                    if(length(quantDatas)>1){iter = clusters[[i]] #lowMemory mode
+                    if(length(quantData)>1){iter = clusters[[i]] #lowMemory mode
                     }else(iter = do.call(c,clusters))
                 }
             }
@@ -275,7 +275,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL,
                                             incompatibleCountMatrix = data.table(GENEID.i = as.numeric(rownames(metadata(quantData_i)$incompatibleCountMatrix)), counts = incompatibleCountMatrix),
                                             txid.index = mcols(annotations)$txid, GENEIDs = GENEIDs.i, isoreParameters = isoreParameters,
                                             emParameters = emParameters, trackReads = trackReads, 
-                                            returnDistTable = returnDistTable, verbose = verbose))}, 
+                                            verbose = verbose))}, 
                                             BPPARAM = bpParameters)
             end.ptm <- proc.time()
             message("Total Time ", round((end.ptm - start.ptm)[3] / 60, 3), " mins.")
@@ -288,7 +288,13 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL,
         }
         countsSeCompressed.all$colnames = ColNames            
         countsSe <- combineCountSes(countsSeCompressed.all, annotations)
-
+        if(returnDistTable){
+            distTables = list()
+            for(i in seq_along(quantData)){
+                distTables[[i]] = metadata(quantData[[i]])$distTable
+            }
+            metadata(countsSe)$distTables = distTables
+        }
         #metadata(countsSe)$warnings = warnings
 
         ColData = generateColData(colnames(countsSe), clusters, demultiplexed, spatial)

From 5e5718864130bf03d0dbb682708f9d77efae8a19 Mon Sep 17 00:00:00 2001
From: Andre 
Date: Thu, 5 Dec 2024 10:45:50 +0800
Subject: [PATCH 158/189] max recommended NDR is now 0.999

---
 R/bambu-extendAnnotations-utilityExtend.R | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/R/bambu-extendAnnotations-utilityExtend.R b/R/bambu-extendAnnotations-utilityExtend.R
index 14257109..338ea822 100644
--- a/R/bambu-extendAnnotations-utilityExtend.R
+++ b/R/bambu-extendAnnotations-utilityExtend.R
@@ -169,8 +169,9 @@ recommendNDR <- function(combinedTranscripts, baselineFDR = 0.1, NDR = NULL, def
     NDRscores = calculateNDR(score, equal)
     NDR.rec = predict(lm(NDRscores~poly(score,3,raw=TRUE)), newdata=data.frame(score=baseline))
     NDR.rec = round(NDR.rec,3)
+    if(NDR.rec > 1){NDR.rec = 0.999}
+    if (NDR.rec < 0) {NDR.rec = 0}
     if(verbose) message("Recommended NDR for baseline FDR of ", baselineFDR, " = ", NDR.rec)
-    if (NDR.rec < 0) NDR.rec = 0
     if(NDR.rec > 0.5){
         message("A high NDR threshold is being recommended by Bambu indicating high levels of novel transcripts, ",
         "limiting the performance of the trained model")

From 22c169c286f8c9d2c5bfc30b28b620884cfed63a Mon Sep 17 00:00:00 2001
From: Andre 
Date: Thu, 5 Dec 2024 11:53:08 +0800
Subject: [PATCH 159/189] Return rcOutDir functionality

---
 R/bambu-assignDist.R   |  1 +
 R/bambu-processReads.R | 40 +++++++++++++++++-----------------------
 R/bambu.R              |  2 --
 3 files changed, 18 insertions(+), 25 deletions(-)

diff --git a/R/bambu-assignDist.R b/R/bambu-assignDist.R
index b82a07ad..1408acc1 100644
--- a/R/bambu-assignDist.R
+++ b/R/bambu-assignDist.R
@@ -5,6 +5,7 @@
 assignReadClasstoTranscripts <- function(readClassList, annotations, isoreParameters, 
                                         verbose, demultiplexed, spatial, 
                                         returnDistTable = FALSE, trackReads = TRUE) {
+    if (is.character(readClassList)) readClassList <- readRDS(file = readClassList)
     metadata(readClassList)$readClassDist <- calculateDistTable(readClassList, annotations, isoreParameters, verbose)
     readClassList = splitReadClassFiles(readClassList)
     readClassDt <- genEquiRCs(metadata(readClassList)$readClassDist, annotations, verbose) 
diff --git a/R/bambu-processReads.R b/R/bambu-processReads.R
index 29555b23..8814ab84 100644
--- a/R/bambu-processReads.R
+++ b/R/bambu-processReads.R
@@ -58,7 +58,6 @@ bambu.processReads <- function(reads, annotations, genomeSequence,
         readClassList <- bplapply(seq_along(reads), function(i) {
             bambu.processReadsByFile(bam.file = reads[i],
             genomeSequence = genomeSequence,annotations = annotations,
-            readClass.outputDir = readClass.outputDir,
             stranded = stranded, min.readCount = min.readCount, 
             fitReadClassModel = fitReadClassModel, min.exonOverlap = min.exonOverlap, 
             defaultModels = defaultModels, returnModel = returnModel, verbose = verbose, 
@@ -69,7 +68,6 @@ bambu.processReads <- function(reads, annotations, genomeSequence,
         readGrgList <- bplapply(seq_along(reads), function(i) {
             bambu.readsByFile(bam.file = reads[i],
             genomeSequence = genomeSequence,annotations = annotations,
-            readClass.outputDir = readClass.outputDir,
             stranded = stranded, min.readCount = min.readCount, 
             fitReadClassModel = fitReadClassModel, min.exonOverlap = min.exonOverlap, 
             defaultModels = defaultModels, returnModel = returnModel, verbose = verbose, 
@@ -90,7 +88,6 @@ bambu.processReads <- function(reads, annotations, genomeSequence,
         readGrgList = do.call(c, readGrgList)    
         mcols(readGrgList)$id <- seq_along(readGrgList) 
         readClassList <- constructReadClasses(readGrgList, genomeSequence = genomeSequence,annotations = annotations,
-            readClass.outputDir = readClass.outputDir,
             stranded = stranded, min.readCount = min.readCount, 
             fitReadClassModel = fitReadClassModel, min.exonOverlap = min.exonOverlap, 
             defaultModels = defaultModels, returnModel = returnModel, verbose = verbose, 
@@ -102,23 +99,20 @@ bambu.processReads <- function(reads, annotations, genomeSequence,
         readClassList = list(readClassList)
     }
         
-    
-
-    # TODO return output
-    # if (!is.null(readClass.outputDir)) {
-    #     readClassFile <- paste0(readClass.outputDir,names(bam.file),
-    #                             "_readClassSe.rds")
-    #     if (file.exists(readClassFile)) {
-    #         show(paste(readClassFile, "exists, will be overwritten"))
-    #         warning(readClassFile, "exists, will be overwritten")
-    #     } else {
-    #         readClassFile <- BiocFileCache::bfcnew(BiocFileCache::BiocFileCache(
-    #             readClass.outputDir, ask = FALSE),
-    #             paste0(names(bam.file),"_readClassSe"), ext = ".rds")
-    #     }
-    #     saveRDS(se, file = readClassFile)
-    #     se <- readClassFile
-    # }
+    if (!is.null(readClass.outputDir)) {
+        for(i in seq_along(readClassList)){
+            readClassFile = "combinedSamples"
+            if(lowMemory){
+                readClassFile <- metadata(readClassList[[i]])$sampleNames
+            }
+            readClassFile <- BiocFileCache::bfcnew(BiocFileCache::BiocFileCache(
+                readClass.outputDir, ask = FALSE),
+                paste0(readClassFile,"_readClassSe"), ext = ".rds")
+            saveRDS(readClassList[[i]], file = readClassFile)
+            readClassList[[i]] <- readClassFile
+        }
+        
+    }
     #TODO don't output list, current there because discovery needs it
     return(readClassList)
 }
@@ -128,7 +122,7 @@ bambu.processReads <- function(reads, annotations, genomeSequence,
 #' @importFrom GenomeInfoDb seqlevels seqlevels<- keepSeqlevels
 #' @noRd
 bambu.processReadsByFile <- function(bam.file, genomeSequence, annotations,
-    readClass.outputDir = NULL, yieldSize = NULL, stranded = FALSE, min.readCount = 2, 
+    yieldSize = NULL, stranded = FALSE, min.readCount = 2, 
     fitReadClassModel = TRUE, min.exonOverlap = 10, defaultModels = NULL, returnModel = FALSE, 
     verbose = FALSE, lowMemory = FALSE, trackReads = FALSE, fusionMode = FALSE, demultiplexed = FALSE, 
     cleanReads = FALSE, dedupUMI = FALSE, index = 0, barcodesToFilter = NULL) {
@@ -220,7 +214,7 @@ bambu.processReadsByFile <- function(bam.file, genomeSequence, annotations,
 #' @importFrom GenomeInfoDb seqlevels seqlevels<- keepSeqlevels
 #' @noRd
 bambu.readsByFile <- function(bam.file, genomeSequence, annotations,
-    readClass.outputDir = NULL, yieldSize = NULL, stranded = FALSE, min.readCount = 2, 
+    yieldSize = NULL, stranded = FALSE, min.readCount = 2, 
     fitReadClassModel = TRUE, min.exonOverlap = 10, defaultModels = NULL, returnModel = FALSE, 
     verbose = FALSE, trackReads = FALSE, fusionMode = FALSE, demultiplexed = FALSE, 
     cleanReads = TRUE, dedupUMI = FALSE, index = 0, barcodesToFilter = NULL) {
@@ -291,7 +285,7 @@ bambu.readsByFile <- function(bam.file, genomeSequence, annotations,
 }
 
 constructReadClasses <- function(readGrgList, genomeSequence, annotations,
-    readClass.outputDir = NULL, stranded = FALSE, min.readCount = 2, 
+    stranded = FALSE, min.readCount = 2, 
     fitReadClassModel = TRUE, min.exonOverlap = 10, defaultModels = NULL, returnModel = FALSE, 
     verbose = FALSE, trackReads = FALSE, fusionMode = FALSE){
     warnings = c() ###TODO
diff --git a/R/bambu.R b/R/bambu.R
index 8205f72b..e6a1f212 100644
--- a/R/bambu.R
+++ b/R/bambu.R
@@ -218,8 +218,6 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL,
   
     if(assignDist){
         message("--- Start calculating equivilance classes ---")
-        if (is.character(readClassList)) readClassList <- list(readRDS(file = readClassList))
-        #if(is.list(readClassList)) readClassList = readClassList[[1]]
         quantData = bplapply(readClassList, FUN = assignReadClasstoTranscripts, 
             annotations = annotations, isoreParameters = isoreParameters, verbose = verbose, 
             demultiplexed = demultiplexed, spatial = spatial, returnDistTable = returnDistTable,

From 4de83925fd9a78f71eeac32c338f1ffa06f6f87a Mon Sep 17 00:00:00 2001
From: Andre 
Date: Thu, 5 Dec 2024 14:23:48 +0800
Subject: [PATCH 160/189] return distTable now returns intermediate distTable

---
 R/bambu-assignDist.R       | 4 ++--
 R/bambu_utilityFunctions.R | 3 ++-
 2 files changed, 4 insertions(+), 3 deletions(-)

diff --git a/R/bambu-assignDist.R b/R/bambu-assignDist.R
index 1408acc1..ef44b127 100644
--- a/R/bambu-assignDist.R
+++ b/R/bambu-assignDist.R
@@ -6,7 +6,7 @@ assignReadClasstoTranscripts <- function(readClassList, annotations, isoreParame
                                         verbose, demultiplexed, spatial, 
                                         returnDistTable = FALSE, trackReads = TRUE) {
     if (is.character(readClassList)) readClassList <- readRDS(file = readClassList)
-    metadata(readClassList)$readClassDist <- calculateDistTable(readClassList, annotations, isoreParameters, verbose)
+    metadata(readClassList)$readClassDist <- calculateDistTable(readClassList, annotations, isoreParameters, verbose, returnDistTable)
     readClassList = splitReadClassFiles(readClassList)
     readClassDt <- genEquiRCs(metadata(readClassList)$readClassDist, annotations, verbose) 
     readClassDt$eqClass.match = match(readClassDt$eqClassById,metadata(readClassList)$eqClassById)
@@ -33,7 +33,7 @@ assignReadClasstoTranscripts <- function(readClassList, annotations, isoreParame
     metadata(quantData)$incompatibleCountMatrix  = metadata(readClassList)$incompatibleCountMatrix 
     metadata(quantData)$sampleNames = metadata(readClassList)$sampleNames 
     if(returnDistTable){
-        metadata(quantData)$distTable = metadata(readClassList)$readClassDist
+        metadata(quantData)$distTable = metadata(metadata(readClassList)$readClassDist)$distTableOld
     }
     if (trackReads){
         metadata(quantData)$readToTranscriptMap = 
diff --git a/R/bambu_utilityFunctions.R b/R/bambu_utilityFunctions.R
index 782b951e..db8a4626 100644
--- a/R/bambu_utilityFunctions.R
+++ b/R/bambu_utilityFunctions.R
@@ -225,13 +225,14 @@ handleWarnings <- function(readClassList, verbose){
 }
 
 #' Calculate the dist table used for Bambu Quantification
-calculateDistTable <- function(readClassList, annotations, isoreParameters, verbose){
+calculateDistTable <- function(readClassList, annotations, isoreParameters, verbose, returnDistTable){
     readClassDist <- isore.estimateDistanceToAnnotations(readClassList, annotations,
                                                             min.exonDistance = isoreParameters[["min.exonDistance"]],
                                                             min.primarySecondaryDist = isoreParameters[['min.primarySecondaryDist']],
                                                             min.primarySecondaryDistStartEnd = isoreParameters[['min.primarySecondaryDistStartEnd2']],
                                                             verbose = verbose)
         metadata(readClassDist)$distTable <- modifyIncompatibleAssignment(metadata(readClassDist)$distTable)
+        if(returnDistTable) metadata(readClassDist)$distTableOld = metadata(readClassDist)$distTable
                 #convert string gene ids into index to save memory
         GENEIDs = factor(unique(mcols(annotations)$GENEID))
         GENEID.i = as.numeric(GENEIDs)

From 03e564b9e039e0051604e7800f952ade9f87abcf Mon Sep 17 00:00:00 2001
From: Andre 
Date: Mon, 16 Dec 2024 09:48:41 +0800
Subject: [PATCH 161/189] lowMemory now processByBam and processByChromosome

---
 R/bambu-processReads.R | 37 ++++++++++++++++++++++++++++---------
 R/bambu.R              | 11 ++++++++---
 2 files changed, 36 insertions(+), 12 deletions(-)

diff --git a/R/bambu-processReads.R b/R/bambu-processReads.R
index 8814ab84..0bd8bc54 100644
--- a/R/bambu-processReads.R
+++ b/R/bambu-processReads.R
@@ -15,7 +15,7 @@
 bambu.processReads <- function(reads, annotations, genomeSequence,
     readClass.outputDir=NULL, yieldSize=1000000, bpParameters, 
     stranded=FALSE, verbose=FALSE, isoreParameters = setIsoreParameters(NULL),
-    lowMemory=FALSE, trackReads = trackReads, fusionMode = fusionMode, 
+    processByChromosome = FALSE, processByBam = TRUE, trackReads = trackReads, fusionMode = fusionMode, 
     demultiplexed = FALSE, cleanReads = FALSE, dedupUMI = FALSE, sampleNames = NULL, barcodesToFilter = NULL) {
     genomeSequence <- checkInputSequence(genomeSequence)
     # ===# create BamFileList object from character #===#
@@ -54,14 +54,14 @@ bambu.processReads <- function(reads, annotations, genomeSequence,
     returnModel = isoreParameters[["returnModel"]]
     min.exonOverlap = isoreParameters[["min.exonOverlap"]]
 
-    if(lowMemory){
+    if(processByBam){
         readClassList <- bplapply(seq_along(reads), function(i) {
             bambu.processReadsByFile(bam.file = reads[i],
             genomeSequence = genomeSequence,annotations = annotations,
             stranded = stranded, min.readCount = min.readCount, 
             fitReadClassModel = fitReadClassModel, min.exonOverlap = min.exonOverlap, 
             defaultModels = defaultModels, returnModel = returnModel, verbose = verbose, 
-            trackReads = trackReads, fusionMode = fusionMode, 
+            processByChromosome = processByChromosome, trackReads = trackReads, fusionMode = fusionMode, 
             demultiplexed = demultiplexed, cleanReads = cleanReads, dedupUMI = dedupUMI, index = 1, barcodesToFilter = barcodesToFilter)},
             BPPARAM = bpParameters)
     } else {
@@ -91,7 +91,7 @@ bambu.processReads <- function(reads, annotations, genomeSequence,
             stranded = stranded, min.readCount = min.readCount, 
             fitReadClassModel = fitReadClassModel, min.exonOverlap = min.exonOverlap, 
             defaultModels = defaultModels, returnModel = returnModel, verbose = verbose, 
-            trackReads = trackReads, fusionMode = fusionMode)
+            processByChromosome = processByChromosome, trackReads = trackReads, fusionMode = fusionMode)
 
         metadata(readClassList)$samples = names(reads)
         metadata(readClassList)$sampleNames = names(reads)
@@ -124,7 +124,7 @@ bambu.processReads <- function(reads, annotations, genomeSequence,
 bambu.processReadsByFile <- function(bam.file, genomeSequence, annotations,
     yieldSize = NULL, stranded = FALSE, min.readCount = 2, 
     fitReadClassModel = TRUE, min.exonOverlap = 10, defaultModels = NULL, returnModel = FALSE, 
-    verbose = FALSE, lowMemory = FALSE, trackReads = FALSE, fusionMode = FALSE, demultiplexed = FALSE, 
+    verbose = FALSE, processByChromosome = FALSE, trackReads = FALSE, fusionMode = FALSE, demultiplexed = FALSE, 
     cleanReads = FALSE, dedupUMI = FALSE, index = 0, barcodesToFilter = NULL) {
     if(verbose) message(names(bam.file)[1])
     readGrgList <- prepareDataFromBam(bam.file[[1]], verbose = verbose, yieldSize = yieldSize, use.names = trackReads, demultiplexed = demultiplexed, cleanReads = cleanReads, dedupUMI = dedupUMI)
@@ -182,9 +182,18 @@ bambu.processReadsByFile <- function(bam.file, genomeSequence, annotations,
     } else {mcols(readGrgList)$sampleID = index}
         
     # construct read classes for each chromosome seperately 
-    se <- lowMemoryConstructReadClasses(readGrgList, genomeSequence, 
+    if(processByChromosome){
+        se <- lowMemoryConstructReadClasses(readGrgList, genomeSequence, 
                                                       annotations, stranded, verbose,bam.file)
+    } else{
+        unlisted_junctions <- unlistIntrons(readGrgList, use.ids = TRUE)
+        uniqueJunctions <- isore.constructJunctionTables(unlisted_junctions, 
+                                                         annotations,genomeSequence, stranded = stranded, verbose = verbose)
+        se <- isore.constructReadClasses(readGrgList, 
+                                              unlisted_junctions, uniqueJunctions, runName = "TODO",
+                                              annotations, stranded, verbose)
 
+    }
 
     metadata(se)$warnings = warnings
     if(trackReads){
@@ -287,12 +296,22 @@ bambu.readsByFile <- function(bam.file, genomeSequence, annotations,
 constructReadClasses <- function(readGrgList, genomeSequence, annotations,
     stranded = FALSE, min.readCount = 2, 
     fitReadClassModel = TRUE, min.exonOverlap = 10, defaultModels = NULL, returnModel = FALSE, 
-    verbose = FALSE, trackReads = FALSE, fusionMode = FALSE){
+    verbose = FALSE, processByChromosome = FALSE, trackReads = FALSE, fusionMode = FALSE){
     warnings = c() ###TODO
-    # construct read classes for each chromosome seperately 
-    se <- lowMemoryConstructReadClasses(readGrgList, genomeSequence, 
+    
+    if(processByChromosome){
+        # construct read classes for each chromosome seperately 
+        se <- lowMemoryConstructReadClasses(readGrgList, genomeSequence, 
                                             annotations, stranded, verbose,"TODO", fusionMode)
+    } else{
+        unlisted_junctions <- unlistIntrons(readGrgList, use.ids = TRUE)
+        uniqueJunctions <- isore.constructJunctionTables(unlisted_junctions, 
+                                                         annotations,genomeSequence, stranded = stranded, verbose = verbose)
+        se <- isore.constructReadClasses(readGrgList, 
+                                              unlisted_junctions, uniqueJunctions, runName = "TODO",
+                                              annotations, stranded, verbose)
 
+    }
     metadata(se)$warnings = warnings
     if(trackReads){
         metadata(se)$readNames = names(readGrgList)
diff --git a/R/bambu.R b/R/bambu.R
index e6a1f212..0471c14b 100644
--- a/R/bambu.R
+++ b/R/bambu.R
@@ -140,17 +140,20 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL,
     assignDist = TRUE, quant = TRUE, stranded = FALSE,  ncore = 1, yieldSize = NULL,  
     trackReads = FALSE, returnDistTable = FALSE, lowMemory = FALSE, 
     fusionMode = FALSE, verbose = FALSE, demultiplexed = FALSE, spatial = NULL, quantData = NULL,
-    sampleNames = NULL, cleanReads = FALSE, dedupUMI = FALSE, barcodesToFilter = NULL, clusters = NULL) {
+    sampleNames = NULL, cleanReads = FALSE, dedupUMI = FALSE, barcodesToFilter = NULL, clusters = NULL,
+    processByChromosome = FALSE, processByBam = TRUE) {
     message(paste0("Running Bambu-v", "3.3.0"))
     if(!is.null(mode)){
         if(mode == "bulk"){
-            lowMemory = TRUE
+            processByChromosome = FALSE
+            processByBam = TRUE
         }
         if(mode == "multiplexed"){
             if(is.null(demultiplex)) demultiplex = TRUE
             cleanReads = TRUE
             opt.em = list(degradationBias = FALSE)
             quant = FALSE
+            processByChromosome = TRUE
         }
         if(mode == "fusion"){
             NDR = 1
@@ -162,6 +165,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL,
             returnDistTable = TRUE
         }
     }
+    if(lowMemory){message("lowMemory has been deprecated and split into processByChromosome and processByBam. Please see Documentation")}
     if(is.null(annotations)) { annotations = GRangesList()
     } else annotations <- checkInputs(annotations, reads,
             readClass.outputDir = rcOutDir, genomeSequence = genome, discovery = discovery, 
@@ -193,7 +197,8 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL,
             readClass.outputDir = rcOutDir, yieldSize = yieldSize, 
             bpParameters = bpParameters, stranded = stranded, verbose = verbose,
             isoreParameters = isoreParameters, trackReads = trackReads, fusionMode = fusionMode, 
-            lowMemory = lowMemory, demultiplexed = demultiplexed,
+            processByChromosome = processByChromosome, processByBam = processByBam, 
+            demultiplexed = demultiplexed,
             sampleNames = sampleNames, cleanReads = cleanReads, dedupUMI = dedupUMI)
     }
 

From fdd3fb03ebdc028b5345ee44f5ab22373362f393 Mon Sep 17 00:00:00 2001
From: Andre 
Date: Mon, 16 Dec 2024 10:23:24 +0800
Subject: [PATCH 162/189] Add lowMemory replacements to documentation and
 importBambuResults

---
 README.md | 18 +++++++++++++-----
 1 file changed, 13 insertions(+), 5 deletions(-)

diff --git a/README.md b/README.md
index f03e31cf..fc7483dd 100755
--- a/README.md
+++ b/README.md
@@ -234,6 +234,11 @@ writeToGTF(se.discoveryOnly.novel, "./output.gtf")
 
 If both quant and discovery are set to FALSE, *bambu* will return an intermediate object see [Storing and using preprocessed files (rcFiles)](#Storing-and-using-preprocessed-files-rcFiles)
 
+To reimport the output of writeBambuOutput() use importBambuResults()
+```rscript
+se <- importBambuResults(path = "/path/to/bambu/output/")
+```
+
 ### Visualization
 You can visualize the novel genes/transcripts using plotBambu function. (Note that the visualization was done by running *bambu* on the three replicates of HepG2 cell line in the SG-NEx project)
 
@@ -476,8 +481,9 @@ se <- bambu(reads = fusionAligned.bam, annotations = fusionAnnotations, genome =
 | discovery | A logical variable indicating whether annotations are to be extended for quantification, defaults to TRUE. |
 | quant | A logical variable indicating whether quantification will be performed, defaults to TRUE. |
 | verbose | A logical variable indicating whether processing messages will be printed. |
-| lowMemory | A logical variable indicating if each input bam file will be processed seperately (TRUE) or all are read in and processed together (FALSE), defaults to TRUE |
-| mode | A string that will set other input arguments ['bulk', 'multiplexed', 'fusion', 'debug']
     bulk - 
        lowMemory = TRUE
    multiplexed - 
        demultiplex = TRUE
        cleanReads = TRUE
        opt.em = list(degradationBias = FALSE)
        quant = FALSE
    fusion - 
        NDR = 1
        fusionMode = TRUE
    debug -
        verbose = TRUE
        trackReads = TRUE
        returnDistTable = TRUE |
+| processByBam | A logical variable indicating if each input bam file will be processed seperately (TRUE) or all are read in and processed together (FALSE), defaults to TRUE |
+| processByChromosome | A logical variable indicating if read classes will be constructed with all reads together (FALSE), or done by chromsome which uses less memory, but provides less information for the junction correction model (TRUE), defaults to FALSE |
+| mode | A string that will set other input arguments ['bulk', 'multiplexed', 'fusion', 'debug']
     bulk - 
        processByBam = TRUE
        processByChromsome = FALSE
    multiplexed - 
        demultiplex = TRUE
        cleanReads = TRUE
        opt.em = list(degradationBias = FALSE)
        quant = FALSE
        processByChromosome = TRUE
    fusion - 
        NDR = 1
        fusionMode = TRUE
    debug -
        verbose = TRUE
        trackReads = TRUE
        returnDistTable = TRUE |
 | demultiplexed | A logical variable indicating whether the input bam file is demultiplexed. The barcode and umi either need to be present in the read name or the $BC and $UG tags, defaults to FALSE. Alternatively a path to a csv file can be provided where column 1 is read names, column 2 is barcodes, and column 3 is UMI. |
 | spatial | A path to the barcode whitelist containing X and Y coordinates, defaults to null. |
 | assignDist | A logical variable indicating whether read class to transcript assignment will be performed, defaults to TRUE. |
@@ -571,9 +577,11 @@ Release date: 2024-October-28
 - Added sampleNames argument
 - Added cleanReads argument
 - Added dedupUMI argument
-- Added clsuters argument
-- Updated lowMemory. The previous lowMemory mode is now always on. The new lowMemory mode is the current implementation, otherwise it will read in all bam files and process them together. 
-- Added importBambuResults
+- Added clusters argument
+- Deprecated lowMemory - This has been replaced by processByChromosome
+- Added processByChomosome (the old memory)
+- Added processByBam argument
+- Added importBambuResults()
 - writeBambuOutput now outputs all information needed to import Bambu results from text files
 - Count outputs are all now in sparse matrix format
 

From 24c5eb9d6accd264df8cc658b129d894929e934b Mon Sep 17 00:00:00 2001
From: Andre 
Date: Tue, 24 Dec 2024 11:07:30 +0800
Subject: [PATCH 163/189] Add more single cell documentation to readme

---
 README.md | 100 ++++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 100 insertions(+)

diff --git a/README.md b/README.md
index fc7483dd..db7ecae7 100755
--- a/README.md
+++ b/README.md
@@ -26,6 +26,7 @@
   - [Modulating the sensitivity of discovery (pre and post analysis)](#Modulating-the-sensitivity-of-discovery-pre-and-post-analysis)
   - [Output](#Output)
   - [Visualization](#Visualization)
+  - [Single-Cell and Spatial](#Single-Cell-and-Spatial)
 - [*bambu* Advanced Options](#Bambu-Advanced-Options)
   - [Using a pretrained model](#Using-a-pretrained-model)
   - [De-novo transcript discovery](#De-novo-transcript-discovery)
@@ -35,6 +36,7 @@
   - [Quantification of gene expression](#Quantification-of-gene-expression)
   - [Including single exons](#Including-single-exons)
   - [Fusion gene/isoform detection](#Fusion-geneisoform-detection)
+  - [Custom single-cell and spatial analysis](#Custom-Single-Cell-and-Spatial)
   - [*bambu* Arguments](#Bambu-Arguments)
   - [Output Description](#Output-Description)
 - [Release History](#Release-History)
@@ -283,6 +285,12 @@ plotBambu(se, type = "heatmap", group.var) # heatmap
 plotBambu(se, type = "pca", group.var) # PCA visualization
 ```
 
+### Single-Cell-and-Spatial
+
+There is a single-cell and spatial pipeline starting from fastq or demultiplexed bamfiles that includes demultiplexing and aligning available here https://github.com/GoekeLab/bambu-singlecell-spatial. We recommend using this pipeline where possible.
+
+For advanced users see the #[Custom single-cell and spatial analysis](#Custom-Single-Cell-and-Spatial) section under advanced options
+
 ### *Bambu* Advanced Options
 Below we include several advanced options and use-cases for *bambu*. We recommend reading and understanding the [paper](https://www.biorxiv.org/content/10.1101/2022.11.14.516358v1) before attempting to use these features.
 
@@ -462,6 +470,98 @@ To use this feature, it is recommended to detect the fusion gene breakpoints usi
 se <- bambu(reads = fusionAligned.bam, annotations = fusionAnnotations, genome = fusionFasta, fusionMode = TRUE)
 ```
 
+### Custom single-cell and spatial
+
+If you want to run Bambu-Clump for single-cell or spatial analysis stand alone and not part of the Bambu-Pipe pipeline we recommend running it in 4 stages which we will describe seperately: Read Class Construction, Transcript Discovery, Read Class Assignment, and EM Quantification. Note that this section will only cover arguments that are different or unique to this analysis.
+
+Read Class Construction:
+
+reads: provided bam files must have barcodes in the read name or in the BC tag. Alternatively a csv file can be provided to demultiplexed mapping the read names to barcodes. For exact requirements see https://github.com/GoekeLab/bambu-singlecell-spatial. 
    
+demultiplexed: must be set to TRUE (or be a barcode map). This will cause bambu to look for barcodes and seperate reads by barcode rather than sample. 
    
+
+Optional:
+
+
+cleanReads: A logical TRUE/FALSE. Chimeric reads in samples can cause issues with barcode assignments. Setting this to TRUE will ensure only the first alignment per barcode is used (We recommend using this). 
    
+sampleNames: A vector of characters assigning names to each sample in the reads argument. By default the sample names are taken from the file names and appended to the barcodes in order to differentiate them. If your sample names are the same across multiple files, but matching barcodes between the samples should be counted seperately, provide them with different sample names using this argument. Similiarly if your samples have different names, but overlapping barcodes should be counted together, give them the same sample name with this argument.  
    
+dedupUMI: A logical TRUE/FALSE.   
    
+
+```rscript
+readClassFile = bambu(reads = samples, annotations = annotations, genome = "$genome", ncore = $params.ncore, discovery = FALSE, quant = FALSE, demultiplexed = barcode_maps, verbose = TRUE, assignDist = FALSE, lowMemory = as.logical("$params.lowMemory"), yieldSize = 10000000, sampleNames = ids, cleanReads = as.logical($cleanReads),  = as.logical($deduplicateUMIs))
+```
+
+Transcript Discovery:
+
+Transript discovery can be run as usual as typically bulk-level discovery is suitable. However cluster-level transcript discovery can be preformed using the clusters argument which can be redone done after clustering. 
+
+```rscript
+extendedAnno = bambu(reads = readClassFile, annotations = annotations, genome = "$genome", ncore = $params.ncore, discovery = TRUE, quant = FALSE, demultiplexed = TRUE, verbose = FALSE, assignDist = FALSE)
+```
+
+Read Class Assignment:
+This step was previously performed together with the quantification, but can be done seperately so that the arguments can be passed to the quantification seperately with different clustering. If you only want barcode level gene counts or unique transcript counts you can stop here and do not need to proceed to the EM quantification.
+
+spatial: This should be a path to your barcode whitelist that also contians the x and y coordinates as extra columns. 
+
+```rscript
+quantData = bambu(reads = readClassFile, annotations = extendedAnno, genome = "$genome", ncore = $params.ncore, discovery = FALSE, quant = FALSE, demultiplexed = TRUE, verbose = FALSE, opt.em = list(degradationBias = FALSE), assignDist = TRUE, spatial = spatial)
+```
+
+EM quantification:
+
+If you plan to run this step with multiple processes we recommend restarting your R instance to ensure that environmental variables do not inflate the memory usage. 
+
+reads: This argument is still mandatory but not needed when performing quantification alone as long as you provide the quantData argument  
    
+quantData:  This is the summerized experiement output from the Read Class Assignment step
    
+clusters:  This is an optional argument which is either a path to a csv containing the barcode to cluster assignments or a list
    
+opt.em = list(degradationBias=TRUE): We recommend including this argument if you are doing barcode level EM quantification to greatly improve runtime with only a small reduction in quantification accuracy. 
+
+```rscript
+#use Seurat to generate clusters from gene counts
+library(Seurat)
+
+clusterCells = function(counts, resolution = 0.8, dim = 15){
+  
+  cellMix <- CreateSeuratObject(counts = counts, 
+                                project = "cellMix", min.cells = 1)#, min.features = 200)
+  #cellMix <- subset(cellMix, subset = nFeature_RNA > nFeature_RNA_threshold & nFeature_RNA < nFeature_RNA_threshold_max)
+  #nFeature_RNA_threshold = 1000, nFeature_RNA_threshold_max = 9000,
+  cellMix <- NormalizeData(cellMix, normalization.method = "LogNormalize", scale.factor = 10000)
+  cellMix <- FindVariableFeatures(cellMix, selection.method = "vst", nfeatures = 2500)
+  all.genes <- rownames(cellMix)
+  cellMix <- ScaleData(cellMix, features = all.genes)
+  npcs = ifelse(ncol(counts)>50, 50, ncol(counts)-1)
+  cellMix <- RunPCA(cellMix, features = VariableFeatures(object = cellMix), npcs = npcs)
+  dim = ifelse(dim >= dim(cellMix@reductions$pca)[2], dim, dim(cellMix@reductions$pca)[2])
+  cellMix <- FindNeighbors(cellMix, dims = 1:dim)
+  cellMix <- FindClusters(cellMix, resolution = resolution)
+  cellMix <- RunUMAP(cellMix, dims = 1:dim)
+  
+  return(cellMix)
+}
+
+quantData.gene = transcriptToGeneExpression(quantData)
+counts = assays(quantData.gene)$counts[,1] #selecting first sample
+cellMix = clusterCells(counts, resolution = resolution) #resolution is dependant on sample. For larger clusters: 0.2-0.6, for higher resolution: 0.8-2
+x = setNames(names(cellMix@active.ident), cellMix@active.ident)
+clusters = splitAsList(unname(x), names(x))
+
+
+
+se = bambu( reads = "placeholder", 
+            annotations = extendedAnno, 
+            genome = "$genome", 
+            quantData = quantDatas, 
+            assignDist = FALSE, 
+            ncore = $params.ncore, 
+            discovery = FALSE, 
+            quant = TRUE, 
+            demultiplexed = TRUE, 
+            verbose = FALSE, 
+            opt.em = list(degradationBias = degBias), 
+            clusters = clusters)
+```
+
 ### *Bambu* Arguments
 
 |argument|description|

From 44519355656664806fc02126a4e5d61636bcdcb9 Mon Sep 17 00:00:00 2001
From: Andre 
Date: Thu, 2 Jan 2025 16:26:24 +0800
Subject: [PATCH 164/189] Fix bugs due to fusion mode on test data

---
 R/bambu-assignDist.R           | 11 +++++++----
 R/bambu.R                      |  1 +
 R/readWrite.R                  | 23 ++++++++++++++---------
 R/transcriptToGeneExpression.R | 12 +++++++-----
 4 files changed, 29 insertions(+), 18 deletions(-)

diff --git a/R/bambu-assignDist.R b/R/bambu-assignDist.R
index ef44b127..81416f02 100644
--- a/R/bambu-assignDist.R
+++ b/R/bambu-assignDist.R
@@ -14,7 +14,6 @@ assignReadClasstoTranscripts <- function(readClassList, annotations, isoreParame
     readClassDt = readClassDt %>% group_by(eqClassId, gene_sid) %>% 
         mutate(multi_align = length(unique(txid))>1) %>% ungroup() %>% mutate(aval = 1) %>%
         data.table()
-
     #return non-em counts
     ColData = generateColData(colnames(metadata(readClassList)$countMatrix), clusters = NULL, demultiplexed, spatial)
     quantData <- SummarizedExperiment(assays = SimpleList(
@@ -76,9 +75,13 @@ generateNonUniqueCounts <- function(readClassDt, countMatrix, annotations){
     x = readClassDt %>% filter(multi_align & !is.na(eqClass.match))
     x = x %>% distinct(eqClassId, .keep_all = TRUE)
     nonuniqueCounts = countMatrix[x$eqClass.match,, drop = FALSE]
-    if(nrow(x)>1){
-    nonuniqueCounts.gene = sparse.model.matrix(~ factor(x$gene_sid) - 1)
-    nonuniqueCounts = t(nonuniqueCounts.gene) %*% nonuniqueCounts
+    if(nrow(x)>1 & length(unique(x$gene_sid))>1){
+        nonuniqueCounts.gene = sparse.model.matrix(~ factor(x$gene_sid) - 1)
+        nonuniqueCounts = t(nonuniqueCounts.gene) %*% nonuniqueCounts
+    } else{
+        warning("The factor variable 'gene_sid' has only one level. Adjusting output.")
+        nonuniqueCounts.gene = Matrix(1, nrow = nrow(x), ncol = 1, sparse = TRUE)
+        nonuniqueCounts = t(nonuniqueCounts.gene) %*% nonuniqueCounts
     }
     #covert ids into gene ids
     geneids = as.numeric(levels(factor(x$gene_sid)))
diff --git a/R/bambu.R b/R/bambu.R
index 0471c14b..466ef206 100644
--- a/R/bambu.R
+++ b/R/bambu.R
@@ -268,6 +268,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL,
                 }
             }
             countsSeCompressed <- bplapply(iter, FUN = function(i){
+                i = i[i %in% colnames(metadata(quantData_i)$countMatrix)]
                 countMatrix = unname(metadata(quantData_i)$countMatrix[,i])
                 incompatibleCountMatrix = unname(metadata(quantData_i)$incompatibleCountMatrix[,i])
                 if(!is.null(dim(countMatrix))){
diff --git a/R/readWrite.R b/R/readWrite.R
index 711221d6..cd0bdfcd 100644
--- a/R/readWrite.R
+++ b/R/readWrite.R
@@ -41,9 +41,11 @@ writeBambuOutput <- function(se, path, prefix = "", outputExtendedAnno = TRUE,
         print(d)
         }
         #write incompatible counts
-        estimates = metadata(se)$incompatibleCounts
-        estimatesfn <- paste(outdir, prefix, "incompatibleCounts.mtx", sep = "")
-            Matrix::writeMM(estimates, estimatesfn)
+        if(!is.null(metadata(se)$incompatibleCounts)){
+            estimates = metadata(se)$incompatibleCounts
+            estimatesfn <- paste(outdir, prefix, "incompatibleCounts.mtx", sep = "")
+                Matrix::writeMM(estimates, estimatesfn)
+        }
         seGene <- transcriptToGeneExpression(se)
         writeCountsOutput(seGene, varname='counts', feature='gene',outdir, prefix)
         #utils::write.table(paste0(colnames(se), "-1"), file = paste0(outdir, "barcodes.tsv"), quote = FALSE, row.names = FALSE, col.names = FALSE)
@@ -68,9 +70,11 @@ writeBambuOutput <- function(se, path, prefix = "", outputExtendedAnno = TRUE,
                     writeCountsOutput(se, varname=d,
                                 feature='transcript',outdir=paste0(outdir, sampleName,"/"), prefix)
                 }
-                estimates = metadata(se)$incompatibleCounts
-                estimatesfn <- paste(outdir, "/", sampleName,"/", prefix, "incompatibleCounts.mtx", sep = "")
-                    Matrix::writeMM(estimates, estimatesfn)
+                if(!is.null(metadata(se)$incompatibleCounts)){
+                    estimates = metadata(se)$incompatibleCounts
+                    estimatesfn <- paste(outdir, "/", sampleName,"/", prefix, "incompatibleCounts.mtx", sep = "")
+                        Matrix::writeMM(estimates, estimatesfn)
+                }
                 seGene <- transcriptToGeneExpression(se)
                 writeCountsOutput(seGene, varname='counts', feature='gene',paste0(outdir, sampleName,"/"), prefix)
                 utils::write.table(colData(se), file = paste0(outdir, "/", sampleName, "/", prefix, "sampleData.tsv"), 
@@ -86,7 +90,6 @@ writeBambuOutput <- function(se, path, prefix = "", outputExtendedAnno = TRUE,
 #' @noRd
 writeCountsOutput <- function(se, varname = "counts",
                               feature = "transcript", outdir, prefix){
-  
     if(!is(assays(se)[[varname]], "sparseMatrix")){
       estimatesfn <- paste(outdir, prefix, varname,"_",feature,".txt", sep = "")
       estimates <- data.table(as.data.frame(assays(se)[[varname]]),
@@ -98,7 +101,6 @@ writeCountsOutput <- function(se, varname = "counts",
       }else{
         setnames(estimates, "rn","GENEID")
       } 
-      
       utils::write.table(estimates, file = estimatesfn, sep = "\t", quote = FALSE, row.names = FALSE)
       
     } else{
@@ -326,7 +328,10 @@ importBambuResults <- function(path, prefixes = NA){
     CPM = readMM(paste0(path, "/CPM_transcript.mtx"))
     fullLengthCounts = readMM(paste0(path, "/fullLengthCounts_transcript.mtx"))
     uniqueCounts = readMM(paste0(path, "/uniqueCounts_transcript.mtx"))
-    incompatibleCounts = readMM(paste0(path, "/incompatibleCounts.mtx"))
+    incompatibleCounts = NULL
+    if(file.exists(paste0(path, "/incompatibleCounts.mtx"))){
+        incompatibleCounts = readMM(paste0(path, "/incompatibleCounts.mtx"))
+    }
     barcodes = read.table(paste0(path, "/barcodes.tsv"))
     geneIds = read.table(paste0(path, "/genes.tsv"))
     txIds = read.table(paste0(path, "/txANDgenes.tsv"))
diff --git a/R/transcriptToGeneExpression.R b/R/transcriptToGeneExpression.R
index 83507853..7ad12076 100644
--- a/R/transcriptToGeneExpression.R
+++ b/R/transcriptToGeneExpression.R
@@ -16,12 +16,14 @@ transcriptToGeneExpression <- function(se) {
     rowDataSe <- as.data.table(rowData(se))
     
     counts  = fac2sparse(rowData(se)$GENEID) %*% counts
-    incompatibleCounts <- metadata(se)$incompatibleCounts
-    if("nonuniqueCounts" %in% names(metadata(se))){
-        incompatibleCounts = incompatibleCounts + metadata(se)$nonuniqueCounts
+    if(!is.null(metadata(se)$incompatibleCounts)){
+        incompatibleCounts <- metadata(se)$incompatibleCounts
+        if("nonuniqueCounts" %in% names(metadata(se))){
+            incompatibleCounts = incompatibleCounts + metadata(se)$nonuniqueCounts
+        }
+        incompatibleCounts = Matrix(incompatibleCounts[match(rownames(counts), rownames(incompatibleCounts)),], sparse = TRUE)
+        counts = counts + incompatibleCounts
     }
-    incompatibleCounts = incompatibleCounts[match(rownames(counts), rownames(incompatibleCounts)),]
-    counts = counts + incompatibleCounts
     counts.total = colSums(counts)
     counts.total[counts.total==0] = 1
     counts.CPM = counts/counts.total * 10^6

From 5ca20efeade3a944e311fb904f411cc562626862 Mon Sep 17 00:00:00 2001
From: Chen Ying 
Date: Thu, 9 Jan 2025 11:19:17 +0800
Subject: [PATCH 165/189] fix library load warnings related to unname and
 expand function

---
 NAMESPACE | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/NAMESPACE b/NAMESPACE
index 4dcac7e6..3adb4e37 100755
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -75,8 +75,8 @@ import(data.table, except=c(last, first, shift, second, between))
 import(dplyr, except=c(last, first, desc, union, setdiff, intersect, slice))
 import(IRanges, except=c(slice, collapse, setdiff, intersect,cor))
 import(SummarizedExperiment)
-import(S4Vectors, except=c(rename, setequal, setdiff, intersect,cor))
+import(Matrix)
+import(S4Vectors, except=c(rename, setequal, setdiff, intersect,cor, unname, expand))
 useDynLib(bambu, .registration = TRUE)
 import(xgboost)
-import(Matrix)
 import(BSgenome)

From 47704b6f88b1865432d67a47e1838b116c367f6e Mon Sep 17 00:00:00 2001
From: Chen Ying 
Date: Thu, 9 Jan 2025 11:20:12 +0800
Subject: [PATCH 166/189] bug fix for 0 value quantification

---
 R/bambu.R | 14 ++++++++------
 1 file changed, 8 insertions(+), 6 deletions(-)

diff --git a/R/bambu.R b/R/bambu.R
index 466ef206..951c7fba 100644
--- a/R/bambu.R
+++ b/R/bambu.R
@@ -228,6 +228,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL,
             demultiplexed = demultiplexed, spatial = spatial, returnDistTable = returnDistTable,
             trackReads = trackReads,
             BPPARAM = bpParameters)                 
+        print(as.numeric(assays(quantData[[1]])$counts))
         if (!quant) return(quantData)
     }
 
@@ -247,7 +248,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL,
         for(i in seq_along(quantData)){
             quantData_i = quantData[[i]]
             #load in the barcode clustering from file if provided
-            iter = seq_len(ncol(metadata(quantData_i)$countMatrix))
+            iter = seq_len(ncol(metadata(quantData_i)$countMatrix)) # iter is integer
             if(!is.null(clusters)){
                 if(!is.list(clusters)){
                     clusterMaps = NULL
@@ -267,13 +268,14 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL,
                     }else(iter = do.call(c,clusters))
                 }
             }
-            countsSeCompressed <- bplapply(iter, FUN = function(i){
-                i = i[i %in% colnames(metadata(quantData_i)$countMatrix)]
-                countMatrix = unname(metadata(quantData_i)$countMatrix[,i])
-                incompatibleCountMatrix = unname(metadata(quantData_i)$incompatibleCountMatrix[,i])
+            countsSeCompressed <- bplapply(iter, FUN = function(j){ # previous i changed to j to avoid duplicated assignment 
+                #i = iter[i %in% colnames(metadata(quantData_i)$countMatrix)] #bug, after assignment, i become emptyprint(i)
+                
+                countMatrix = unname(metadata(quantData_i)$countMatrix[,j]) # same here 
+                incompatibleCountMatrix = unname(metadata(quantData_i)$incompatibleCountMatrix[,j]) # same here
                 if(!is.null(dim(countMatrix))){
                     countMatrix = rowSums(countMatrix)
-                    incompatibleCountMatrix = rowSums(metadata(quantData_i)$incompatibleCountMatrix[,i])
+                    incompatibleCountMatrix = rowSums(metadata(quantData_i)$incompatibleCountMatrix[,j]) # same here
                 }
                 return(bambu.quantify(readClassDt = metadata(quantData_i)$readClassDt, countMatrix = countMatrix, 
                                             incompatibleCountMatrix = data.table(GENEID.i = as.numeric(rownames(metadata(quantData_i)$incompatibleCountMatrix)), counts = incompatibleCountMatrix),

From 314ec29c960fcb5e8df83282b024fc197a0a3ee1 Mon Sep 17 00:00:00 2001
From: Chen Ying 
Date: Thu, 9 Jan 2025 11:34:28 +0800
Subject: [PATCH 167/189] remove print line

---
 R/bambu.R | 2 --
 1 file changed, 2 deletions(-)

diff --git a/R/bambu.R b/R/bambu.R
index 951c7fba..7f266913 100644
--- a/R/bambu.R
+++ b/R/bambu.R
@@ -228,7 +228,6 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL,
             demultiplexed = demultiplexed, spatial = spatial, returnDistTable = returnDistTable,
             trackReads = trackReads,
             BPPARAM = bpParameters)                 
-        print(as.numeric(assays(quantData[[1]])$counts))
         if (!quant) return(quantData)
     }
 
@@ -270,7 +269,6 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL,
             }
             countsSeCompressed <- bplapply(iter, FUN = function(j){ # previous i changed to j to avoid duplicated assignment 
                 #i = iter[i %in% colnames(metadata(quantData_i)$countMatrix)] #bug, after assignment, i become emptyprint(i)
-                
                 countMatrix = unname(metadata(quantData_i)$countMatrix[,j]) # same here 
                 incompatibleCountMatrix = unname(metadata(quantData_i)$incompatibleCountMatrix[,j]) # same here
                 if(!is.null(dim(countMatrix))){

From 051480c0c73f198f3ac967f3a65f7ffb295f0cb9 Mon Sep 17 00:00:00 2001
From: SuiYue-2308 
Date: Tue, 14 Jan 2025 10:19:03 +0000
Subject: [PATCH 168/189] min.txScore.singleExon bug fix

---
 R/bambu-extendAnnotations-utilityCombine.R | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/R/bambu-extendAnnotations-utilityCombine.R b/R/bambu-extendAnnotations-utilityCombine.R
index dc58b69e..48d11844 100644
--- a/R/bambu-extendAnnotations-utilityCombine.R
+++ b/R/bambu-extendAnnotations-utilityCombine.R
@@ -19,7 +19,7 @@ isore.combineTranscriptCandidates <- function(readClassList,
         min.readCount, min.readFractionByGene, 
         min.txScore.multiExon, min.txScore.singleExon, verbose) %>% data.table()
     combinedSplicedTranscripts[,confidenceType := "highConfidenceJunctionReads"]
-    if (min.txScore.singleExon < 1) {return(combinedSplicedTranscripts)}
+    if (min.txScore.singleExon == 1) {return(combinedSplicedTranscripts)}
     combinedUnsplicedTranscripts <- 
         combineUnsplicedTranscriptModels(readClassList, bpParameters, 
         stranded, min.readCount, min.readFractionByGene, 

From 8bd703ca7ccdd85e157dc53d60ee735fa27a6de1 Mon Sep 17 00:00:00 2001
From: Chen Ying 
Date: Mon, 20 Jan 2025 10:42:58 +0800
Subject: [PATCH 169/189] fix barcodesToFilter not working bug

---
 R/bambu-processReads.R | 9 ++++-----
 R/bambu.R              | 3 ++-
 2 files changed, 6 insertions(+), 6 deletions(-)

diff --git a/R/bambu-processReads.R b/R/bambu-processReads.R
index 0bd8bc54..e7a65a6c 100644
--- a/R/bambu-processReads.R
+++ b/R/bambu-processReads.R
@@ -54,7 +54,7 @@ bambu.processReads <- function(reads, annotations, genomeSequence,
     returnModel = isoreParameters[["returnModel"]]
     min.exonOverlap = isoreParameters[["min.exonOverlap"]]
 
-    if(processByBam){
+    if(processByBam){ # bulk mode
         readClassList <- bplapply(seq_along(reads), function(i) {
             bambu.processReadsByFile(bam.file = reads[i],
             genomeSequence = genomeSequence,annotations = annotations,
@@ -64,7 +64,7 @@ bambu.processReads <- function(reads, annotations, genomeSequence,
             processByChromosome = processByChromosome, trackReads = trackReads, fusionMode = fusionMode, 
             demultiplexed = demultiplexed, cleanReads = cleanReads, dedupUMI = dedupUMI, index = 1, barcodesToFilter = barcodesToFilter)},
             BPPARAM = bpParameters)
-    } else {
+    } else { # single cell mode 
         readGrgList <- bplapply(seq_along(reads), function(i) {
             bambu.readsByFile(bam.file = reads[i],
             genomeSequence = genomeSequence,annotations = annotations,
@@ -74,7 +74,6 @@ bambu.processReads <- function(reads, annotations, genomeSequence,
             trackReads = trackReads, fusionMode = fusionMode, 
             demultiplexed = demultiplexed, cleanReads = cleanReads, dedupUMI = dedupUMI, index = i, barcodesToFilter = barcodesToFilter)},
             BPPARAM = bpParameters)
-        
         sampleNames = as.numeric(as.factor(sampleNames))
         for(i in seq_along(readGrgList)){
             if(!isFALSE(demultiplexed)){
@@ -92,7 +91,6 @@ bambu.processReads <- function(reads, annotations, genomeSequence,
             fitReadClassModel = fitReadClassModel, min.exonOverlap = min.exonOverlap, 
             defaultModels = defaultModels, returnModel = returnModel, verbose = verbose, 
             processByChromosome = processByChromosome, trackReads = trackReads, fusionMode = fusionMode)
-
         metadata(readClassList)$samples = names(reads)
         metadata(readClassList)$sampleNames = names(reads)
         if(!isFALSE(demultiplexed))metadata(readClassList)$samples =  levels(mcols(readGrgList)$BC)
@@ -130,7 +128,8 @@ bambu.processReadsByFile <- function(bam.file, genomeSequence, annotations,
     readGrgList <- prepareDataFromBam(bam.file[[1]], verbose = verbose, yieldSize = yieldSize, use.names = trackReads, demultiplexed = demultiplexed, cleanReads = cleanReads, dedupUMI = dedupUMI)
     if(verbose) message(paste0("Number of alignments/reads: ",length(readGrgList)))
     warnings = c()
-    if(!is.null(barcodesToFilter) & demultiplexed){ readGrgList = readGrgList[!mcols(readGrgList)$CB %in% barcodesToFilter]}
+    if(!is.null(barcodesToFilter) & demultiplexed)
+        readGrgList = readGrgList[!(mcols(readGrgList)$BC %in% barcodesToFilter)]
     warnings = seqlevelCheckReadsAnnotation(readGrgList, annotations)
     if(verbose & length(warnings) > 0) warning(paste(warnings,collapse = "\n"))
     #check seqlevels for consistency, drop ranges not present in genomeSequence
diff --git a/R/bambu.R b/R/bambu.R
index 7f266913..b54eaa74 100644
--- a/R/bambu.R
+++ b/R/bambu.R
@@ -199,7 +199,8 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL,
             isoreParameters = isoreParameters, trackReads = trackReads, fusionMode = fusionMode, 
             processByChromosome = processByChromosome, processByBam = processByBam, 
             demultiplexed = demultiplexed,
-            sampleNames = sampleNames, cleanReads = cleanReads, dedupUMI = dedupUMI)
+            sampleNames = sampleNames, cleanReads = cleanReads, dedupUMI = dedupUMI,
+            barcodesToFilter = barcodesToFilter)
     }
 
   #warnings = handleWarnings(readClassList, verbose)

From b907925d5015f29fbd32f48e1550a9f654f6be6e Mon Sep 17 00:00:00 2001
From: Chen Ying 
Date: Mon, 20 Jan 2025 11:02:34 +0800
Subject: [PATCH 170/189] fix typo in main function

---
 R/bambu.R | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/R/bambu.R b/R/bambu.R
index b54eaa74..18047be9 100644
--- a/R/bambu.R
+++ b/R/bambu.R
@@ -149,7 +149,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL,
             processByBam = TRUE
         }
         if(mode == "multiplexed"){
-            if(is.null(demultiplex)) demultiplex = TRUE
+            if(is.null(demultiplexed)) demultiplexed = TRUE
             cleanReads = TRUE
             opt.em = list(degradationBias = FALSE)
             quant = FALSE

From 3a9e06a1a3d715916d8a87593b5d2f5b8d4fdeb6 Mon Sep 17 00:00:00 2001
From: Chen Ying 
Date: Mon, 20 Jan 2025 11:38:21 +0800
Subject: [PATCH 171/189] add documentation for barcodesToFilter argument and
 update the formats for some paragraphs

---
 README.md | 90 ++++++++++++++++++++++++++++++++-----------------------
 1 file changed, 52 insertions(+), 38 deletions(-)

diff --git a/README.md b/README.md
index db7ecae7..956700f7 100755
--- a/README.md
+++ b/README.md
@@ -27,7 +27,7 @@
   - [Output](#Output)
   - [Visualization](#Visualization)
   - [Single-Cell and Spatial](#Single-Cell-and-Spatial)
-- [*bambu* Advanced Options](#Bambu-Advanced-Options)
+  - [*bambu* Advanced Options](#Bambu-Advanced-Options)
   - [Using a pretrained model](#Using-a-pretrained-model)
   - [De-novo transcript discovery](#De-novo-transcript-discovery)
   - [Storing and using preprocessed files (rcFiles)](#Storing-and-using-preprocessed-files-rcFiles)
@@ -287,7 +287,7 @@ plotBambu(se, type = "pca", group.var) # PCA visualization
 
 ### Single-Cell-and-Spatial
 
-There is a single-cell and spatial pipeline starting from fastq or demultiplexed bamfiles that includes demultiplexing and aligning available here https://github.com/GoekeLab/bambu-singlecell-spatial. We recommend using this pipeline where possible.
+There is a single-cell and spatial pipeline starting from fastq or demultiplexed bam files that include demultiplexing and aligning available here https://github.com/GoekeLab/bambu-singlecell-spatial. We recommend using this pipeline where possible.
 
 For advanced users see the #[Custom single-cell and spatial analysis](#Custom-Single-Cell-and-Spatial) section under advanced options
 
@@ -303,13 +303,13 @@ se <- bambu(reads = test.bam, annotations = annotations, genome = fa.file, opt.d
 ```
 The default pretrained model was trained on SGNex_HepG2_directRNA_replicate5_run1 and has the following characteristics:
 
-Genome: Homo_sapiens.GRCh38.dna_sm.primary_assembly 
    
-Annotations: Homo_sapiens.GRCh38.91
    
-Read count:  7,861,846
    
-Technology: Nanopore (ONT)
    
-Library preparation: directRNA
    
-Base Calling Accuracy: 79%
    
-Average Read Length: 1093
    
+**Genome**: Homo_sapiens.GRCh38.dna_sm.primary_assembly 
    
+**Annotations**: Homo_sapiens.GRCh38.91
    
+**Read count**:  7,861,846
    
+**Technology**: Nanopore (ONT)
    
+**Library preparation**: directRNA
    
+**Base Calling Accuracy**: 79%
    
+**Average Read Length**: 1093
    
 
 We have found the pretrained model works successfully across species borders (on Arabidopsis thaliana) and on different technologies (PacBio), with only small decreases in performance compared to using a sample specific model. The pretrained model is not always effective in samples with large differences in sequencing quality or if the library preparation results in biases in the overall structure of the transcriptome. In this case, we would recommend training a new model using similar data from a different sample that has quality reference annotations (See [Training a model on another species/dataset and applying it](#Training-a-model-on-another-speciesdataset-and-applying-it)).
 
@@ -368,7 +368,7 @@ rowData(se[[1]])
 |readCount.posStrand|The number of reads assigned to this read class that aligned to the positive strand|
 |intronStarts|A comma separated character vector of intron start coordinates|
 |intronEnds|A comma separated character vector of intron end coordinates|
-|confidenceType|Category of confidence: 
     **highConfidenceJunctionReads** - the read class contain no low confidence junctions 
     **lowConfidenceJunctionReads** - the read class contains low confidence junctions 
     **unsplicedWithin** - single exon read class that is within the exon boundaries of an annotation 
     **unsplicedNew** - single exon read class that does not fully overlap with annotated exons|
+|confidenceType|Category of confidence: 
     **highConfidenceJunctionReads** - the read class contain no low confidence junctions 
     **lowConfidenceJunctionReads** - the read class contains low confidence junctions 
     **unsplicedWithin** - single exon read class that is within the exon boundaries of an annotation 
     **unsplicedNew** - single exon read class that does not fully overlap with annotated exons|
 |readCount|The number of reads assigned to this read class|
 |readId *only present when trackReads = TRUE|An integer list of bambu internal read ids that belong to the read class. (See the metadata of the object for full read names)|
 |GENEID|The gene ID the transcript is associated with|
@@ -474,23 +474,27 @@ se <- bambu(reads = fusionAligned.bam, annotations = fusionAnnotations, genome =
 
 If you want to run Bambu-Clump for single-cell or spatial analysis stand alone and not part of the Bambu-Pipe pipeline we recommend running it in 4 stages which we will describe seperately: Read Class Construction, Transcript Discovery, Read Class Assignment, and EM Quantification. Note that this section will only cover arguments that are different or unique to this analysis.
 
-Read Class Construction:
+#### Read Class Construction:
 
-reads: provided bam files must have barcodes in the read name or in the BC tag. Alternatively a csv file can be provided to demultiplexed mapping the read names to barcodes. For exact requirements see https://github.com/GoekeLab/bambu-singlecell-spatial. 
    
-demultiplexed: must be set to TRUE (or be a barcode map). This will cause bambu to look for barcodes and seperate reads by barcode rather than sample. 
    
+**reads**: provided bam files must have barcodes in the read name or in the BC tag. Alternatively a csv file can be provided to demultiplexed mapping the read names to barcodes. For exact requirements see https://github.com/GoekeLab/bambu-singlecell-spatial.
    
+
+**demultiplexed**: must be set to TRUE (or be a barcode map). This will cause bambu to look for barcodes and seperate reads by barcode rather than sample. 
    
 
 Optional:
 
+**cleanReads**: A logical TRUE/FALSE. Chimeric reads in samples can cause issues with barcode assignments. Setting this to TRUE will ensure only the first alignment per barcode is used (We recommend using this). 
    
+
+**sampleNames**: A vector of characters assigning names to each sample in the reads argument. By default the sample names are taken from the file names and appended to the barcodes in order to differentiate them. If your sample names are the same across multiple files, but matching barcodes between the samples should be counted seperately, provide them with different sample names using this argument. Similiarly if your samples have different names, but overlapping barcodes should be counted together, give them the same sample name with this argument.  
    
 
-cleanReads: A logical TRUE/FALSE. Chimeric reads in samples can cause issues with barcode assignments. Setting this to TRUE will ensure only the first alignment per barcode is used (We recommend using this). 
    
-sampleNames: A vector of characters assigning names to each sample in the reads argument. By default the sample names are taken from the file names and appended to the barcodes in order to differentiate them. If your sample names are the same across multiple files, but matching barcodes between the samples should be counted seperately, provide them with different sample names using this argument. Similiarly if your samples have different names, but overlapping barcodes should be counted together, give them the same sample name with this argument.  
    
-dedupUMI: A logical TRUE/FALSE.   
    
+**dedupUMI**: A logical TRUE/FALSE.   
    
+
+**barcodesToFilter**: A string vector indicating barcodes to be filtered out.  
     
 
 ```rscript
-readClassFile = bambu(reads = samples, annotations = annotations, genome = "$genome", ncore = $params.ncore, discovery = FALSE, quant = FALSE, demultiplexed = barcode_maps, verbose = TRUE, assignDist = FALSE, lowMemory = as.logical("$params.lowMemory"), yieldSize = 10000000, sampleNames = ids, cleanReads = as.logical($cleanReads),  = as.logical($deduplicateUMIs))
+readClassFile = bambu(reads = samples, annotations = annotations, genome = "$genome", ncore = $params.ncore, discovery = FALSE, quant = FALSE, demultiplexed = barcode_maps, verbose = TRUE, assignDist = FALSE, lowMemory = as.logical("$params.lowMemory"), yieldSize = 10000000, sampleNames = ids, cleanReads = as.logical($cleanReads), dedupUMI = as.logical($deduplicateUMIs))
 ```
 
-Transcript Discovery:
+#### Transcript Discovery:
 
 Transript discovery can be run as usual as typically bulk-level discovery is suitable. However cluster-level transcript discovery can be preformed using the clusters argument which can be redone done after clustering. 
 
@@ -498,23 +502,27 @@ Transript discovery can be run as usual as typically bulk-level discovery is sui
 extendedAnno = bambu(reads = readClassFile, annotations = annotations, genome = "$genome", ncore = $params.ncore, discovery = TRUE, quant = FALSE, demultiplexed = TRUE, verbose = FALSE, assignDist = FALSE)
 ```
 
-Read Class Assignment:
+#### Read Class Assignment:
+
 This step was previously performed together with the quantification, but can be done seperately so that the arguments can be passed to the quantification seperately with different clustering. If you only want barcode level gene counts or unique transcript counts you can stop here and do not need to proceed to the EM quantification.
 
-spatial: This should be a path to your barcode whitelist that also contians the x and y coordinates as extra columns. 
+**spatial**: This should be a path to your barcode whitelist that also contians the x and y coordinates as extra columns. 
 
 ```rscript
 quantData = bambu(reads = readClassFile, annotations = extendedAnno, genome = "$genome", ncore = $params.ncore, discovery = FALSE, quant = FALSE, demultiplexed = TRUE, verbose = FALSE, opt.em = list(degradationBias = FALSE), assignDist = TRUE, spatial = spatial)
 ```
 
-EM quantification:
+#### EM quantification:
 
 If you plan to run this step with multiple processes we recommend restarting your R instance to ensure that environmental variables do not inflate the memory usage. 
 
-reads: This argument is still mandatory but not needed when performing quantification alone as long as you provide the quantData argument  
    
-quantData:  This is the summerized experiement output from the Read Class Assignment step
    
-clusters:  This is an optional argument which is either a path to a csv containing the barcode to cluster assignments or a list
    
-opt.em = list(degradationBias=TRUE): We recommend including this argument if you are doing barcode level EM quantification to greatly improve runtime with only a small reduction in quantification accuracy. 
+**reads**: This argument is still mandatory but not needed when performing quantification alone as long as you provide the quantData argument  
    
+
+**quantData**:  This is the summerized experiement output from the Read Class Assignment step
    
+
+**clusters**:  This is an optional argument which is either a path to a csv containing the barcode to cluster assignments or a list
    
+
+**opt.em = list(degradationBias=FALSE)**: We recommend including this argument if you are doing barcode level EM quantification to greatly improve runtime with only a small reduction in quantification accuracy. 
 
 ```rscript
 #use Seurat to generate clusters from gene counts
@@ -558,7 +566,7 @@ se = bambu( reads = "placeholder",
             quant = TRUE, 
             demultiplexed = TRUE, 
             verbose = FALSE, 
-            opt.em = list(degradationBias = degBias), 
+            opt.em = list(degradationBias = FALSE), 
             clusters = clusters)
 ```
 
@@ -574,16 +582,14 @@ se = bambu( reads = "placeholder",
 | ncore | specifying number of cores used when parallel processing is used, defaults to 1. |
 | NDR | specifying the maximum NDR rate to novel transcript output among detected transcripts, defaults to 0.1 |
 | yieldSize | see Rsamtools. |
-| opt.discovery | A list of controlling parameters for isoform reconstruction process:  
     **prefix** specifying prefix for new gene Ids (genePrefix.number), defaults to empty 
     **remove.subsetTx** indicating whether filter to remove read classes which are a subset of known transcripts, defaults to TRUE 
     **min.readCount** specifying minimun read count to consider a read class valid in a sample, defaults to 2 
     **min.readFractionByGene** specifying minimum relative read count per gene, highly expressed genes will have many high read count low relative abundance transcripts that can be filtered, defaults to 0.05 
     **min.sampleNumber** specifying minimum sample number with minimum read count, gene read proportion, and TPS, defaults to 1 
     **min.exonDistance** specifying minimum distance to known transcript to be considered valid as new, defaults to 35bp 
     **min.exonOverlap** specifying minimum number of bases shared with annotation to be assigned to the same gene id, defaults to 10bp 
     **min.primarySecondaryDist** specifying the minimum number of distance threshold between a read class and the annotations internal exons. Read classes with distances less than the threshold are not annotated as novel and counted with the annotations for quantification, defaults to 5bp 
     **min.primarySecondaryDistStartEnd1** specifying the minimum number of distance threshold between a read class and the annotations start/end exons. Read classes with distances less than the threshold are not annotated as novel, defaults to 5bp 
     **min.primarySecondaryDistStartEnd2** specifying the minimum number of distance threshold between a read class and the annotations start/end exons. Read classes with distances less than the threshold are counted with the annotations, defaults to 5bp 
     **min.txScore.multiExon** specifying the minimum transcript probility score threshold for multi-exon transcripts for min.sampleNumber, defaults to 0 
     **min.txScore.singleExon** specifying the minimum transcript probability score threshold for single-exon transcripts for min.sampleNumber 
     **fitReadClassModel** a boolean specifying if bambu should train a model on each sample. If set to false bambu will use the default model for ranking novel transcripts. defaults to TRUE 
     **defaultModels** a bambu trained model object that bambu will use when fitReadClassModel==FALSE or the data is not suitable for training, defaults to the pretrained model in the *bambu* package 
     **returnModel** a boolean specifying if bambu will output the model it trained on the data, defaults to FALSE 
     **baselineFDR** a value between 0-1. Bambu uses this FDR on the trained model to recommend an equivilent NDR threshold to be used for the sample. By default, a baseline FDR of 0.1 is used. This does not impact the analysis if an NDR is set. 
     **min.readFractionByEqClass** indicating the minimum relative read count of a subset transcript compared to all superset transcripts (ie the relative read count within the minimum equivalent class). This filter is applied on the set of annotations across all samples using the total read count, this is not a per-sample filter. Please use with  caution. defaults to 0 |
-| opt.em | A list of controlling parameters for quantification algorithm estimation process: 
     **maxiter** specifying maximum number of run iterations, defaults to 10000 
     **degradationBias** correcting for degradation bias, defaults to TRUE 
     **conv** specifying the covergence threshold control, defaults to 0.0001 
     **minvalue** specifying the minvalue for convergence consideration, defaults to 0.00000001 |
+| opt.discovery | A list of controlling parameters for isoform reconstruction process:  
     **prefix** specifying prefix for new gene Ids (genePrefix.number), defaults to empty 
     **remove.subsetTx** indicating whether filter to remove read classes which are a subset of known transcripts, defaults to TRUE 
     **min.readCount** specifying minimun read count to consider a read class valid in a sample, defaults to 2 
     **min.readFractionByGene** specifying minimum relative read count per gene, highly expressed genes will have many high read count low relative abundance transcripts that can be filtered, defaults to 0.05 
     **min.sampleNumber** specifying minimum sample number with minimum read count, gene read proportion, and TPS, defaults to 1 
     **min.exonDistance** specifying minimum distance to known transcript to be considered valid as new, defaults to 35bp 
     **min.exonOverlap** specifying minimum number of bases shared with annotation to be assigned to the same gene id, defaults to 10bp 
     **min.primarySecondaryDist** specifying the minimum number of distance threshold between a read class and the annotations internal exons. Read classes with distances less than the threshold are not annotated as novel and counted with the annotations for quantification, defaults to 5bp 
     **min.primarySecondaryDistStartEnd1** specifying the minimum number of distance threshold between a read class and the annotations start/end exons. Read classes with distances less than the threshold are not annotated as novel, defaults to 5bp 
     **min.primarySecondaryDistStartEnd2** specifying the minimum number of distance threshold between a read class and the annotations start/end exons. Read classes with distances less than the threshold are counted with the annotations, defaults to 5bp 
     **min.txScore.multiExon** specifying the minimum transcript probility score threshold for multi-exon transcripts for min.sampleNumber, defaults to 0 
     **min.txScore.singleExon** specifying the minimum transcript probability score threshold for single-exon transcripts for min.sampleNumber 
     **fitReadClassModel** a boolean specifying if bambu should train a model on each sample. If set to false bambu will use the default model for ranking novel transcripts. defaults to TRUE 
     **defaultModels** a bambu trained model object that bambu will use when fitReadClassModel==FALSE or the data is not suitable for training, defaults to the pretrained model in the *bambu* package 
     **returnModel** a boolean specifying if bambu will output the model it trained on the data, defaults to FALSE 
     **baselineFDR** a value between 0-1. Bambu uses this FDR on the trained model to recommend an equivilent NDR threshold to be used for the sample. By default, a baseline FDR of 0.1 is used. This does not impact the analysis if an NDR is set. 
     **min.readFractionByEqClass** indicating the minimum relative read count of a subset transcript compared to all superset transcripts (ie the relative read count within the minimum equivalent class). This filter is applied on the set of annotations across all samples using the total read count, this is not a per-sample filter. Please use with  caution. defaults to 0 |
+| opt.em | A list of controlling parameters for quantification algorithm estimation process: 
     **maxiter** specifying maximum number of run iterations, defaults to 10000 
     **degradationBias** correcting for degradation bias, defaults to TRUE 
     **conv** specifying the covergence threshold control, defaults to 0.0001 
     **minvalue** specifying the minvalue for convergence consideration, defaults to 0.00000001 |
 | trackReads | When TRUE read names will be tracked and output as metadata in the final output as readToTranscriptMaps detailing the assignment of reads to transcripts.The output is a list with an entry for each sample. |
 | returnDistTable | When TRUE the calculated distance table between read classes and annotations will be output as metadata as distTables. The output is a list with an entry for each sample. |
 | discovery | A logical variable indicating whether annotations are to be extended for quantification, defaults to TRUE. |
 | quant | A logical variable indicating whether quantification will be performed, defaults to TRUE. |
 | verbose | A logical variable indicating whether processing messages will be printed. |
-| processByBam | A logical variable indicating if each input bam file will be processed seperately (TRUE) or all are read in and processed together (FALSE), defaults to TRUE |
-| processByChromosome | A logical variable indicating if read classes will be constructed with all reads together (FALSE), or done by chromsome which uses less memory, but provides less information for the junction correction model (TRUE), defaults to FALSE |
-| mode | A string that will set other input arguments ['bulk', 'multiplexed', 'fusion', 'debug']
     bulk - 
        processByBam = TRUE
        processByChromsome = FALSE
    multiplexed - 
        demultiplex = TRUE
        cleanReads = TRUE
        opt.em = list(degradationBias = FALSE)
        quant = FALSE
        processByChromosome = TRUE
    fusion - 
        NDR = 1
        fusionMode = TRUE
    debug -
        verbose = TRUE
        trackReads = TRUE
        returnDistTable = TRUE |
+| mode | A string that will set other input arguments ['bulk', 'multiplexed', 'fusion', 'debug']
     bulk - 
        processByBam = TRUE
        processByChromsome = FALSE
    multiplexed - 
        demultiplex = TRUE
        cleanReads = TRUE
        opt.em = list(degradationBias = FALSE)
        quant = FALSE
        processByChromosome = TRUE
    fusion - 
        NDR = 1
        fusionMode = TRUE
    debug -
        verbose = TRUE
        trackReads = TRUE
        returnDistTable = TRUE |
 | demultiplexed | A logical variable indicating whether the input bam file is demultiplexed. The barcode and umi either need to be present in the read name or the $BC and $UG tags, defaults to FALSE. Alternatively a path to a csv file can be provided where column 1 is read names, column 2 is barcodes, and column 3 is UMI. |
 | spatial | A path to the barcode whitelist containing X and Y coordinates, defaults to null. |
 | assignDist | A logical variable indicating whether read class to transcript assignment will be performed, defaults to TRUE. |
@@ -591,9 +597,13 @@ se = bambu( reads = "placeholder",
 | sampleNames | A vector of strings representing the sample name associated with each input bam. bam files with the same sample name will be combined |
 | cleanReads | A logical variable indicating whether only the first sequenced alignment in a read should be kept. This helps to remove chimeric reads, but will remove alignments from fusion genes, defaults to FALSE. |
 | dedupUMI | A logical variable indicating whether UMI deduplication is performed. The longest read per UMI will be used and the rest discarded, defaults to FALSE.|
+| barcodesToFilter | A vector of strings indicating the barcodes to be filtered out in reads.|
 | clusters | Either a list containing the barcodes for each cluster, or a path to a csv file containg the barcode to cluster mapping. When provided, clusters will be used during discovery and EM quant steps, defaults to null. |
+| processByBam | A logical variable indicating if each input bam file will be processed seperately (TRUE) or all are read in and processed together (FALSE), defaults to TRUE |
+| processByChromosome | A logical variable indicating if read classes will be constructed with all reads together (FALSE), or done by chromsome which uses less memory, but provides less information for the junction correction model (TRUE), defaults to FALSE |
 
 ### setNDR() arguments
+
 |argument|description|
 |---|---|
 |extendedAnnotations| A GRangesList object produced from bambu(quant = FALSE) or rowRanges(se) or loaded in from prepareAnnotations() of a Bambu dervived .gtf |
@@ -604,6 +614,7 @@ se = bambu( reads = "placeholder",
 |defaultModels| a bambu trained model object used to recommend an NDR threshold if no NDR is provided. Defaults to the pretrained model in the bambu package|
 
 ### Output Description
+
 Access annotations that are matched to the transcript expression estimates by rowRanges()
 ```rscript
 rowRanges(se)
@@ -633,7 +644,7 @@ rowData(se)
 |eqClass|A character vector with the transcript names of all the equivalent transcripts (those which have this transcripts contiguous exon junctions)|
 |txId|A bambu specific transcript id used for indexing purposes
 |eqClassById|A integer list with the transcript ids of all equivalent transcripts
-|txClassDescription|A concatenated string containing the classes the transcript falls under: 
     **annotation** - Transcript matches an annotation transcript 
     **allNew** - All the intron-junctions are novel 
     **newFirstJunction** - the first junction is novel and at least one other junction matches an annotated transcript 
     **newLastJunction** - the last junction is novel and at least one other junction matches an annotated transcript 
     **newJunction** - an internal junction is novel and at least one other internal junction matches an annotated transcript 
     **newWithin** -  A novel transcript with matching junctions but is not a subset of an annotation 
     **unsplicedNew** - A single exon transcript that doesn’t completely overlap with annotations 
     **compatible** - Is a subset of an annotated transcript 
     **newFirstExon** - The first exon is novel 
     **newLastExon** - The last exon is novel|
+|txClassDescription|A concatenated string containing the classes the transcript falls under: 
     **annotation** - Transcript matches an annotation transcript 
     **allNew** - All the intron-junctions are novel 
     **newFirstJunction** - the first junction is novel and at least one other junction matches an annotated transcript 
     **newLastJunction** - the last junction is novel and at least one other junction matches an annotated transcript 
     **newJunction** - an internal junction is novel and at least one other internal junction matches an annotated transcript 
     **newWithin** -  A novel transcript with matching junctions but is not a subset of an annotation 
     **unsplicedNew** - A single exon transcript that doesn’t completely overlap with annotations 
     **compatible** - Is a subset of an annotated transcript 
     **newFirstExon** - The first exon is novel 
     **newLastExon** - The last exon is novel|
 |readCount|The number of full length reads associated with this transcript (filtered by min.readCount)|
 |NDR|The NDR score calculated for the transcript|
 |relReadCount|The proportion of reads this transcript has relative to all reads assigned to its gene|
@@ -645,8 +656,8 @@ rowData(se)
 metadata(se)$incompatibleCounts
 metadata(se)$warnings
 ```
-IncompatibleCounts - A table containing counts for incompatible reads that can be assigned to a gene but to none of the provided transcripts.
-warnings - A list containing the warnings produced by each sample
+**IncompatibleCounts** - A table containing counts for incompatible reads that can be assigned to a gene but to none of the provided transcripts. 
    
+**warnings** - A list containing the warnings produced by each sample 
    
 
 ```rscript
 metadata(rowRanges(se))$NDRthreshold
@@ -654,10 +665,13 @@ metadata(rowRanges(se))$subsetTranscripts
 metadata(rowRanges(se))$lowConfidenceTranscripts
 metadata(rowRanges(se))$warnings
 ```
-NDRthreshold - The NDR threshold currently appled to the novel transcripts. A number between 0 and 1 
-subsetTranscripts - A GrangesList containing subset transcripts when remove.subsetTx = TRUE. readCount and txScore can be accessed from mcols.
-lowConfidenceTranscripts - A GrangesList containing novel transcripts above the NDR threshold
-warnings - A list containing the warnings produced by each sample
+**NDRthreshold** - The NDR threshold currently appled to the novel transcripts. A number between 0 and 1 
    
+
+**subsetTranscripts** - A GrangesList containing subset transcripts when remove.subsetTx = TRUE. readCount and txScore can be accessed from mcols. 
    
+
+**lowConfidenceTranscripts** - A GrangesList containing novel transcripts above the NDR threshold 
    
+
+**warnings** - A list containing the warnings produced by each sample 
    
 
 
 ### Release History

From 790dd175b6436a1bfa53b28802f9285f959b6434 Mon Sep 17 00:00:00 2001
From: Chen Ying 
Date: Tue, 21 Jan 2025 15:27:17 +0800
Subject: [PATCH 172/189] add check flag when read name does not contain BC and
 UMI information

---
 R/prepareDataFromBam.R | 95 ++++++++++++++++++++++++++----------------
 1 file changed, 58 insertions(+), 37 deletions(-)

diff --git a/R/prepareDataFromBam.R b/R/prepareDataFromBam.R
index ee8f7e78..98bfb778 100755
--- a/R/prepareDataFromBam.R
+++ b/R/prepareDataFromBam.R
@@ -28,29 +28,39 @@ prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE,
     counter <- 1
     cells <- c()
     umi <- c()
-    use.names.OG = use.names
-    if(!isFALSE(demultiplexed) | cleanReads) use.names = TRUE
-    if(grepl(".[ct]sv$",demultiplexed)){
-        readMap = read.table(demultiplexed, 
-            sep = ifelse(grepl(".tsv$",demultiplexed), "\t", ","), header = FALSE)
+    use.names.OG <- use.names
+    if(!isFALSE(demultiplexed) | cleanReads) use.names <- TRUE
+    # grepl(".[ct]sv$",demultiplexed)
+    if(!is.logical(demultiplexed)){ # if demultiplexed argument is not logical value  
+        if(file.exists(demultiplexed)){ # check if file path exists, it has to be a regular delimited file, can be compressed 
+            readMap <- fread(demultiplexed,header = FALSE, data.table = FALSE) # changed function to more efficiently read in data and also correct error of "no lines available as input" for csv format input
+        }else{
+            stop("Provided barcode to map file does not exists! Please provide the correct path to demultiplex argument!")
+        }
     }
     while (isIncomplete(bf)) {
         alignmentInfo <- readGAlignments(bf, param = ScanBamParam(tag = c("BC", "UG"), 
                                          flag = scanBamFlag(isSecondaryAlignment = FALSE)), 
                                          use.names = use.names)
         readGrgList[[counter]] <-grglist(alignmentInfo)
-        if (!isFALSE(demultiplexed)){
-            if(isTRUE(demultiplexed)){
-                mcols(readGrgList[[counter]])$BC <- ifelse(!is.na(mcols(alignmentInfo)$BC), mcols(alignmentInfo)$BC, 
-                                                        gsub("(^[GACT]+(?=_)).*", '\\1', names(readGrgList[[counter]]), perl = TRUE))
+        if (!isFALSE(demultiplexed)){ # if demultiplexed is TRUE or a string path 
+            if(isTRUE(demultiplexed)){ # if demultiplexed is TRUE
+                mcols(readGrgList[[counter]])$BC <- ifelse(!is.na(mcols(alignmentInfo)$BC), 
+                                                           mcols(alignmentInfo)$BC, 
+                                                           ifelse(grepl("[GACT]_",names(readGrgList[[counter]])), # a checkpoint to see whether BC is contained in the name, with specific format BC_UMI#READNAME
+                                                        gsub("(^[GACT]+(?=_)).*", '\\1', 
+                                                        names(readGrgList[[counter]]), perl = TRUE),
+                                                        NA))
                 mcols(readGrgList[[counter]])$UMI <- ifelse(!is.na(mcols(alignmentInfo)$UG), mcols(alignmentInfo)$UG, 
-                                                        gsub(".*((?<=_)[GACT]*(?=#)).*", '\\1', names(readGrgList[[counter]]), perl = TRUE))
-            } else{
-                mcols(readGrgList[[counter]])$BC = NA
-                mcols(readGrgList[[counter]])$UMI = "NA"
-                mcols(readGrgList[[counter]])$BC = readMap[,2][match(names(readGrgList[[counter]]),readMap[,1])]
+                                                            ifelse(grepl("[GACT]#",names(readGrgList[[counter]])), # a checkpoint to see whether UMI is contained in the name, with specific format BC_UMI#READNAME
+                                                        gsub(".*((?<=_)[GACT]*(?=#)).*", '\\1', names(readGrgList[[counter]]), perl = TRUE),
+                                                        NA))
+            } else{ # if demultiplexed is a string path
+                mcols(readGrgList[[counter]])$BC <- NA
+                mcols(readGrgList[[counter]])$UMI <- "NA"
+                mcols(readGrgList[[counter]])$BC <- readMap[,2][match(names(readGrgList[[counter]]),readMap[,1])]
                 if(ncol(readMap)>2){
-                    mcols(readGrgList[[counter]])$UMI = readMap[,3][match(names(readGrgList[[counter]]),readMap[,1])]
+                    mcols(readGrgList[[counter]])$UMI <- readMap[,3][match(names(readGrgList[[counter]]),readMap[,1])]
                 }
             }
             cells <- unique(c(cells, mcols(readGrgList[[counter]])$BC))
@@ -59,17 +69,21 @@ prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE,
             mcols(readGrgList[[counter]])$UMI <- factor(mcols(readGrgList[[counter]])$UMI, levels = umi)
         }
         if(cleanReads){
-            softClip5Prime <-suppressWarnings(pmax(0,as.numeric(gsub('^(\\d*)[S].*','\\1',GenomicAlignments::cigar(alignmentInfo))), na.rm=T))
-            softClip3Prime <-suppressWarnings(pmax(0,as.numeric(gsub('.*\\D(\\d*)[S]$','\\1',GenomicAlignments::cigar(alignmentInfo))), na.rm=T))
-            hardClip5Prime <-suppressWarnings(pmax(0,as.numeric(gsub('^(\\d*)[H].*','\\1',GenomicAlignments::cigar(alignmentInfo))), na.rm=T))
-            hardClip3Prime <-suppressWarnings(pmax(0,as.numeric(gsub('.*\\D(\\d*)[H]$','\\1',GenomicAlignments::cigar(alignmentInfo))), na.rm=T))
-            mcols(readGrgList[[counter]])$clip5Prime = pmax(softClip5Prime, hardClip5Prime)
-            mcols(readGrgList[[counter]])$clip3Prime = pmax(softClip3Prime, hardClip3Prime)
-            rev = as.vector(strand(alignmentInfo) == '-')
-            rev2 = grepl("_-.+of", names(alignmentInfo))
-            temp = mcols(readGrgList[[counter]])$clip5Prime
-            mcols(readGrgList[[counter]])$clip5Prime[rev != rev2] = mcols(readGrgList[[counter]])$clip3Prime[rev != rev2]
-            mcols(readGrgList[[counter]])$clip3Prime[rev != rev2] = temp[rev != rev2]
+            softClip5Prime <- clipFunction(cigarData = GenomicAlignments::cigar(alignmentInfo), grep_pattern = '^(\\d*)[S].*', replace_pattern = '\\1')
+            softClip3Prime <- clipFunction(cigarData = GenomicAlignments::cigar(alignmentInfo), grep_pattern = '.*\\D(\\d*)[S]$', replace_pattern = '\\1')
+            hardClip5Prime <- clipFunction(alignData = GenomicAlignments::cigar(alignmentInfo), grep_pattern = '^(\\d*)[H].*', replace_pattern = '\\1')
+            hardClip3Prime <- clipFunction(alignData = GenomicAlignments::cigar(alignmentInfo), grep_pattern = '.*\\D(\\d*)[H]$', replace_pattern = '\\1')
+            # softClip5Prime <-suppressWarnings(pmax(0,as.numeric(gsub('^(\\d*)[S].*','\\1',GenomicAlignments::cigar(alignmentInfo))), na.rm=T))
+            # softClip3Prime <-suppressWarnings(pmax(0,as.numeric(gsub('.*\\D(\\d*)[S]$','\\1',GenomicAlignments::cigar(alignmentInfo))), na.rm=T))
+            # hardClip5Prime <-suppressWarnings(pmax(0,as.numeric(gsub('^(\\d*)[H].*','\\1',GenomicAlignments::cigar(alignmentInfo))), na.rm=T))
+            # hardClip3Prime <-suppressWarnings(pmax(0,as.numeric(gsub('.*\\D(\\d*)[H]$','\\1',GenomicAlignments::cigar(alignmentInfo))), na.rm=T))
+            mcols(readGrgList[[counter]])$clip5Prime <- pmax(softClip5Prime, hardClip5Prime)
+            mcols(readGrgList[[counter]])$clip3Prime <- pmax(softClip3Prime, hardClip3Prime)
+            rev <- as.vector(strand(alignmentInfo) == '-')
+            rev2 <- grepl("_-.+of", names(alignmentInfo))
+            temp <- mcols(readGrgList[[counter]])$clip5Prime
+            mcols(readGrgList[[counter]])$clip5Prime[rev != rev2] <- mcols(readGrgList[[counter]])$clip3Prime[rev != rev2]
+            mcols(readGrgList[[counter]])$clip3Prime[rev != rev2] <- temp[rev != rev2]
         }
         
         counter <- counter + 1
@@ -84,10 +98,10 @@ prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE,
     }
     # remove microexons of width 1bp from list
     readGrgList <- readGrgList[width(readGrgList) > 1]
-    numNoBCs = sum(is.na(mcols(readGrgList)$BC))
+    numNoBCs <- sum(is.na(mcols(readGrgList)$BC))
     if(numNoBCs > 0){
         message("Removing ", numNoBCs, " reads that were not assigned barcodes. If this is unexpected check the barcode map input")
-    readGrgList = readGrgList[!is.na(mcols(readGrgList)$BC)]
+        readGrgList <- readGrgList[!is.na(mcols(readGrgList)$BC)]
     }
     if(cleanReads){
         #extract duplicated reads from flexiplex to clean
@@ -102,10 +116,10 @@ prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE,
 
        #select alignments closest to barcode
         start.ptm <- proc.time()
-        df = data.frame(name = names(readGrgList), 
+        df <- data.frame(name = names(readGrgList), 
             clip5 = mcols(readGrgList)$clip5Prime)
-        df = df %>% mutate(id = row_number()) %>% group_by(name) %>% summarise(primary.id = id[which.min(clip5)])
-        readGrgList = unname(readGrgList[df$primary.id])
+        df <- df %>% mutate(id = row_number()) %>% group_by(name) %>% summarise(primary.id = id[which.min(clip5)])
+        readGrgList <- unname(readGrgList[df$primary.id])
         end.ptm <- proc.time()
         message("Primary alignment selection time ", round((end.ptm - start.ptm)[3] / 60, 3), " mins.")
         
@@ -113,13 +127,13 @@ prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE,
     if(dedupUMI){
         #UMI deduplication by barcode
         start.ptm <- proc.time()
-        numUMIs = length(unique(mcols(readGrgList)$UMI))
+        numUMIs <- length(na.omit(unique(mcols(readGrgList)$UMI))) # remove NA UMIs
         if(numUMIs > 100){
-            df = data.frame(umi = mcols(readGrgList)$BC, 
+            df <- data.frame(umi = mcols(readGrgList)$BC, 
                 barcode = mcols(readGrgList)$UMI,
                 lengths = sum(width(readGrgList)))
-            df = df %>% mutate(id = row_number()) %>% group_by(barcode, umi) %>% summarise(primary.id = id[which.max(lengths)])
-            readGrgList = readGrgList[df$primary.id]
+            df <- df %>% mutate(id = row_number()) %>% group_by(barcode, umi) %>% summarise(primary.id = id[which.max(lengths)])
+            readGrgList <- readGrgList[df$primary.id]
             end.ptm <- proc.time()
             message("UMI deduplication time ", round((end.ptm - start.ptm)[3] / 60, 3), " mins.")
         } else {
@@ -129,8 +143,15 @@ prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE,
  
         #readGrgList = c(readGrgList.filt, unname(readGrgList.keep))
     }
-    if(!use.names.OG) {names(readGrgList) <- NULL }
-    seqlevels(readGrgList)=as.character(unique(getChrFromGrList(readGrgList)))
+    if(!use.names.OG) names(readGrgList) <- NULL
+    seqlevels(readGrgList) <- as.character(unique(getChrFromGrList(readGrgList)))
     return(readGrgList)
 }
 
+
+#' Function to clip sequences 
+#' @noRd
+clipFunction <- function(cigarData, grep_pattern, replace_pattern){
+    return(suppressWarnings(pmax(0,as.numeric(gsub(grep_pattern,replace_pattern,
+                                                   cigarData)), na.rm=T)))
+}
\ No newline at end of file

From 7a4fe5c8aaa06483d0407478d0613be91190a9e2 Mon Sep 17 00:00:00 2001
From: Chen Ying 
Date: Tue, 21 Jan 2025 15:29:46 +0800
Subject: [PATCH 173/189] comment unused code after return in
 generateUniqueCounts function

---
 R/bambu-assignDist.R | 119 +++++++++++++++++++++++--------------------
 1 file changed, 65 insertions(+), 54 deletions(-)

diff --git a/R/bambu-assignDist.R b/R/bambu-assignDist.R
index 81416f02..25d2d3e2 100644
--- a/R/bambu-assignDist.R
+++ b/R/bambu-assignDist.R
@@ -7,91 +7,102 @@ assignReadClasstoTranscripts <- function(readClassList, annotations, isoreParame
                                         returnDistTable = FALSE, trackReads = TRUE) {
     if (is.character(readClassList)) readClassList <- readRDS(file = readClassList)
     metadata(readClassList)$readClassDist <- calculateDistTable(readClassList, annotations, isoreParameters, verbose, returnDistTable)
-    readClassList = splitReadClassFiles(readClassList)
+    readClassList <- splitReadClassFiles(readClassList)
     readClassDt <- genEquiRCs(metadata(readClassList)$readClassDist, annotations, verbose) 
     readClassDt$eqClass.match = match(readClassDt$eqClassById,metadata(readClassList)$eqClassById)
     readClassDt <- simplifyNames(readClassDt)
-    readClassDt = readClassDt %>% group_by(eqClassId, gene_sid) %>% 
-        mutate(multi_align = length(unique(txid))>1) %>% ungroup() %>% mutate(aval = 1) %>%
+    readClassDt <- readClassDt %>% group_by(eqClassId, gene_sid) %>% 
+        mutate(multi_align = length(unique(txid))>1) %>% 
+        ungroup() %>% 
+        mutate(aval = 1) %>%
         data.table()
     #return non-em counts
-    ColData = generateColData(colnames(metadata(readClassList)$countMatrix), clusters = NULL, demultiplexed, spatial)
+    ColData <- generateColData(colnames(metadata(readClassList)$countMatrix), clusters = NULL, demultiplexed, spatial)
     quantData <- SummarizedExperiment(assays = SimpleList(
         counts = generateUniqueCounts(readClassDt, metadata(readClassList)$countMatrix, annotations)),
         rowRanges = annotations,
         colData = ColData)
-    colnames(quantData) = ColData$id
+    colnames(quantData) <- ColData$id
     if(sum(metadata(readClassList)$incompatibleCountMatrix)==0){
-        metadata(quantData)$incompatibleCounts = NULL
-    } else{
-        metadata(quantData)$incompatibleCounts = generateIncompatibleCounts(metadata(readClassList)$incompatibleCountMatrix, annotations)       
-    }
-    metadata(quantData)$nonuniqueCounts = generateNonUniqueCounts(readClassDt, metadata(readClassList)$countMatrix, annotations)
-    metadata(quantData)$readClassDt = readClassDt
-    metadata(quantData)$countMatrix = metadata(readClassList)$countMatrix
-    metadata(quantData)$incompatibleCountMatrix  = metadata(readClassList)$incompatibleCountMatrix 
-    metadata(quantData)$sampleNames = metadata(readClassList)$sampleNames 
-    if(returnDistTable){
-        metadata(quantData)$distTable = metadata(metadata(readClassList)$readClassDist)$distTableOld
+        metadata(quantData)$incompatibleCounts <- NULL
+    }else{
+        metadata(quantData)$incompatibleCounts <- generateIncompatibleCounts(metadata(readClassList)$incompatibleCountMatrix, annotations)       
     }
-    if (trackReads){
-        metadata(quantData)$readToTranscriptMap = 
-            generateReadToTranscriptMap(readClassList, metadata(readClassList)$readClassDist, 
-                                  annotations)
-    } 
+    metadata(quantData)$nonuniqueCounts <- generateNonUniqueCounts(readClassDt, metadata(readClassList)$countMatrix, annotations)
+    metadata(quantData)$readClassDt <- readClassDt
+    metadata(quantData)$countMatrix <- metadata(readClassList)$countMatrix
+    metadata(quantData)$incompatibleCountMatrix <- metadata(readClassList)$incompatibleCountMatrix 
+    metadata(quantData)$sampleNames <- metadata(readClassList)$sampleNames 
+    if(returnDistTable)
+        metadata(quantData)$distTable <- metadata(metadata(readClassList)$readClassDist)$distTableOld
+
+    if(trackReads)
+        metadata(quantData)$readToTranscriptMap <- 
+            generateReadToTranscriptMap(readClassList, 
+                                        metadata(readClassList)$readClassDist, 
+                                        annotations)
+
     return(quantData)     
 
 }
 
-
+#' Generate unique counts
+#' @noRd
 generateUniqueCounts <- function(readClassDt, countMatrix, annotations){
-    x = readClassDt %>% filter(!multi_align & !is.na(eqClass.match))
-    uniqueCounts = countMatrix[x$eqClass.match,]
-    uniqueCounts.tx = sparse.model.matrix(~ factor(x$txid) - 1)
-    uniqueCounts = t(uniqueCounts.tx) %*% uniqueCounts
-    rownames(uniqueCounts) = names(annotations)[match(as.numeric(levels(factor(x$txid))),mcols(annotations)$txid)]
-    counts = sparseMatrix(length(annotations), ncol(uniqueCounts), x = 0)
-    rownames(counts) = names(annotations)
-    counts[rownames(uniqueCounts),] = uniqueCounts
+    x <- readClassDt %>% filter(!multi_align & !is.na(eqClass.match))
+    uniqueCounts <- countMatrix[x$eqClass.match,]
+    uniqueCounts.tx <- sparse.model.matrix(~ factor(x$txid) - 1)
+    uniqueCounts <- t(uniqueCounts.tx) %*% uniqueCounts
+    rownames(uniqueCounts) <- names(annotations)[match(as.numeric(levels(factor(x$txid))),mcols(annotations)$txid)]
+    counts <- sparseMatrix(length(annotations), ncol(uniqueCounts), x = 0)
+    rownames(counts) <- names(annotations)
+    counts[rownames(uniqueCounts),] <- uniqueCounts
     return(counts)
-
-    counts.total = colSums(countMatrix) + colSums(incompatibleCountMatrix)
-    counts.total[counts.total==0] = 1
-    counts.CPM = counts/counts.total * 10^6
+    
+    # these three lines appear after return, so it's not used, is this used for debug only?
+    # counts.total = colSums(countMatrix) + colSums(incompatibleCountMatrix)
+    # counts.total[counts.total==0] = 1
+    # counts.CPM = counts/counts.total * 10^6
 
 }
 
+
+#' Generate incompatible counts
+#' @noRd
 generateIncompatibleCounts <- function(incompatibleCountMatrix, annotations){
-    genes = levels(factor(unique(mcols(annotations)$GENEID)))
-    rownames(incompatibleCountMatrix) = genes[as.numeric(rownames(incompatibleCountMatrix))]
-    geneMat = sparseMatrix(length(genes), ncol(incompatibleCountMatrix), x = 0)
-    rownames(geneMat) = genes
-    geneMat[rownames(incompatibleCountMatrix),] = incompatibleCountMatrix
+    genes <- levels(factor(unique(mcols(annotations)$GENEID)))
+    rownames(incompatibleCountMatrix) <- genes[as.numeric(rownames(incompatibleCountMatrix))]
+    geneMat <- sparseMatrix(length(genes), ncol(incompatibleCountMatrix), x = 0)
+    rownames(geneMat) <- genes
+    geneMat[rownames(incompatibleCountMatrix),] <- incompatibleCountMatrix
     return(geneMat)
 }
 
+
+#' Generate non-unique counts
+#' @noRd
 generateNonUniqueCounts <- function(readClassDt, countMatrix, annotations){
     #fuse multi align RCs by gene
-    x = readClassDt %>% filter(multi_align & !is.na(eqClass.match))
-    x = x %>% distinct(eqClassId, .keep_all = TRUE)
-    nonuniqueCounts = countMatrix[x$eqClass.match,, drop = FALSE]
+    x <- readClassDt %>% filter(multi_align & !is.na(eqClass.match))
+    x <- x %>% distinct(eqClassId, .keep_all = TRUE)
+    nonuniqueCounts <- countMatrix[x$eqClass.match,, drop = FALSE]
     if(nrow(x)>1 & length(unique(x$gene_sid))>1){
-        nonuniqueCounts.gene = sparse.model.matrix(~ factor(x$gene_sid) - 1)
-        nonuniqueCounts = t(nonuniqueCounts.gene) %*% nonuniqueCounts
+        nonuniqueCounts.gene <- sparse.model.matrix(~ factor(x$gene_sid) - 1)
+        nonuniqueCounts <- t(nonuniqueCounts.gene) %*% nonuniqueCounts
     } else{
         warning("The factor variable 'gene_sid' has only one level. Adjusting output.")
-        nonuniqueCounts.gene = Matrix(1, nrow = nrow(x), ncol = 1, sparse = TRUE)
-        nonuniqueCounts = t(nonuniqueCounts.gene) %*% nonuniqueCounts
+        nonuniqueCounts.gene <- Matrix(1, nrow = nrow(x), ncol = 1, sparse = TRUE)
+        nonuniqueCounts <- t(nonuniqueCounts.gene) %*% nonuniqueCounts
     }
     #covert ids into gene ids
-    geneids = as.numeric(levels(factor(x$gene_sid)))
-    geneids = x$txid[match(geneids, x$gene_sid)]
-    geneids = mcols(annotations)$GENEID[as.numeric(geneids)]
-    rownames(nonuniqueCounts) = geneids
+    geneids <- as.numeric(levels(factor(x$gene_sid)))
+    geneids <- x$txid[match(geneids, x$gene_sid)]
+    geneids <- mcols(annotations)$GENEID[as.numeric(geneids)]
+    rownames(nonuniqueCounts) <- geneids
     #create matrix for all annotated genes
-    genes = levels(factor(unique(mcols(annotations)$GENEID)))
-    geneMat = sparseMatrix(length(genes), ncol(nonuniqueCounts), x = 0)
-    rownames(geneMat) = genes
-    geneMat[rownames(nonuniqueCounts),] = nonuniqueCounts
+    genes <- levels(factor(unique(mcols(annotations)$GENEID)))
+    geneMat <- sparseMatrix(length(genes), ncol(nonuniqueCounts), x = 0)
+    rownames(geneMat) <- genes
+    geneMat[rownames(nonuniqueCounts),] <- nonuniqueCounts
     return(geneMat)
 }

From 4f3c629acf8a0fbf4e4771defe7c5e3e7b4cf032 Mon Sep 17 00:00:00 2001
From: Chen Ying 
Date: Tue, 21 Jan 2025 15:32:40 +0800
Subject: [PATCH 174/189] comment out some internal messages to avoid
 duplicated output for each sample

---
 R/bambu-quantify.R                  |  6 +--
 R/bambu-quantify_utilityFunctions.R | 83 ++++++++++++++---------------
 2 files changed, 44 insertions(+), 45 deletions(-)

diff --git a/R/bambu-quantify.R b/R/bambu-quantify.R
index d996c189..68b41395 100644
--- a/R/bambu-quantify.R
+++ b/R/bambu-quantify.R
@@ -20,7 +20,7 @@ bambu.quantify <- function(readClassDt, countMatrix, incompatibleCountMatrix, tx
                     fullLengthCounts = as(round(counts$fullLengthCounts,sig.digit), "sparseVector"),
                     uniqueCounts = as(round(counts$uniqueCounts,sig.digit), "sparseVector"))              
     end.ptm <- proc.time()
-    if (verbose) message("bambu.quantify ", round((end.ptm - start.ptm)[3] / 60, 3), " mins.")
+    # if (verbose) message("bambu.quantify ", round((end.ptm - start.ptm)[3] / 60, 3), " mins.")
     return(seOutput)
 }
 
@@ -43,8 +43,8 @@ bambu.quantDT <- function(readClassDt = readClassDt,
                                      maxiter = emParameters[["maxiter"]],
                                      conv = emParameters[["conv"]], minvalue = emParameters[["minvalue"]])
     end.ptm <- proc.time()
-    if (verbose) message("Finished EM estimation in ",
-                        round((end.ptm - start.ptm)[3] / 60, 1), " mins.")
+    # if (verbose) message("Finished EM estimation in ",
+    #                     round((end.ptm - start.ptm)[3] / 60, 1), " mins.")
     outEst <- modifyQuantOut(outEst,outIni)
     theta_est <- rbind(rcPreOut[[2]],outEst)
     theta_est <- removeDuplicates(theta_est)
diff --git a/R/bambu-quantify_utilityFunctions.R b/R/bambu-quantify_utilityFunctions.R
index 0bb8c85d..936763f1 100644
--- a/R/bambu-quantify_utilityFunctions.R
+++ b/R/bambu-quantify_utilityFunctions.R
@@ -257,8 +257,8 @@ calculateDegradationRate <- function(readClassDt){
   geneCountLength[, d_rate := dObs/nobs]
   if (length(which(geneCountLength$nobs >= 30 & 
                    ((geneCountLength$nobs - geneCountLength$dObs) >= 5))) == 0) {
-    message("There is not enough read count and full length coverage!
-            Hence degradation rate is estimated using all data!")
+    # message("There is not enough read count and full length coverage!
+    #         Hence degradation rate is estimated using all data!")
   } else {
     geneCountLength <- geneCountLength[nobs >= 30 & ((nobs - dObs) >= 5)]
   }
@@ -461,58 +461,57 @@ removeDuplicates <- function(counts){
 #' Generate read to transcript mapping
 #' @noRd
 generateReadToTranscriptMap <- function(readClass, distTable, annotations){
-  if(!is.null(metadata(readClass)$readNames)) { 
-    read_id = metadata(readClass)$readNames}
-  else { read_id = metadata(readClass)$readId}
-  print(1)
+    if(!is.null(metadata(readClass)$readNames)) { 
+        read_id <- metadata(readClass)$readNames
+    } else { 
+        read_id <- metadata(readClass)$readId
+    }
   #unpack and reverse the read class to read id relationship
-  readOrder = order(unlist(rowData(readClass)$readIds))
-  lens = lengths(rowData(readClass)$readIds)
-  rcIndex = seq_along(readClass)
-  readToRC = rep(rcIndex, lens)[readOrder]
-  read_id = read_id[(match(unlist(rowData(readClass)$readIds)[readOrder], metadata(readClass)$readId))]
-  print(2)
+  readOrder <- order(unlist(rowData(readClass)$readIds))
+  lens <- lengths(rowData(readClass)$readIds)
+  rcIndex <- seq_along(readClass)
+  readToRC <- rep(rcIndex, lens)[readOrder]
+  read_id <- read_id[(match(unlist(rowData(readClass)$readIds)[readOrder], 
+                           metadata(readClass)$readId))]
   #get annotation indexs
-  distTable = metadata(distTable)$distTable
-    print(head(distTable))
-  distTable$annotationTxId = match(distTable$annotationTxId, names(annotations))
-  print(2.1)
-  print(head(distTable))
+  distTable <- metadata(distTable)$distTable
+  distTable$annotationTxId <- match(distTable$annotationTxId, names(annotations))
   #match read classes with transcripts
-  readClass_id = rownames(readClass)[readToRC]
-  distTable$exClassById = NULL
-  print(3)
-  equalMatches = as_tibble(distTable) %>%
+  readClass_id <- rownames(readClass)[readToRC]
+  distTable$exClassById <- NULL
+  equalMatches <- as_tibble(distTable) %>%
     filter(equal) %>% 
-    group_by(readClassId) %>% summarise(annotationTxIds = list(annotationTxId))
-  equalMatches = equalMatches$annotationTxIds[match(readClass_id, equalMatches$readClassId)]
-  print(4)
-  compatibleMatches =  as_tibble(distTable) %>% 
+    group_by(readClassId) %>% 
+      summarise(annotationTxIds = list(annotationTxId))
+  equalMatches <- equalMatches$annotationTxIds[match(readClass_id,
+                        equalMatches$readClassId)]
+  compatibleMatches <- as_tibble(distTable) %>% 
     filter(!equal & compatible) %>% 
     group_by(readClassId) %>% summarise(annotationTxIds = list(annotationTxId))
-  compatibleMatches = compatibleMatches$annotationTxIds[match(readClass_id, compatibleMatches$readClassId)]
-  print(5)
-  readToTranscriptMap = tibble(readId=read_id, equalMatches = equalMatches, compatibleMatches = compatibleMatches)
+  compatibleMatches <- compatibleMatches$annotationTxIds[match(readClass_id,
+                            compatibleMatches$readClassId)]
+  readToTranscriptMap <- tibble(readId=read_id, equalMatches = equalMatches, 
+                             compatibleMatches = compatibleMatches)
   return(readToTranscriptMap)
 }
 
 #' Get counts of equivilent classes from a distTable and match to a readClassDt
 #' @noRd
-calculateEqClassCounts = function(distTable, readClassDt){
-        eqClasses = distTable %>% group_by(eqClassById) %>%
-        mutate(anyEqual = any(equal)) %>%
-        select(eqClassById, firstExonWidth,totalWidth, readCount,GENEID,anyEqual) %>% #eqClassByIdTemp,
-        distinct() %>%
-        mutate(nobs = sum(readCount),
-                rcWidth = ifelse(anyEqual, max(totalWidth), 
-                                max(firstExonWidth))) %>%
-        select(eqClassById,GENEID,nobs,rcWidth) %>% 
-        ungroup()  %>%
-        distinct()
-        eqCounts = eqClasses$nobs[match(readClassDt$eqClassById,eqClasses$eqClassById)]
-        eqCounts[is.na(eqCounts)] = 0
+calculateEqClassCounts <- function(distTable, readClassDt){
+        eqClasses <- distTable %>% group_by(eqClassById) %>%
+                         mutate(anyEqual = any(equal)) %>%
+                         select(eqClassById, firstExonWidth,totalWidth,
+                                readCount,GENEID,anyEqual) %>% #eqClassByIdTemp,
+                         distinct() %>%
+                         mutate(nobs = sum(readCount),
+                             rcWidth = ifelse(anyEqual, max(totalWidth), 
+                             max(firstExonWidth))) %>%
+                         select(eqClassById,GENEID,nobs,rcWidth) %>% 
+                         ungroup() %>% distinct()
+        eqCounts <- eqClasses$nobs[match(readClassDt$eqClassById,eqClasses$eqClassById)]
+        eqCounts[is.na(eqCounts)] <- 0
         return(eqCounts)
-    }
+}
 
 #' calculate CPM post estimation
 #' @noRd

From 17b993a5d1cb31612bc52e2ffc23a4a0a3ddf245 Mon Sep 17 00:00:00 2001
From: Chen Ying 
Date: Tue, 21 Jan 2025 15:34:31 +0800
Subject: [PATCH 175/189] fix bug for demultiplexed when demultiplexed is
 provided as a file

---
 R/bambu_utilityFunctions.R | 92 +++++++++++++++++++++-----------------
 1 file changed, 51 insertions(+), 41 deletions(-)

diff --git a/R/bambu_utilityFunctions.R b/R/bambu_utilityFunctions.R
index db8a4626..7c7d1bcd 100644
--- a/R/bambu_utilityFunctions.R
+++ b/R/bambu_utilityFunctions.R
@@ -9,6 +9,7 @@ setBiocParallelParameters <- function(reads, ncore, verbose, demultiplexed){
     "to resolve the issue that originates from the XGboost package.")
     bpParameters <- bpparam()
     #===# set parallel options: otherwise use parallel to distribute samples
+    # when demultiplexed is FALSE, isFALSE(demultiplexed) is TRUE
     bpParameters$workers <- ifelse(length(reads) == 1 & isFALSE(demultiplexed), 1, ncore)
     bpParameters$progressbar <- ifelse(length(reads) > 1 & !verbose, TRUE, FALSE)
     return(bpParameters)
@@ -198,17 +199,20 @@ checkInputSequence <- function(genomeSequence) {
 #' Function that gathers warnings from several read class lists and outputs the counts
 #' @noRd
 handleWarnings <- function(readClassList, verbose){
-    warnings = list()
-    sampleNames = c()
+    warnings <- list()
+    sampleNames <- c()
     for(i in seq_along(readClassList)){
-        readClassSe = readClassList[[i]]
-        if (is.character(readClassSe)) {
-            readClassSe <- readRDS(file = readClassSe)}
-        warnings[[i]] = metadata(readClassSe)$warnings
-        if(is.null(metadata(readClassSe)$warnings)) {warnings[[i]] = NA}
-        sampleNames = c(sampleNames, colnames(readClassSe))
+        readClassSe <- readClassList[[i]]
+        if (is.character(readClassSe))
+            readClassSe <- readRDS(file = readClassSe)
+        
+        warnings[[i]] <- metadata(readClassSe)$warnings
+        
+        if(is.null(metadata(readClassSe)$warnings)) 
+            warnings[[i]] <- NA
+        sampleNames <- c(sampleNames, colnames(readClassSe))
     }
-    names(warnings) = sampleNames
+    names(warnings) <- sampleNames
     if(verbose & any(lengths(warnings)>0)){
         message("--- per sample warnings during read class construction ---")
         for(i in seq_along(warnings)){
@@ -232,12 +236,12 @@ calculateDistTable <- function(readClassList, annotations, isoreParameters, verb
                                                             min.primarySecondaryDistStartEnd = isoreParameters[['min.primarySecondaryDistStartEnd2']],
                                                             verbose = verbose)
         metadata(readClassDist)$distTable <- modifyIncompatibleAssignment(metadata(readClassDist)$distTable)
-        if(returnDistTable) metadata(readClassDist)$distTableOld = metadata(readClassDist)$distTable
+        if(returnDistTable) metadata(readClassDist)$distTableOld <- metadata(readClassDist)$distTable
                 #convert string gene ids into index to save memory
-        GENEIDs = factor(unique(mcols(annotations)$GENEID))
-        GENEID.i = as.numeric(GENEIDs)
-        metadata(readClassDist)$distTable$GENEID.i = GENEID.i[match(metadata(readClassDist)$distTable$GENEID, GENEIDs)]
-        metadata(readClassDist)$distTable.incompatible = data.table(as.data.frame(metadata(readClassDist)$distTable)) %>% 
+        GENEIDs <- factor(unique(mcols(annotations)$GENEID))
+        GENEID.i <- as.numeric(GENEIDs)
+        metadata(readClassDist)$distTable$GENEID.i <- GENEID.i[match(metadata(readClassDist)$distTable$GENEID, GENEIDs)]
+        metadata(readClassDist)$distTable.incompatible <- data.table(as.data.frame(metadata(readClassDist)$distTable)) %>% 
             filter(grepl("unidentified", annotationTxId)) %>% distinct(readClassId, .keep_all = TRUE)
         metadata(readClassDist)$distTable <- genEquiRCsBasedOnObservedReads(readClassDist)     
         return(readClassDist)
@@ -246,23 +250,27 @@ calculateDistTable <- function(readClassList, annotations, isoreParameters, verb
 #' Combine count se object while preserving the metadata objects
 #' @noRd
 combineCountSes <- function(countsSe, annotations){
-    countsData <- c("counts", "CPM", "fullLengthCounts", "uniqueCounts", "incompatibleCounts")
-    sampleNames = countsSe$colnames
-    countsSe$colnames = NULL
+    countsData <- c("counts", "CPM", "fullLengthCounts", 
+                    "uniqueCounts", "incompatibleCounts")
+    sampleNames <- countsSe$colnames
+    countsSe$colnames <- NULL
     countsDataMat <- lapply(countsData, FUN = function(k){
         countsVecList <- lapply(countsSe, function(j){j[[k]]})
-        countsMat <- sparseMatrix(i = unlist(lapply(countsVecList, function(j){j@i})),
-                                j = unlist(lapply(seq_along(countsVecList), function(j){rep(j, length(countsVecList[[j]]@i))})),
-                                x = unlist(lapply(countsVecList, function(j){j@x})),
+        countsMat <- sparseMatrix(i = unlist(lapply(countsVecList, function(j) j@i)),
+                                j = unlist(lapply(seq_along(countsVecList), function(j) rep(j, length(countsVecList[[j]]@i)))),
+                                x = unlist(lapply(countsVecList, function(j) j@x)),
                                 dims = c(length(countsVecList[[1]]), length(countsVecList)))
-        if(all(is.na(countsMat))){countsMat = sparseMatrix(i=NULL, j = NULL, dims = c(length(countsVecList[[1]]), length(countsVecList)))}
+        if(all(is.na(countsMat)))
+            countsMat <- sparseMatrix(i=NULL, j = NULL, dims = c(length(countsVecList[[1]]), length(countsVecList)))
+        
         colnames(countsMat) <- sampleNames
-        if (k == "incompatibleCounts"){
-            rownames(countsMat) = unique(mcols(annotations)$GENEID)
-        }
+        
+        if (k == "incompatibleCounts")
+            rownames(countsMat) <- unique(mcols(annotations)$GENEID)
+        
         return(countsMat)
     })
-    names(countsDataMat) = countsData
+    names(countsDataMat) <- countsData
     countsSe <- SummarizedExperiment(assays = SimpleList(counts = countsDataMat$counts, 
                                                         CPM = countsDataMat$CPM, 
                                                         fullLengthCounts = countsDataMat$fullLengthCounts, 
@@ -275,29 +283,31 @@ combineCountSes <- function(countsSe, annotations){
 #' Generate the coldata for se options using colnames, and other option inputs
 #' @noRd
 generateColData <- function(sampleNames, clusters, demultiplexed, spatial){
-    ColData = DataFrame(id = sampleNames)
-    if(demultiplexed & is.null(clusters)){
-        ColData = DataFrame(id = sampleNames, 
+    ColData <- DataFrame(id = sampleNames)
+    if(!isFALSE(demultiplexed) & is.null(clusters)){
+        ColData <- DataFrame(id = sampleNames, 
                         sampleName = gsub("_[^_]+$","", sampleNames, perl = TRUE), 
                         Barcode = gsub(".*_(?=[^_]*$)","", sampleNames, perl = TRUE))
     }
     if(!is.null(spatial) & is.null(clusters)){
-        ColData$x_coordinate = NA
-        ColData$y_coordinate = NA
+        ColData$x_coordinate <- NA
+        ColData$y_coordinate <- NA
         if(length(spatial)==1){
-            bc_coords = DataFrame(read.table(gzfile(spatial), col.names = c("Barcode", "x_coordinate", "y_coordinate")))
-            bcMatch = match(ColData$Barcode, bc_coords$Barcode)
-            ColData$x_coordinate = bc_coords$x_coordinate[bcMatch]
-            ColData$y_coordinate = bc_coords$y_coordinate[bcMatch]
+            bc_coords <- DataFrame(read.table(gzfile(spatial),
+                col.names = c("Barcode", "x_coordinate", "y_coordinate")))
+            bcMatch <- match(ColData$Barcode, bc_coords$Barcode)
+            ColData$x_coordinate <- bc_coords$x_coordinate[bcMatch]
+            ColData$y_coordinate <- bc_coords$y_coordinate[bcMatch]
         } else{
-            spatial.unique = unique(spatial)
+            spatial.unique <- unique(spatial)
             for(whitelist in spatial.unique){
-                i = which(spatial.unique==whitelist)
-                bc_coords = DataFrame(read.table(gzfile(whitelist), col.names = c("Barcode", "x_coordinate", "y_coordinate")))
-                bcSampleIndex = ColData$sampleName %in% sampleNames[i]
-                bcMatch = match(ColData$Barcode[bcSampleIndex], bc_coords$Barcode)
-                ColData$x_coordinate[bcSampleIndex] = bc_coords$x_coordinate[bcMatch]
-                ColData$y_coordinate[bcSampleIndex] = bc_coords$y_coordinate[bcMatch]
+                i <- which(spatial.unique==whitelist)
+                bc_coords <- DataFrame(read.table(gzfile(whitelist), 
+                    col.names = c("Barcode", "x_coordinate", "y_coordinate")))
+                bcSampleIndex <- ColData$sampleName %in% sampleNames[i]
+                bcMatch <- match(ColData$Barcode[bcSampleIndex], bc_coords$Barcode)
+                ColData$x_coordinate[bcSampleIndex] <- bc_coords$x_coordinate[bcMatch]
+                ColData$y_coordinate[bcSampleIndex] <- bc_coords$y_coordinate[bcMatch]
             }
         }
     }

From 9f7b49b208e4c7f203b3b5c9a26b8a03481b5569 Mon Sep 17 00:00:00 2001
From: Chen Ying 
Date: Tue, 21 Jan 2025 15:35:11 +0800
Subject: [PATCH 176/189] code style updates

---
 R/bambu-processReads.R | 225 +++++++++++++++++++++++------------------
 R/bambu.R              | 144 +++++++++++++++-----------
 2 files changed, 212 insertions(+), 157 deletions(-)

diff --git a/R/bambu-processReads.R b/R/bambu-processReads.R
index e7a65a6c..b62e67a1 100644
--- a/R/bambu-processReads.R
+++ b/R/bambu-processReads.R
@@ -48,11 +48,11 @@ bambu.processReads <- function(reads, annotations, genomeSequence,
             names(reads)[seq_along(sampleNames)] <- sampleNames
         }
     }
-    min.readCount = isoreParameters[["min.readCount"]]
-    fitReadClassModel = isoreParameters[["fitReadClassModel"]]
-    defaultModels = isoreParameters[["defaultModels"]]
-    returnModel = isoreParameters[["returnModel"]]
-    min.exonOverlap = isoreParameters[["min.exonOverlap"]]
+    min.readCount <- isoreParameters[["min.readCount"]]
+    fitReadClassModel <- isoreParameters[["fitReadClassModel"]]
+    defaultModels <- isoreParameters[["defaultModels"]]
+    returnModel <- isoreParameters[["returnModel"]]
+    min.exonOverlap <- isoreParameters[["min.exonOverlap"]]
 
     if(processByBam){ # bulk mode
         readClassList <- bplapply(seq_along(reads), function(i) {
@@ -74,32 +74,38 @@ bambu.processReads <- function(reads, annotations, genomeSequence,
             trackReads = trackReads, fusionMode = fusionMode, 
             demultiplexed = demultiplexed, cleanReads = cleanReads, dedupUMI = dedupUMI, index = i, barcodesToFilter = barcodesToFilter)},
             BPPARAM = bpParameters)
-        sampleNames = as.numeric(as.factor(sampleNames))
+        sampleNames <- as.numeric(as.factor(sampleNames))
         for(i in seq_along(readGrgList)){
             if(!isFALSE(demultiplexed)){
-                mcols(readGrgList[[i]])$BC = paste0(names(reads)[i], '_', mcols(readGrgList[[i]])$BC)
-            } else{mcols(readGrgList[[i]])$BC = sampleNames[i]}
-            mcols(readGrgList[[i]])$BC = as.factor(mcols(readGrgList[[i]])$BC)
+                mcols(readGrgList[[i]])$BC <- paste0(names(reads)[i], '_', mcols(readGrgList[[i]])$BC)
+            } else{
+                mcols(readGrgList[[i]])$BC <- sampleNames[i]
+            }
+            
+            mcols(readGrgList[[i]])$BC <- as.factor(mcols(readGrgList[[i]])$BC)
+            
             if(!isFALSE(demultiplexed)){ 
-                mcols(readGrgList[[i]])$sampleID = as.numeric(mcols(readGrgList[[i]])$BC)
-            } else {mcols(readGrgList[[i]])$sampleID = i}
+                mcols(readGrgList[[i]])$sampleID <- as.numeric(mcols(readGrgList[[i]])$BC)
+            } else {
+                mcols(readGrgList[[i]])$sampleID <- i
+            }
         }
-        readGrgList = do.call(c, readGrgList)    
+        readGrgList <- do.call(c, readGrgList)    
         mcols(readGrgList)$id <- seq_along(readGrgList) 
         readClassList <- constructReadClasses(readGrgList, genomeSequence = genomeSequence,annotations = annotations,
             stranded = stranded, min.readCount = min.readCount, 
             fitReadClassModel = fitReadClassModel, min.exonOverlap = min.exonOverlap, 
             defaultModels = defaultModels, returnModel = returnModel, verbose = verbose, 
             processByChromosome = processByChromosome, trackReads = trackReads, fusionMode = fusionMode)
-        metadata(readClassList)$samples = names(reads)
-        metadata(readClassList)$sampleNames = names(reads)
-        if(!isFALSE(demultiplexed))metadata(readClassList)$samples =  levels(mcols(readGrgList)$BC)
-        readClassList = list(readClassList)
+        metadata(readClassList)$samples <- names(reads)
+        metadata(readClassList)$sampleNames <- names(reads)
+        if(!isFALSE(demultiplexed)) metadata(readClassList)$samples <- levels(mcols(readGrgList)$BC)
+        readClassList <- list(readClassList)
     }
         
     if (!is.null(readClass.outputDir)) {
         for(i in seq_along(readClassList)){
-            readClassFile = "combinedSamples"
+            readClassFile <- "combinedSamples"
             if(lowMemory){
                 readClassFile <- metadata(readClassList[[i]])$sampleNames
             }
@@ -127,10 +133,10 @@ bambu.processReadsByFile <- function(bam.file, genomeSequence, annotations,
     if(verbose) message(names(bam.file)[1])
     readGrgList <- prepareDataFromBam(bam.file[[1]], verbose = verbose, yieldSize = yieldSize, use.names = trackReads, demultiplexed = demultiplexed, cleanReads = cleanReads, dedupUMI = dedupUMI)
     if(verbose) message(paste0("Number of alignments/reads: ",length(readGrgList)))
-    warnings = c()
-    if(!is.null(barcodesToFilter) & demultiplexed)
-        readGrgList = readGrgList[!(mcols(readGrgList)$BC %in% barcodesToFilter)]
-    warnings = seqlevelCheckReadsAnnotation(readGrgList, annotations)
+    warnings <- c()
+    if(!is.null(barcodesToFilter) & !isFALSE(demultiplexed))
+        readGrgList <- readGrgList[!(mcols(readGrgList)$BC %in% barcodesToFilter)]
+    warnings <- seqlevelCheckReadsAnnotation(readGrgList, annotations)
     if(verbose & length(warnings) > 0) warning(paste(warnings,collapse = "\n"))
     #check seqlevels for consistency, drop ranges not present in genomeSequence
     refSeqLevels <- seqlevels(genomeSequence)
@@ -138,17 +144,17 @@ bambu.processReadsByFile <- function(bam.file, genomeSequence, annotations,
         refSeqLevels <- intersect(refSeqLevels, seqlevels(readGrgList))
         if (!all(seqlevels(annotations) %in% refSeqLevels)&(!(length(annotations)==0))) {
             refSeqLevels <- intersect(refSeqLevels, seqlevels(annotations))
-            warningText = paste0("not all chromosomes from annotations present in ", 
+            warningText <- paste0("not all chromosomes from annotations present in ", 
             "reference genome sequence, annotations without reference genomic sequence ",
             "are dropped")
-            warnings = c(warnings, warningText)
+            warnings <- c(warnings, warningText)
             if(verbose) warning(warningText)
             annotations <- keepSeqlevels(annotations, value = refSeqLevels,
                                          pruning.mode = "coarse")
         }
-        warningText = paste0("not all chromosomes from reads present in reference ",
+        warningText <- paste0("not all chromosomes from reads present in reference ",
         "genome sequence, reads without reference chromosome sequence are dropped")
-        warnings = c(warnings, warningText)
+        warnings <- c(warnings, warningText)
         if(verbose) warning(warningText)
         readGrgList <- keepSeqlevels(readGrgList, value =  refSeqLevels,
                                      pruning.mode = "coarse")
@@ -156,29 +162,33 @@ bambu.processReadsByFile <- function(bam.file, genomeSequence, annotations,
         mcols(readGrgList)$id <- seq_along(readGrgList) 
     }
     #removes reads that are outside genome coordinates
-    badReads = which(max(end(ranges(readGrgList)))>
+    badReads <- which(max(end(ranges(readGrgList)))>
                          seqlengths(genomeSequence)[as.character(getChrFromGrList(readGrgList))])
     if(length(badReads) > 0 ){
-        readGrgList = readGrgList[-badReads]
-        warningText = paste0(length(badReads), " reads are mapped outside the provided ",
+        readGrgList <- readGrgList[-badReads]
+        warningText <- paste0(length(badReads), " reads are mapped outside the provided ",
                        "genomic regions. These reads will be dropped. Check you are using the ",
                        "same genome used for the alignment")
-        warnings = c(warnings, warningText)
+        warnings <- c(warnings, warningText)
         if(verbose) warning(warningText)
     }
-    if(length(readGrgList) == 0) {
+    if(length(readGrgList) == 0)
         stop("No reads left after filtering.")
-    }
+
     mcols(readGrgList)$id <- seq_along(readGrgList) 
 
-    sampleName = names(bam.file)[1]
+    sampleName <- names(bam.file)[1]
     if(!isFALSE(demultiplexed)){
-        mcols(readGrgList)$BC = paste0(sampleName, '_', mcols(readGrgList)$BC)
-    } else{mcols(readGrgList)$BC = sampleName}
-    mcols(readGrgList)$BC = as.factor(mcols(readGrgList)$BC)
+        mcols(readGrgList)$BC <- paste0(sampleName, '_', mcols(readGrgList)$BC)
+    } else{
+        mcols(readGrgList)$BC <- sampleName
+        }
+    mcols(readGrgList)$BC <- as.factor(mcols(readGrgList)$BC)
     if(!isFALSE(demultiplexed)){ 
-        mcols(readGrgList)$sampleID = as.numeric(mcols(readGrgList)$BC)
-    } else {mcols(readGrgList)$sampleID = index}
+        mcols(readGrgList)$sampleID <- as.numeric(mcols(readGrgList)$BC)
+    } else {
+        mcols(readGrgList)$sampleID <- index
+    }
         
     # construct read classes for each chromosome seperately 
     if(processByChromosome){
@@ -194,10 +204,10 @@ bambu.processReadsByFile <- function(bam.file, genomeSequence, annotations,
 
     }
 
-    metadata(se)$warnings = warnings
+    metadata(se)$warnings <- warnings
     if(trackReads){
-        metadata(se)$readNames = names(readGrgList)
-        metadata(se)$readId = mcols(readGrgList)$id
+        metadata(se)$readNames <- names(readGrgList)
+        metadata(se)$readId <- mcols(readGrgList)$id
     }
     refSeqLevels <- seqlevels(genomeSequence)
     GenomeInfoDb::seqlevels(se) <- refSeqLevels
@@ -211,9 +221,9 @@ bambu.processReadsByFile <- function(bam.file, genomeSequence, annotations,
                              fusionMode = fusionMode,
                              verbose = verbose)
 
-    metadata(se)$samples = names(bam.file)[1]
-    metadata(se)$sampleNames = names(bam.file)[1]
-    if(!isFALSE(demultiplexed))metadata(se)$samples =  levels(mcols(readGrgList)$BC)                         
+    metadata(se)$samples <- names(bam.file)[1]
+    metadata(se)$sampleNames <- names(bam.file)[1]
+    if(!isFALSE(demultiplexed)) metadata(se)$samples <- levels(mcols(readGrgList)$BC)                         
     return(se)
 }
 
@@ -227,44 +237,48 @@ bambu.readsByFile <- function(bam.file, genomeSequence, annotations,
     verbose = FALSE, trackReads = FALSE, fusionMode = FALSE, demultiplexed = FALSE, 
     cleanReads = TRUE, dedupUMI = FALSE, index = 0, barcodesToFilter = NULL) {
     readGrgList <- prepareDataFromBam(bam.file[[1]], verbose = verbose, yieldSize = yieldSize, use.names = trackReads, demultiplexed = demultiplexed, cleanReads = cleanReads, dedupUMI = dedupUMI)
-    if(!is.null(barcodesToFilter) & demultiplexed){ readGrgList = readGrgList[!mcols(readGrgList)$CB %in% barcodesToFilter]}
+    
+    if(!is.null(barcodesToFilter) & !isFALSE(demultiplexed)) readGrgList <- readGrgList[!mcols(readGrgList)$BC %in% barcodesToFilter]
+    
     if(verbose) message("Number of alignments/reads: ",length(readGrgList))
-    warnings = c()
-    warnings = seqlevelCheckReadsAnnotation(readGrgList, annotations)
-    if(verbose & length(warnings) > 0) {warning(paste(warnings,collapse = "\n"))}
+    
+    warnings <- c()
+    warnings <- seqlevelCheckReadsAnnotation(readGrgList, annotations)
+    
+    if(verbose & length(warnings) > 0) warning(paste(warnings,collapse = "\n"))
     #check seqlevels for consistency, drop ranges not present in genomeSequence
     refSeqLevels <- seqlevels(genomeSequence)
     if (!all(seqlevels(readGrgList) %in% refSeqLevels)) {
         refSeqLevels <- intersect(refSeqLevels, seqlevels(readGrgList))
         if (!all(seqlevels(annotations) %in% refSeqLevels)&(!(length(annotations)==0))) {
           refSeqLevels <- intersect(refSeqLevels, seqlevels(annotations))
-          warningText = paste0("not all chromosomes from annotations present in ", 
+          warningText <- paste0("not all chromosomes from annotations present in ", 
                                "reference genome sequence, annotations without reference genomic sequence ",
                                "are dropped")
-          warnings = c(warnings, warningText)
-          if(verbose){warning(warningText)}
+          warnings <- c(warnings, warningText)
+          if(verbose) warning(warningText)
           annotations <- keepSeqlevels(annotations, value = refSeqLevels,
                                        pruning.mode = "coarse")
         }
-        warningText = paste0("not all chromosomes from reads present in reference ",
+        warningText <- paste0("not all chromosomes from reads present in reference ",
                              "genome sequence, reads without reference chromosome sequence are dropped")
-        warnings = c(warnings, warningText)
-        if(verbose){warning(warningText)}
+        warnings <- c(warnings, warningText)
+        if(verbose) warning(warningText)
         readGrgList <- keepSeqlevels(readGrgList, value =  refSeqLevels,
                                      pruning.mode = "coarse")
         # reassign Ids after seqlevels are dropped
         mcols(readGrgList)$id <- seq_along(readGrgList) 
     }
     #removes reads that are outside genome coordinates
-    badReads = which(max(end(ranges(readGrgList)))>=
+    badReads <- which(max(end(ranges(readGrgList)))>=
                          seqlengths(genomeSequence)[as.character(getChrFromGrList(readGrgList))])
       if(length(badReads) > 0 ){
-        readGrgList = readGrgList[-badReads]
-        warningText = paste0(length(badReads), " reads are mapped outside the provided ",
+        readGrgList <- readGrgList[-badReads]
+        warningText <- paste0(length(badReads), " reads are mapped outside the provided ",
                              "genomic regions. These reads will be dropped. Check you are using the ",
                              "same genome used for the alignment")
-        warnings = c(warnings, warningText)
-        if(verbose){warning(warningText)}
+        warnings <- c(warnings, warningText)
+        if(verbose) warning(warningText)
       }
       
       ### add ### 
@@ -272,9 +286,8 @@ bambu.readsByFile <- function(bam.file, genomeSequence, annotations,
       mcols(readGrgList)$id <- seq_along(readGrgList) 
       ### add ###
       if(verbose) message("Number of post-filter alignments/reads: ",length(readGrgList))
-      if(length(readGrgList) == 0) {
+      if(length(readGrgList) == 0)
         stop("No reads left after filtering.")
-      }
       
       ## add ###
       #if (isTRUE(demultiplexed)){
@@ -292,11 +305,13 @@ bambu.readsByFile <- function(bam.file, genomeSequence, annotations,
     return(readGrgList)
 }
 
+#' Construct read classes
+#' @noRd
 constructReadClasses <- function(readGrgList, genomeSequence, annotations,
     stranded = FALSE, min.readCount = 2, 
     fitReadClassModel = TRUE, min.exonOverlap = 10, defaultModels = NULL, returnModel = FALSE, 
     verbose = FALSE, processByChromosome = FALSE, trackReads = FALSE, fusionMode = FALSE){
-    warnings = c() ###TODO
+    warnings <- c() ###TODO
     
     if(processByChromosome){
         # construct read classes for each chromosome seperately 
@@ -311,10 +326,10 @@ constructReadClasses <- function(readGrgList, genomeSequence, annotations,
                                               annotations, stranded, verbose)
 
     }
-    metadata(se)$warnings = warnings
+    metadata(se)$warnings <- warnings
     if(trackReads){
-        metadata(se)$readNames = names(readGrgList)
-        metadata(se)$readId = mcols(readGrgList)$id
+        metadata(se)$readNames <- names(readGrgList)
+        metadata(se)$readId <- mcols(readGrgList)$id
     }
     rm(readGrgList)
     refSeqLevels <- seqlevels(genomeSequence)
@@ -331,15 +346,18 @@ constructReadClasses <- function(readGrgList, genomeSequence, annotations,
     return(se)
 }
 
+
+#' Low memory mode for construct read classes (processByChromosome)
+#' @noRd
 lowMemoryConstructReadClasses <- function(readGrgList, genomeSequence, 
                                           annotations, stranded, verbose,bam.file, fusionMode = FALSE){
     if(fusionMode){
-        readGrgList = list(readGrgList)
-        names(readGrgList) = c("fusion")
+        readGrgList <- list(readGrgList)
+        names(readGrgList) <- c("fusion")
     } else{
-        readGrgList = split(readGrgList, getChrFromGrList(readGrgList))
+        readGrgList <- split(readGrgList, getChrFromGrList(readGrgList))
     }
-    se = lapply(names(readGrgList),FUN = function(i){
+    se <- lapply(names(readGrgList),FUN = function(i){
         if(length(readGrgList[[i]]) == 0) return(NULL)
         # create error and strand corrected junction tables
         unlisted_junctions <- unlistIntrons(readGrgList[[i]], use.ids = TRUE)
@@ -350,9 +368,9 @@ lowMemoryConstructReadClasses <- function(readGrgList, genomeSequence,
                                               annotations, stranded, verbose)
         return(se.temp)
     })
-    se = se[!sapply(se, FUN = is.null)]
-    se = do.call("rbind",se)
-    rownames(se) = paste("rc", seq_len(nrow(se)), sep = ".")
+    se <- se[!sapply(se, FUN = is.null)]
+    se <- do.call("rbind",se)
+    rownames(se) <- paste("rc", seq_len(nrow(se)), sep = ".")
     return(se)
 }
 
@@ -360,62 +378,70 @@ lowMemoryConstructReadClasses <- function(readGrgList, genomeSequence,
 #' @importFrom GenomeInfoDb seqlevels
 #' @noRd
 seqlevelCheckReadsAnnotation <- function(reads, annotations){
-    warnings = c()
+    warnings <- c()
     if (length(intersect(seqlevels(reads),
                          seqlevels(annotations))) == 0)
-        warnings = c(warnings, paste0("no annotations with matching seqlevel styles, ",
+        warnings <- c(warnings, paste0("no annotations with matching seqlevel styles, ",
         "all missing chromosomes will use de-novo annotations"))
     if (!all(seqlevels(reads) %in% 
              seqlevels(annotations))) 
-        warnings = c(warnings, paste0("not all chromosomes present in reference annotations, ",
+        warnings <- c(warnings, paste0("not all chromosomes present in reference annotations, ",
             "annotations might be incomplete. Please compare objects ",
             "on the same reference"))
     return(warnings)
 }
 
+
+#' Split read class files
+#' @importFrom dplyr Matrix
+#' @noRd
 splitReadClassFiles = function(readClassFile){
-    distTable = metadata(metadata(readClassFile)$readClassDist)$distTable  
-    eqClasses = distTable %>% group_by(eqClassById) %>% 
+    distTable <- metadata(metadata(readClassFile)$readClassDist)$distTable  
+    eqClasses <- distTable %>% group_by(eqClassById) %>% 
         distinct(eqClassById, readCount,GENEID, totalWidth, firstExonWidth, .keep_all = TRUE)
-    eqClasses$sampleIDs = rowData(readClassFile)$sampleIDs[match(eqClasses$readClassId, rownames(readClassFile))]
-    eqClasses = eqClasses %>% summarise(nobs = sum(readCount),
+    eqClasses$sampleIDs <- rowData(readClassFile)$sampleIDs[match(eqClasses$readClassId, rownames(readClassFile))]
+    eqClasses <- eqClasses %>% summarise(nobs = sum(readCount),
                                                 sampleIDs = list(unlist(sampleIDs)))
-    counts.table = lapply(eqClasses$sampleIDs, FUN = function(x){table(x)})
-    counts = sparseMatrix(
+    counts.table <- tableFunction(eqClasses$sampleIDs)
+    counts <- sparseMatrix(
         i = rep(seq_along(counts.table), lengths(counts.table)),
         j = as.numeric(names(unlist(counts.table))),
         x = unlist(counts.table),
         dims = c(nrow(eqClasses), length(metadata(readClassFile)$samples)))
     #incompatible counts
-    distTable = metadata(metadata(readClassFile)$readClassDist)$distTable.incompatible
+    distTable <- metadata(metadata(readClassFile)$readClassDist)$distTable.incompatible
     if(nrow(distTable)==0) {
-        counts.incompatible = sparseMatrix(i= 1, j = 1, x = 0,
+        counts.incompatible <- sparseMatrix(i= 1, j = 1, x = 0,
         dims = c(1, length(metadata(readClassFile)$samples)))
-        rownames(counts.incompatible) = "TODO"
+        rownames(counts.incompatible) <- "TODO"
     } else{
-        distTable$sampleIDs = rowData(readClassFile)$sampleIDs[match(distTable$readClassId, rownames(readClassFile))]
-        distTable = distTable %>% group_by(GENEID.i) %>% summarise(counts = sum(readCount),
+        distTable$sampleIDs <- rowData(readClassFile)$sampleIDs[match(distTable$readClassId, rownames(readClassFile))]
+        distTable <- distTable %>% group_by(GENEID.i) %>% summarise(counts = sum(readCount),
                     sampleIDs = list(unlist(sampleIDs)))
-        counts.table = lapply(distTable$sampleIDs, FUN = function(x){table(x)})
-        counts.incompatible = sparseMatrix(
+        counts.table <- lapply(distTable$sampleIDs, FUN = function(x){table(x)})
+        counts.incompatible <- sparseMatrix(
             i = rep(seq_along(counts.table), lengths(counts.table)),
             j = as.numeric(names(unlist(counts.table))),
             x = unlist(counts.table),
             dims = c(nrow(distTable), length(metadata(readClassFile)$samples)))
-        colnames(counts.incompatible) = metadata(readClassFile)$samples
-        rownames(counts.incompatible) = distTable$GENEID.i 
+        colnames(counts.incompatible) <- metadata(readClassFile)$samples
+        rownames(counts.incompatible) <- distTable$GENEID.i 
     }
-    colnames(counts) = metadata(readClassFile)$samples
-    metadata(readClassFile)$eqClassById = eqClasses$eqClassById
+    colnames(counts) <- metadata(readClassFile)$samples
+    metadata(readClassFile)$eqClassById <- eqClasses$eqClassById
     #rownames(counts) = eqClasses$eqClassById
-    metadata(readClassFile)$countMatrix = counts
-    metadata(readClassFile)$incompatibleCountMatrix = counts.incompatible  
-    return(readClassFile )
+    metadata(readClassFile)$countMatrix <- counts
+    metadata(readClassFile)$incompatibleCountMatrix <- counts.incompatible  
+    return(readClassFile)
 }
 
-splitReadClassFilesByRC = function(readClassFile){
-    counts.table = lapply(rowData(readClassFile)$sampleIDs, FUN = function(x){table(x)})
-    counts = sparseMatrix(
+
+#' Split read class files by RC
+#' @importFrom Matrix
+#' @noRd
+splitReadClassFilesByRC <- function(readClassFile){
+    counts.table <- tableFunction(rowData(readClassFile)$sampleIDs)
+    counts <- sparseMatrix(
         i = rep(seq_along(counts.table), lengths(counts.table)),
         j = as.numeric(names(unlist(counts.table))),
         x = unlist(counts.table),
@@ -423,3 +449,8 @@ splitReadClassFilesByRC = function(readClassFile){
     return(counts)
 }
 
+#' table sample IDs list column
+#' @noRd
+tableFunction <- function(xList){
+    return(lapply(xList, function(x) table(x)))
+}
diff --git a/R/bambu.R b/R/bambu.R
index 18047be9..c36f5bb8 100644
--- a/R/bambu.R
+++ b/R/bambu.R
@@ -145,31 +145,38 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL,
     message(paste0("Running Bambu-v", "3.3.0"))
     if(!is.null(mode)){
         if(mode == "bulk"){
-            processByChromosome = FALSE
-            processByBam = TRUE
+            processByChromosome <- FALSE
+            processByBam <- TRUE
         }
         if(mode == "multiplexed"){
-            if(is.null(demultiplexed)) demultiplexed = TRUE
-            cleanReads = TRUE
-            opt.em = list(degradationBias = FALSE)
-            quant = FALSE
-            processByChromosome = TRUE
+            if(is.null(demultiplexed)) 
+                demultiplexed <- TRUE
+            cleanReads <- TRUE
+            opt.em <- list(degradationBias = FALSE)
+            quant <- FALSE
+            processByChromosome <- TRUE
         }
         if(mode == "fusion"){
-            NDR = 1
-            fusionMode = TRUE
+            NDR <- 1
+            fusionMode <- TRUE
         }
         if(mode == "debug"){
-            verbose = TRUE
-            trackReads = TRUE
-            returnDistTable = TRUE
+            verbose <- TRUE
+            trackReads <- TRUE
+            returnDistTable <- TRUE
         }
     }
-    if(lowMemory){message("lowMemory has been deprecated and split into processByChromosome and processByBam. Please see Documentation")}
-    if(is.null(annotations)) { annotations = GRangesList()
-    } else annotations <- checkInputs(annotations, reads,
-            readClass.outputDir = rcOutDir, genomeSequence = genome, discovery = discovery, 
+    if(lowMemory)
+        message("lowMemory has been deprecated and split into processByChromosome and processByBam. Please see Documentation")
+    
+    if(is.null(annotations)){ 
+        annotations <- GRangesList()
+    } else {
+        annotations <- checkInputs(annotations, reads,
+            readClass.outputDir = rcOutDir, 
+            genomeSequence = genome, discovery = discovery, 
             sampleNames = sampleNames, spatial = spatial)
+    }
     isoreParameters <- setIsoreParameters(isoreParameters = opt.discovery)
     #below line is to be compatible with earlier version of running bambu
     if(!is.null(isoreParameters$max.txNDR)) NDR = isoreParameters$max.txNDR
@@ -178,11 +185,13 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL,
     bpParameters <- setBiocParallelParameters(reads, ncore, verbose, demultiplexed)
 
     rm.readClassSe <- FALSE
-    readClassList = reads
-    isRDSs = all(sapply(reads, class)=="RangedSummarizedExperiment")
-    isBamFiles = !isRDSs
-    warnings = NULL
-    if(!isRDSs) isBamFiles = ifelse(!is(reads, "BamFileList"), all(grepl(".bam$", reads)), FALSE)
+    readClassList <- reads
+    isRDSs <- all(sapply(reads, class)=="RangedSummarizedExperiment")
+    isBamFiles <- !isRDSs
+    warnings <- NULL
+    if(!isRDSs) 
+        isBamFiles <- ifelse(!is(reads, "BamFileList"), 
+                             all(grepl(".bam$", reads)), FALSE)
     if (isBamFiles | is(reads, "BamFileList")) {
         if (length(reads) > 10 & (is.null(rcOutDir))) {
             rcOutDir <- tempdir() #>=10 samples, save to temp folder
@@ -196,11 +205,12 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL,
             genomeSequence = genome, 
             readClass.outputDir = rcOutDir, yieldSize = yieldSize, 
             bpParameters = bpParameters, stranded = stranded, verbose = verbose,
-            isoreParameters = isoreParameters, trackReads = trackReads, fusionMode = fusionMode, 
+            isoreParameters = isoreParameters, trackReads = trackReads, 
+            fusionMode = fusionMode, 
             processByChromosome = processByChromosome, processByBam = processByBam, 
             demultiplexed = demultiplexed,
-            sampleNames = sampleNames, cleanReads = cleanReads, dedupUMI = dedupUMI,
-            barcodesToFilter = barcodesToFilter)
+            sampleNames = sampleNames, cleanReads = cleanReads, 
+            dedupUMI = dedupUMI,barcodesToFilter = barcodesToFilter)
     }
 
   #warnings = handleWarnings(readClassList, verbose)
@@ -213,68 +223,82 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL,
         
         #### cluster based transcript discovery
         if(!is.null(clusters)){
-            annotations.clusters = isore.extendAnnotations.clusters(readClassList, annotations, clusters, NDR, 
+            annotations.clusters <- isore.extendAnnotations.clusters(readClassList,
+                annotations, clusters, NDR, 
                 isoreParameters, stranded, bpParameters, fusionMode, verbose = FALSE)  
-                metadata(extendedAnnotations)$clusters = annotations.clusters    
+            metadata(extendedAnnotations)$clusters <- annotations.clusters    
         }
-        annotations = extendedAnnotations
+        annotations <- extendedAnnotations
         
         if (!quant & !assignDist) return(annotations)
     }
   
     if(assignDist){
         message("--- Start calculating equivilance classes ---")
-        quantData = bplapply(readClassList, FUN = assignReadClasstoTranscripts, 
-            annotations = annotations, isoreParameters = isoreParameters, verbose = verbose, 
-            demultiplexed = demultiplexed, spatial = spatial, returnDistTable = returnDistTable,
-            trackReads = trackReads,
-            BPPARAM = bpParameters)                 
+        quantData <- bplapply(readClassList, 
+                              FUN = assignReadClasstoTranscripts, 
+                              annotations = annotations, 
+                              isoreParameters = isoreParameters, 
+                              verbose = verbose, 
+                              demultiplexed = demultiplexed, 
+                              spatial = spatial, 
+                              returnDistTable = returnDistTable,
+                              trackReads = trackReads,
+                              BPPARAM = bpParameters)
         if (!quant) return(quantData)
     }
 
     if (quant) {
         message("--- Start isoform EM quantification ---")
         if(!is.null(NDR) & !discovery)
-            annotations = setNDR(annotations, NDR, prefix = isoreParameters$prefix, 
+            annotations <- setNDR(annotations, NDR, 
+                                  prefix = isoreParameters$prefix, 
                 baselineFDR = isoreParameters[["baselineFDR"]], 
                 defaultModels2 = isoreParameters[["defaultModels"]])
         if(length(annotations)==0) stop("No valid annotations, if running
                                     de novo please try less stringent parameters")
         if(is.null(quantData)) stop("quantData must be provided or assignDist = TRUE")
-        GENEIDs.i = as.numeric(factor(unique(mcols(annotations)$GENEID)))
+        GENEIDs.i <- as.numeric(factor(unique(mcols(annotations)$GENEID)))
         start.ptm <- proc.time()
-        countsSeCompressed.all = NULL
-        ColNames = c()
+        countsSeCompressed.all <- NULL
+        ColNames <- c()
         for(i in seq_along(quantData)){
-            quantData_i = quantData[[i]]
+            quantData_i <- quantData[[i]]
             #load in the barcode clustering from file if provided
-            iter = seq_len(ncol(metadata(quantData_i)$countMatrix)) # iter is integer
+            iter <- seq_len(ncol(metadata(quantData_i)$countMatrix)) # iter is integer
             if(!is.null(clusters)){
                 if(!is.list(clusters)){
-                    clusterMaps = NULL
+                    clusterMaps <- NULL
                     for(j in seq_along(metadata(quantData_i)$sampleNames)){ #load in a file per sample name provided
-                        clusterMap = read.table(clusters[[j]], 
-                            sep = ifelse(grepl(".tsv$",clusters[[j]]), "\t", ","), header = FALSE)
-                        clusterMap[,1] = paste0(metadata(quantData_i)$sampleNames[j],"_",clusterMap[,1])
-                        clusterMaps = rbind(clusterMaps, clusterMap)                        
+                        clusterMap <- fread(clusters[[j]], header = FALSE, 
+                                            data.table = FALSE)
+                        # read.table(clusters[[j]], 
+                        #     sep = ifelse(grepl(".tsv$",clusters[[j]]), "\t", ","), 
+                        #     header = FALSE)
+                        clusterMap[,1] <- paste0(metadata(quantData_i)$sampleNames[j],
+                                                "_",clusterMap[,1])
+                        clusterMaps <- rbind(clusterMaps, clusterMap)                        
                     }
-                    clustering = splitAsList(clusterMaps[,1], clusterMaps[,2]) 
+                    clustering <- splitAsList(clusterMaps[,1], clusterMaps[,2]) 
                     rm(clusterMaps)
                     rm(clusterMap)
-                    iter = clustering
+                    iter <- clustering
 
                 } else{ #if clusters is a list
-                    if(length(quantData)>1){iter = clusters[[i]] #lowMemory mode
-                    }else(iter = do.call(c,clusters))
+                    if(length(quantData)>1){
+                        iter <- clusters[[i]] #lowMemory mode
+                    }else{
+                        iter <- do.call(c,clusters)
+                    }
                 }
             }
             countsSeCompressed <- bplapply(iter, FUN = function(j){ # previous i changed to j to avoid duplicated assignment 
                 #i = iter[i %in% colnames(metadata(quantData_i)$countMatrix)] #bug, after assignment, i become emptyprint(i)
-                countMatrix = unname(metadata(quantData_i)$countMatrix[,j]) # same here 
-                incompatibleCountMatrix = unname(metadata(quantData_i)$incompatibleCountMatrix[,j]) # same here
+                countMatrix <- unname(metadata(quantData_i)$countMatrix[,j]) # same here 
+                incompatibleCountMatrix <- unname(metadata(quantData_i)$incompatibleCountMatrix[,j]) # same here
                 if(!is.null(dim(countMatrix))){
-                    countMatrix = rowSums(countMatrix)
-                    incompatibleCountMatrix = rowSums(metadata(quantData_i)$incompatibleCountMatrix[,j]) # same here
+                    countMatrix <- rowSums(countMatrix)
+                    incompatibleCountMatrix <- rowSums(metadata(quantData_i)$incompatibleCountMatrix[,j]) # same here
                 }
                 return(bambu.quantify(readClassDt = metadata(quantData_i)$readClassDt, countMatrix = countMatrix, 
                                             incompatibleCountMatrix = data.table(GENEID.i = as.numeric(rownames(metadata(quantData_i)$incompatibleCountMatrix)), counts = incompatibleCountMatrix),
@@ -285,26 +309,26 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL,
             end.ptm <- proc.time()
             message("Total Time ", round((end.ptm - start.ptm)[3] / 60, 3), " mins.")
             if(!is.null(clusters)){
-                ColNames = c(ColNames, names(iter))
+                ColNames <- c(ColNames, names(iter))
             } else{
-                ColNames = c(ColNames, colnames(quantData_i)) 
+                ColNames <- c(ColNames, colnames(quantData_i)) 
             }
-            countsSeCompressed.all = c(countsSeCompressed.all, countsSeCompressed)
+            countsSeCompressed.all <- c(countsSeCompressed.all, countsSeCompressed)
         }
-        countsSeCompressed.all$colnames = ColNames            
+        countsSeCompressed.all$colnames <- ColNames            
         countsSe <- combineCountSes(countsSeCompressed.all, annotations)
         if(returnDistTable){
             distTables = list()
             for(i in seq_along(quantData)){
-                distTables[[i]] = metadata(quantData[[i]])$distTable
+                distTables[[i]] <- metadata(quantData[[i]])$distTable
             }
-            metadata(countsSe)$distTables = distTables
+            metadata(countsSe)$distTables <- distTables
         }
         #metadata(countsSe)$warnings = warnings
 
-        ColData = generateColData(colnames(countsSe), clusters, demultiplexed, spatial)
-        colData(countsSe) = ColData
-        colnames(countsSe) = ColData[,1]
+        ColData <- generateColData(colnames(countsSe), clusters, demultiplexed, spatial)
+        colData(countsSe) <- ColData
+        colnames(countsSe) <- ColData[,1]
         return(countsSe)
     }
 }

From c66f216ed1287b40e29a6fb2705ce999a6fddc88 Mon Sep 17 00:00:00 2001
From: Chen Ying 
Date: Tue, 21 Jan 2025 16:57:34 +0800
Subject: [PATCH 177/189] allow reads be NULL when quantData is provided for
 quant mode only

---
 R/bambu.R                  | 127 +++++++++++++++++++------------------
 R/bambu_utilityFunctions.R |  40 +++++++-----
 2 files changed, 92 insertions(+), 75 deletions(-)

diff --git a/R/bambu.R b/R/bambu.R
index c36f5bb8..13f2f3c0 100644
--- a/R/bambu.R
+++ b/R/bambu.R
@@ -175,7 +175,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL,
         annotations <- checkInputs(annotations, reads,
             readClass.outputDir = rcOutDir, 
             genomeSequence = genome, discovery = discovery, 
-            sampleNames = sampleNames, spatial = spatial)
+            sampleNames = sampleNames, spatial = spatial,quantData = quantData)
     }
     isoreParameters <- setIsoreParameters(isoreParameters = opt.discovery)
     #below line is to be compatible with earlier version of running bambu
@@ -183,73 +183,80 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL,
     
     emParameters <- setEmParameters(emParameters = opt.em)
     bpParameters <- setBiocParallelParameters(reads, ncore, verbose, demultiplexed)
-
-    rm.readClassSe <- FALSE
-    readClassList <- reads
-    isRDSs <- all(sapply(reads, class)=="RangedSummarizedExperiment")
-    isBamFiles <- !isRDSs
-    warnings <- NULL
-    if(!isRDSs) 
-        isBamFiles <- ifelse(!is(reads, "BamFileList"), 
-                             all(grepl(".bam$", reads)), FALSE)
-    if (isBamFiles | is(reads, "BamFileList")) {
-        if (length(reads) > 10 & (is.null(rcOutDir))) {
-            rcOutDir <- tempdir() #>=10 samples, save to temp folder
-            message("There are more than 10 samples, read class files
+    # only when reads is not NULL, this proceed, otherwise, it will jump to quant step
+    if(!is.null(reads)){ 
+        rm.readClassSe <- FALSE
+        readClassList <- reads
+        isRDSs <- all(sapply(reads, class)=="RangedSummarizedExperiment")
+        isBamFiles <- !isRDSs
+        warnings <- NULL
+        if(!isRDSs) 
+            isBamFiles <- ifelse(!is(reads, "BamFileList"), 
+                                 all(grepl(".bam$", reads)), FALSE)
+        if (isBamFiles | is(reads, "BamFileList")) {
+            if (length(reads) > 10 & (is.null(rcOutDir))) {
+                rcOutDir <- tempdir() #>=10 samples, save to temp folder
+                message("There are more than 10 samples, read class files
                 will be temporarily saved to ", rcOutDir,
-                    " for more efficient processing")
-            rm.readClassSe <- TRUE # remove temporary read class files 
+                        " for more efficient processing")
+                rm.readClassSe <- TRUE # remove temporary read class files 
+            }
+            message("--- Start generating read class files ---")
+            readClassList <- bambu.processReads(reads, annotations, 
+                                                genomeSequence = genome, 
+                                                readClass.outputDir = rcOutDir, yieldSize = yieldSize, 
+                                                bpParameters = bpParameters, stranded = stranded, verbose = verbose,
+                                                isoreParameters = isoreParameters, trackReads = trackReads, 
+                                                fusionMode = fusionMode, 
+                                                processByChromosome = processByChromosome, processByBam = processByBam, 
+                                                demultiplexed = demultiplexed,
+                                                sampleNames = sampleNames, cleanReads = cleanReads, 
+                                                dedupUMI = dedupUMI,barcodesToFilter = barcodesToFilter)
         }
-        message("--- Start generating read class files ---")
-        readClassList <- bambu.processReads(reads, annotations, 
-            genomeSequence = genome, 
-            readClass.outputDir = rcOutDir, yieldSize = yieldSize, 
-            bpParameters = bpParameters, stranded = stranded, verbose = verbose,
-            isoreParameters = isoreParameters, trackReads = trackReads, 
-            fusionMode = fusionMode, 
-            processByChromosome = processByChromosome, processByBam = processByBam, 
-            demultiplexed = demultiplexed,
-            sampleNames = sampleNames, cleanReads = cleanReads, 
-            dedupUMI = dedupUMI,barcodesToFilter = barcodesToFilter)
-    }
-
-  #warnings = handleWarnings(readClassList, verbose)
-    if (!discovery & !assignDist & !quant) return(readClassList)
-    if (discovery) {
-        message("--- Start extending annotations ---")
-        extendedAnnotations <- bambu.extendAnnotations(readClassList, annotations, NDR,
-                                            isoreParameters, stranded, bpParameters, fusionMode, verbose)
-        metadata(extendedAnnotations)$warnings = warnings
         
-        #### cluster based transcript discovery
-        if(!is.null(clusters)){
-            annotations.clusters <- isore.extendAnnotations.clusters(readClassList,
-                annotations, clusters, NDR, 
-                isoreParameters, stranded, bpParameters, fusionMode, verbose = FALSE)  
-            metadata(extendedAnnotations)$clusters <- annotations.clusters    
+        #warnings = handleWarnings(readClassList, verbose)
+        if (!discovery & !assignDist & !quant) return(readClassList)
+        if (discovery) {
+            message("--- Start extending annotations ---")
+            extendedAnnotations <- bambu.extendAnnotations(readClassList, annotations, NDR,
+                                                           isoreParameters, stranded, bpParameters, fusionMode, verbose)
+            metadata(extendedAnnotations)$warnings = warnings
+            
+            #### cluster based transcript discovery
+            if(!is.null(clusters)){
+                annotations.clusters <- isore.extendAnnotations.clusters(readClassList,
+                                                                         annotations, clusters, NDR, 
+                                                                         isoreParameters, stranded, bpParameters, fusionMode, verbose = FALSE)  
+                metadata(extendedAnnotations)$clusters <- annotations.clusters    
+            }
+            annotations <- extendedAnnotations
+            
+            if (!quant & !assignDist) return(annotations)
+        }
+        if(assignDist){
+            message("--- Start calculating equivilance classes ---")
+            quantData <- bplapply(readClassList, 
+                                  FUN = assignReadClasstoTranscripts, 
+                                  annotations = annotations, 
+                                  isoreParameters = isoreParameters, 
+                                  verbose = verbose, 
+                                  demultiplexed = demultiplexed, 
+                                  spatial = spatial, 
+                                  returnDistTable = returnDistTable,
+                                  trackReads = trackReads,
+                                  BPPARAM = bpParameters)
+            if (!quant) return(quantData)
         }
-        annotations <- extendedAnnotations
-        
-        if (!quant & !assignDist) return(annotations)
-    }
-  
-    if(assignDist){
-        message("--- Start calculating equivilance classes ---")
-        quantData <- bplapply(readClassList, 
-                              FUN = assignReadClasstoTranscripts, 
-                              annotations = annotations, 
-                              isoreParameters = isoreParameters, 
-                              verbose = verbose, 
-                              demultiplexed = demultiplexed, 
-                              spatial = spatial, 
-                              returnDistTable = returnDistTable,
-                              trackReads = trackReads,
-                              BPPARAM = bpParameters)
-        if (!quant) return(quantData)
     }
+    
+   
 
     if (quant) {
         message("--- Start isoform EM quantification ---")
+        # the step below is a bit confusing but it seems to be the only way 
+        # if discovery == TRUE, extendAnnotations happen already
+        # if users want discovery at this step, assign a desired value for NDR with discovery being FALSE
+        # here also reads need to be not file or bam file or rc file
         if(!is.null(NDR) & !discovery)
             annotations <- setNDR(annotations, NDR, 
                                   prefix = isoreParameters$prefix, 
diff --git a/R/bambu_utilityFunctions.R b/R/bambu_utilityFunctions.R
index 7c7d1bcd..50eae74f 100644
--- a/R/bambu_utilityFunctions.R
+++ b/R/bambu_utilityFunctions.R
@@ -112,25 +112,35 @@ checkInputs <- function(annotations, reads, readClass.outputDir, genomeSequence,
         if (!dir.exists(readClass.outputDir)) 
             stop("output folder does not exist")
     }
-
-    if (is(reads, "BamFileList")){
-        if(is.null(genomeSequence)){
-            stop("A genome must be provided when running bambu from bam files")
-        }
-    } else{
-    # ===# Check whether provided read files are all in the same format (.bam or .rds) #===#
-        isRDSs = all(sapply(reads, class)=="RangedSummarizedExperiment")
-        if(!isRDSs){
-            if (!all(grepl(".bam$", reads)) & !all(grepl(".rds$", reads)))
-                    stop("Reads should either be: a vector of paths to .bam files, ", 
-                    "a vector of paths to Bambu RCfile .rds files, ",
-                    "or a list of loaded Bambu RCfiles")
-            # if bam files are loaded in check that a genome is provided
-            if (all(grepl(".bam$", reads)) & is.null(genomeSequence)){
+    if(!is.null(reads)){
+        if (is(reads, "BamFileList")){
+            if(is.null(genomeSequence)){
                 stop("A genome must be provided when running bambu from bam files")
             }
+        } else{
+            # ===# Check whether provided read files are all in the same format (.bam or .rds) #===#
+            isRDSs <- all(sapply(reads, class)=="RangedSummarizedExperiment")
+            # there is a bug here, when reads is NULL, isRDSs == TRUE
+            if(!isRDSs){
+                if (!all(grepl(".bam$", reads)) & !all(grepl(".rds$", reads)))
+                    stop("Reads should either be: a vector of paths to .bam files, ", 
+                         "a vector of paths to Bambu RCfile .rds files, ",
+                         "or a list of loaded Bambu RCfiles")
+                # if bam files are loaded in check that a genome is provided
+                if (all(grepl(".bam$", reads)) & is.null(genomeSequence)){
+                    stop("A genome must be provided when running bambu from bam files")
+                }
+            }
         }
+    }else if(is.null(quantData)){
+        stop("Please provide either reads or quantData!",
+             "Reads should either be: a vector of paths to .bam files, ", 
+             "a vector of paths to Bambu RCfile .rds files, ",
+             "or a list of loaded Bambu RCfiles. ",
+             "quantData should be output from bambu with ",
+             "assignDist = TRUE and quant = FALSE")
     }
+    
     ## check genomeSequence can't be FaFile in Windows as faFile will be dealt
     ## strangely in windows system
     if (.Platform$OS.type == "windows") {

From b2be43361829fc81230f0464d766740c32b636ba Mon Sep 17 00:00:00 2001
From: Chen Ying 
Date: Tue, 21 Jan 2025 17:01:11 +0800
Subject: [PATCH 178/189] fix typo

---
 R/bambu_utilityFunctions.R | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/R/bambu_utilityFunctions.R b/R/bambu_utilityFunctions.R
index 50eae74f..03f92434 100644
--- a/R/bambu_utilityFunctions.R
+++ b/R/bambu_utilityFunctions.R
@@ -75,7 +75,8 @@ updateParameters <- function(Parameters, Parameters.default) {
 #' @param readClass.outputDir path to readClass output directory
 #' @importFrom methods is
 #' @noRd
-checkInputs <- function(annotations, reads, readClass.outputDir, genomeSequence, discovery, sampleNames, spatial){
+checkInputs <- function(annotations, reads, readClass.outputDir, genomeSequence, 
+                        discovery, sampleNames, spatial, quantData){
     # ===# Check annotation inputs #===#
     if (!is.null(annotations)) {
         if (is(annotations, "CompressedGRangesList")) {

From e2e300a5f6a5e8bc209574e90436aad44d092cc9 Mon Sep 17 00:00:00 2001
From: Chen Ying 
Date: Wed, 22 Jan 2025 15:20:16 +0800
Subject: [PATCH 179/189] update documentation

---
 R/bambu.R | 10 ++--------
 README.md | 31 +++++++++++++++++--------------
 2 files changed, 19 insertions(+), 22 deletions(-)

diff --git a/R/bambu.R b/R/bambu.R
index 13f2f3c0..536354c3 100644
--- a/R/bambu.R
+++ b/R/bambu.R
@@ -142,7 +142,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL,
     fusionMode = FALSE, verbose = FALSE, demultiplexed = FALSE, spatial = NULL, quantData = NULL,
     sampleNames = NULL, cleanReads = FALSE, dedupUMI = FALSE, barcodesToFilter = NULL, clusters = NULL,
     processByChromosome = FALSE, processByBam = TRUE) {
-    message(paste0("Running Bambu-v", "3.3.0"))
+    message(paste0("Running Bambu-v", "3.9.0"))
     if(!is.null(mode)){
         if(mode == "bulk"){
             processByChromosome <- FALSE
@@ -249,15 +249,9 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL,
         }
     }
     
-   
-
     if (quant) {
         message("--- Start isoform EM quantification ---")
-        # the step below is a bit confusing but it seems to be the only way 
-        # if discovery == TRUE, extendAnnotations happen already
-        # if users want discovery at this step, assign a desired value for NDR with discovery being FALSE
-        # here also reads need to be not file or bam file or rc file
-        if(!is.null(NDR) & !discovery)
+        if(!is.null(NDR) & !discovery)# this step is used when reset NDR is needed 
             annotations <- setNDR(annotations, NDR, 
                                   prefix = isoreParameters$prefix, 
                 baselineFDR = isoreParameters[["baselineFDR"]], 
diff --git a/README.md b/README.md
index 956700f7..6e710ec6 100755
--- a/README.md
+++ b/README.md
@@ -365,12 +365,14 @@ rowData(se[[1]])
 |chr.rc|The chromosome name the read class is found on|
 |strand.rc|The strand of the read class|
 |startSD|The standard deviation of the aligned genomic start positions of all reads assigned to the read class|
+|endSD|The standard deviation of the aligned genomic end positions of all reads assigned to the read class|
 |readCount.posStrand|The number of reads assigned to this read class that aligned to the positive strand|
 |intronStarts|A comma separated character vector of intron start coordinates|
 |intronEnds|A comma separated character vector of intron end coordinates|
 |confidenceType|Category of confidence: 
     **highConfidenceJunctionReads** - the read class contain no low confidence junctions 
     **lowConfidenceJunctionReads** - the read class contains low confidence junctions 
     **unsplicedWithin** - single exon read class that is within the exon boundaries of an annotation 
     **unsplicedNew** - single exon read class that does not fully overlap with annotated exons|
 |readCount|The number of reads assigned to this read class|
-|readId *only present when trackReads = TRUE|An integer list of bambu internal read ids that belong to the read class. (See the metadata of the object for full read names)|
+|readIds|An integer list of bambu internal read ids that belong to the read class. (See the metadata of the object for full read names)|
+|sampleIds|An integer list of bambu internal sample ids based on barcodes.|
 |GENEID|The gene ID the transcript is associated with|
 |novelGene|A logical that is true if the read class belongs to a novel gene (does not overlap with an annotated gene loci)|
 |numExons|The number of exons the read class has|
@@ -382,8 +384,8 @@ rowData(se[[1]])
 |numAend|An integer counting the number of A nucleotides found within a 20bp window centered on the read class genomic end position|
 |numTstart|An integer counting the number of T nucleotides found within a 20bp window centered on the read class genomic start position|
 |numTend|An integer counting the number of T nucleotides found within a 20bp window centered on the read class genomic end position|
-|txScore|This is the TPS generated by the sample trained model|
 |txScore.noFit|This is the TPS generated by the pretrained model|
+|txScore|This is the TPS generated by the sample trained model|
 
 
 ### Tracking read-to-transcript assignment
@@ -476,9 +478,9 @@ If you want to run Bambu-Clump for single-cell or spatial analysis stand alone a
 
 #### Read Class Construction:
 
-**reads**: provided bam files must have barcodes in the read name or in the BC tag. Alternatively a csv file can be provided to demultiplexed mapping the read names to barcodes. For exact requirements see https://github.com/GoekeLab/bambu-singlecell-spatial.
    
+**reads**: provided bam files should have barcodes in the read name or in the BC tag ( and UG tag for UMI identifiers). In the case where both tags and read names contain barcode information, tags will be used a prior. If not, a regular delimited headerless file that contain the demultiplexing information for each read should be provided to demultiplexed argument below. For exact requirements see https://github.com/GoekeLab/bambu-singlecell-spatial.
    
 
-**demultiplexed**: must be set to TRUE (or be a barcode map). This will cause bambu to look for barcodes and seperate reads by barcode rather than sample. 
    
+**demultiplexed**: should be either set to TRUE or the path to barcode mapping file. Otherwise, bambu will not look for barcodes and seperate reads by barcode rather than sample. 
    
 
 Optional:
 
@@ -486,12 +488,12 @@ Optional:
 
 **sampleNames**: A vector of characters assigning names to each sample in the reads argument. By default the sample names are taken from the file names and appended to the barcodes in order to differentiate them. If your sample names are the same across multiple files, but matching barcodes between the samples should be counted seperately, provide them with different sample names using this argument. Similiarly if your samples have different names, but overlapping barcodes should be counted together, give them the same sample name with this argument.  
    
 
-**dedupUMI**: A logical TRUE/FALSE.   
    
+**dedupUMI**: A logical TRUE/FALSE.  
    
 
 **barcodesToFilter**: A string vector indicating barcodes to be filtered out.  
     
 
 ```rscript
-readClassFile = bambu(reads = samples, annotations = annotations, genome = "$genome", ncore = $params.ncore, discovery = FALSE, quant = FALSE, demultiplexed = barcode_maps, verbose = TRUE, assignDist = FALSE, lowMemory = as.logical("$params.lowMemory"), yieldSize = 10000000, sampleNames = ids, cleanReads = as.logical($cleanReads), dedupUMI = as.logical($deduplicateUMIs))
+readClassFile = bambu(reads = samples, annotations = annotations, genome = fa.file, ncore = 1, discovery = FALSE, quant = FALSE, demultiplexed = barcode_maps, verbose = TRUE, assignDist = FALSE, lowMemory = as.logical("$params.lowMemory"), yieldSize = 10000000, sampleNames = ids, cleanReads = as.logical($cleanReads), dedupUMI = as.logical($deduplicateUMIs))
 ```
 
 #### Transcript Discovery:
@@ -499,7 +501,7 @@ readClassFile = bambu(reads = samples, annotations = annotations, genome = "$gen
 Transript discovery can be run as usual as typically bulk-level discovery is suitable. However cluster-level transcript discovery can be preformed using the clusters argument which can be redone done after clustering. 
 
 ```rscript
-extendedAnno = bambu(reads = readClassFile, annotations = annotations, genome = "$genome", ncore = $params.ncore, discovery = TRUE, quant = FALSE, demultiplexed = TRUE, verbose = FALSE, assignDist = FALSE)
+extendedAnno = bambu(reads = readClassFile, annotations = annotations, genome = fa.file, ncore = 1, discovery = TRUE, quant = FALSE, demultiplexed = TRUE, verbose = FALSE, assignDist = FALSE)
 ```
 
 #### Read Class Assignment:
@@ -509,7 +511,7 @@ This step was previously performed together with the quantification, but can be
 **spatial**: This should be a path to your barcode whitelist that also contians the x and y coordinates as extra columns. 
 
 ```rscript
-quantData = bambu(reads = readClassFile, annotations = extendedAnno, genome = "$genome", ncore = $params.ncore, discovery = FALSE, quant = FALSE, demultiplexed = TRUE, verbose = FALSE, opt.em = list(degradationBias = FALSE), assignDist = TRUE, spatial = spatial)
+quantData = bambu(reads = readClassFile, annotations = extendedAnno, genome = fa.file, ncore = 1, discovery = FALSE, quant = FALSE, demultiplexed = TRUE, verbose = FALSE, opt.em = list(degradationBias = FALSE), assignDist = TRUE, spatial = spatial)
 ```
 
 #### EM quantification:
@@ -641,14 +643,15 @@ rowData(se)
 |---|---|
 |TXNAME|The transcript name for the transcript. Will use either the transcript name from the provided annotations or tx.X if it is a novel transcript where X is a unique integer.|
 |GENEID|The gene name for the transcript. Will use either the gene name from the provided annotations or gene.X if it is a novel transcript where X is a unique integer.| 
-|eqClass|A character vector with the transcript names of all the equivalent transcripts (those which have this transcripts contiguous exon junctions)|
-|txId|A bambu specific transcript id used for indexing purposes
-|eqClassById|A integer list with the transcript ids of all equivalent transcripts
+|NDR|The NDR score calculated for the transcript|
+|novelGene|A logical variable that is true if transcript model is from a novel gene (does not overlap with an annotated gene loci)|
+|novelTranscript|A logical variable that is true if transcript model is novel  (passing NDR threshold)|
 |txClassDescription|A concatenated string containing the classes the transcript falls under: 
     **annotation** - Transcript matches an annotation transcript 
     **allNew** - All the intron-junctions are novel 
     **newFirstJunction** - the first junction is novel and at least one other junction matches an annotated transcript 
     **newLastJunction** - the last junction is novel and at least one other junction matches an annotated transcript 
     **newJunction** - an internal junction is novel and at least one other internal junction matches an annotated transcript 
     **newWithin** -  A novel transcript with matching junctions but is not a subset of an annotation 
     **unsplicedNew** - A single exon transcript that doesn’t completely overlap with annotations 
     **compatible** - Is a subset of an annotated transcript 
     **newFirstExon** - The first exon is novel 
     **newLastExon** - The last exon is novel|
 |readCount|The number of full length reads associated with this transcript (filtered by min.readCount)|
-|NDR|The NDR score calculated for the transcript|
 |relReadCount|The proportion of reads this transcript has relative to all reads assigned to its gene|
 |relSubsetCount|The proportion of reads this transcript has relative to all reads that either fully or partially match this transcript|
+|txId|A bambu specific transcript id used for indexing purposes
+|eqClassById|A integer list with the transcript ids of all equivalent transcripts
 |maxTxScore|The maximum model score across samples from the sample-trained model. Used internally by Bambu to calculate NDR scores|
 |maxTxScore.noFit|The maximum model score across samples from the pretrained model. Used internally by Bambu to recommend NDR thresholds|
 
@@ -676,9 +679,9 @@ metadata(rowRanges(se))$warnings
 
 ### Release History
 
-**bambu v3.3.0**
+**bambu v3.9.0**
 
-Release date: 2024-October-28
+Release date: 2025-xxx-xx
 
 - Subset transcripts and those above the NDR threshold are placed into the metadata of the annotations in $subsetTranscripts and $lowConfidenceTranscripts respectively (when filtered out by default).
 - adds the setNDR function

From 7e88470ae417deedd7a36639ab7dbbe73cbed354 Mon Sep 17 00:00:00 2001
From: Chen Ying 
Date: Wed, 22 Jan 2025 15:20:45 +0800
Subject: [PATCH 180/189] add comment message to understand codes better

---
 R/bambu-extendAnnotations-utilityCombine.R | 15 +++++++++------
 1 file changed, 9 insertions(+), 6 deletions(-)

diff --git a/R/bambu-extendAnnotations-utilityCombine.R b/R/bambu-extendAnnotations-utilityCombine.R
index 48d11844..2836c2eb 100644
--- a/R/bambu-extendAnnotations-utilityCombine.R
+++ b/R/bambu-extendAnnotations-utilityCombine.R
@@ -19,7 +19,10 @@ isore.combineTranscriptCandidates <- function(readClassList,
         min.readCount, min.readFractionByGene, 
         min.txScore.multiExon, min.txScore.singleExon, verbose) %>% data.table()
     combinedSplicedTranscripts[,confidenceType := "highConfidenceJunctionReads"]
-    if (min.txScore.singleExon == 1) {return(combinedSplicedTranscripts)}
+    # when single exon min score is 1, skip unspliced transcripts combination 
+    # by right, estimated txScore will not reach 1 
+    if (min.txScore.singleExon == 1) 
+        return(combinedSplicedTranscripts)
     combinedUnsplicedTranscripts <- 
         combineUnsplicedTranscriptModels(readClassList, bpParameters, 
         stranded, min.readCount, min.readFractionByGene, 
@@ -36,11 +39,11 @@ isore.combineTranscriptCandidates <- function(readClassList,
 combineSplicedTranscriptModels <- function(readClassList, bpParameters, 
         min.readCount, min.readFractionByGene, min.txScore.multiExon, 
         min.txScore.singleExon, verbose){
-    bpParameters$progressbar = FALSE
+    bpParameters$progressbar <- FALSE
     options(scipen = 999) #maintain numeric basepair locations not sci.notfi.
     start.ptm <- proc.time()
     n_sample <- length(readClassList)
-    nGroups = max(ceiling(n_sample/10),min(bpworkers(bpParameters), 
+    nGroups <- max(ceiling(n_sample/10),min(bpworkers(bpParameters), 
                                             round(n_sample/2)))
     indexList <- sample(rep(seq_len(nGroups), length.out=n_sample))
     indexList <- splitAsList(seq_len(n_sample), indexList)
@@ -135,7 +138,7 @@ combineFeatureTibble <- function(combinedFeatureTibble,
             maxTxScore.noFit, NSampleReadCount, NSampleReadProp,NSampleTxScore, 
             starts_with('start'), starts_with('end'), starts_with('readCount'))
     } else { 
-        combinedTable = full_join(combinedFeatureTibble, 
+        combinedTable <- full_join(combinedFeatureTibble, 
             featureTibbleSummarised, by = c('intronStarts', 'intronEnds', 'chr',
             'strand'), suffix=c('.combined','.new')) %>% 
             mutate(NSampleReadCount=pmax0NA(NSampleReadCount.combined) + 
@@ -215,7 +218,7 @@ combineUnsplicedTranscriptModels <-
             min.readFractionByGene, min.txScore.multiExon,
             min.txScore.singleExon, verbose){
         start.ptm <- proc.time()
-        bpParameters$progressbar = FALSE
+        bpParameters$progressbar <- FALSE
         newUnsplicedSeList <- 
             bplapply(seq_along(readClassList), function(sample_id)
                 extractNewUnsplicedRanges(readClassSe = 
@@ -292,7 +295,7 @@ reduceUnsplicedRanges <- function(rangesList, stranded){
 makeUnsplicedTibble <- function(combinedNewUnsplicedSe,newUnsplicedSeList,
         colDataNames,min.readCount, min.readFractionByGene,
         min.txScore.multiExon, min.txScore.singleExon, bpParameters){
-        bpParameters$progressbar = FALSE
+        bpParameters$progressbar <- FALSE
     newUnsplicedTibble <- as_tibble(combinedNewUnsplicedSe) %>%
         rename(chr = seqnames) %>% select(chr, start, end, strand, row_id) %>%
         separate_rows(row_id, sep = "\\+") 

From 8bc682c3d97e6ec6c2c9fbad9c2ba86ac7ed4391 Mon Sep 17 00:00:00 2001
From: Chen Ying 
Date: Wed, 22 Jan 2025 15:34:57 +0800
Subject: [PATCH 181/189] update code style

---
 R/bambu-extendAnnotations-utilityExtend.R | 196 +++++++++++-----------
 1 file changed, 100 insertions(+), 96 deletions(-)

diff --git a/R/bambu-extendAnnotations-utilityExtend.R b/R/bambu-extendAnnotations-utilityExtend.R
index 338ea822..8d20ba7c 100644
--- a/R/bambu-extendAnnotations-utilityExtend.R
+++ b/R/bambu-extendAnnotations-utilityExtend.R
@@ -23,7 +23,9 @@ isore.extendAnnotations <- function(combinedTranscripts, annotationGrangesList,
                                                        rowDataSplicedTibble, annotationGrangesList, 
                                                        min.exonDistance, min.primarySecondaryDist,
                                                        min.primarySecondaryDistStartEnd, verbose)
-    } else{ rowDataFilteredSpliced = NULL}
+    } else{ 
+        rowDataFilteredSpliced <- NULL
+    }
     rowDataFilteredUnspliced <- rowDataTibble[which(confidenceTypeVec == "unsplicedNew"),]
     SEnRng <- addNewUnsplicedReadClasses(rowDataFilteredUnspliced, 
                                          rowDataFilteredSpliced, transcriptRanges$exons, 
@@ -98,19 +100,19 @@ filterTranscriptsByAnnotation <- function(rowDataCombined, annotationGrangesList
         rowDataCombined[!notCompatibleIds,], 
         exonRangesCombined[!notCompatibleIds])
     rowDataCombined$maxTxScore[grepl("compatible", rowDataCombined$readClassType) &
-        rowDataCombined$readClassType != "equal:compatible"]=-1
+        rowDataCombined$readClassType != "equal:compatible"] <- -1
     rowDataCombined$maxTxScore.noFit[grepl("compatible", rowDataCombined$readClassType) &
-        rowDataCombined$readClassType != "equal:compatible"]=-1
+        rowDataCombined$readClassType != "equal:compatible"] <- -1
   }
   #(2) remove transcripts below NDR threshold/identical junctions to annotations
-  rowDataCombined = calculateNDROnTranscripts(rowDataCombined, 
+  rowDataCombined <- calculateNDROnTranscripts(rowDataCombined, 
                         useTxScore = length(annotationGrangesList)==0)
   if(length(annotationGrangesList)>0){ #only recommend an NDR if its possible to calculate an NDR
-      NDR = recommendNDR(rowDataCombined, baselineFDR, NDR, defaultModels, verbose)
-  } else {
-      if(is.null(NDR)) NDR = 0.5
+      NDR <- recommendNDR(rowDataCombined, baselineFDR, NDR, defaultModels, verbose)
+  } else if(is.null(NDR)) {
+          NDR <- 0.5
   }
-  filterSet = (rowDataCombined$NDR <= NDR | rowDataCombined$readClassType == "equal:compatible")
+  filterSet <- (rowDataCombined$NDR <= NDR | rowDataCombined$readClassType == "equal:compatible")
   lowConfidenceTranscripts <- combindRowDataWithRanges(
         rowDataCombined[!filterSet,], 
         exonRangesCombined[!filterSet])
@@ -156,21 +158,21 @@ filterTranscriptsByAnnotation <- function(rowDataCombined, annotationGrangesList
 #' @noRd
 recommendNDR <- function(combinedTranscripts, baselineFDR = 0.1, NDR = NULL, defaultModels = defaultModels, verbose = FALSE){
     if(verbose) message("-- Predicting annotation completeness to determine NDR threshold --")
-    combinedTranscripts = combinedTranscripts[combinedTranscripts$maxTxScore.noFit >=0, ] #ignore filtered out read classes
-    equal = combinedTranscripts$readClassType == "equal:compatible"
-    equal[is.na(equal)] = FALSE
+    combinedTranscripts <- combinedTranscripts[combinedTranscripts$maxTxScore.noFit >=0, ] #ignore filtered out read classes
+    equal <- combinedTranscripts$readClassType == "equal:compatible"
+    equal[is.na(equal)] <- FALSE
     #add envirnment so poly() works
     attr(defaultModels$lmNDR[["terms"]], ".Environment") <- new.env(parent = parent.env(globalenv()))
-    baseline = predict(defaultModels$lmNDR, newdata=data.frame(NDR=baselineFDR))
-    attr(defaultModels$lmNDR[["terms"]], ".Environment") = c()
-
-    score = combinedTranscripts$maxTxScore.noFit
-    score[is.na(score)] = 0
-    NDRscores = calculateNDR(score, equal)
-    NDR.rec = predict(lm(NDRscores~poly(score,3,raw=TRUE)), newdata=data.frame(score=baseline))
-    NDR.rec = round(NDR.rec,3)
-    if(NDR.rec > 1){NDR.rec = 0.999}
-    if (NDR.rec < 0) {NDR.rec = 0}
+    baseline <- predict(defaultModels$lmNDR, newdata=data.frame(NDR=baselineFDR))
+    attr(defaultModels$lmNDR[["terms"]], ".Environment") <- c()
+
+    score <- combinedTranscripts$maxTxScore.noFit
+    score[is.na(score)] <- 0
+    NDRscores <- calculateNDR(score, equal)
+    NDR.rec <- predict(lm(NDRscores~poly(score,3,raw=TRUE)), newdata=data.frame(score=baseline))
+    NDR.rec <- round(NDR.rec,3)
+    if(NDR.rec > 1) NDR.rec <- 0.999
+    if (NDR.rec < 0) NDR.rec <- 0
     if(verbose) message("Recommended NDR for baseline FDR of ", baselineFDR, " = ", NDR.rec)
     if(NDR.rec > 0.5){
         message("A high NDR threshold is being recommended by Bambu indicating high levels of novel transcripts, ",
@@ -181,33 +183,29 @@ recommendNDR <- function(combinedTranscripts, baselineFDR = 0.1, NDR = NULL, def
     }
     
     #if users are using an NDR let them know if the recommended NDR is different
-    if(is.null(NDR)) 
-    {
-        NDR = NDR.rec
+    if(is.null(NDR)) {
+        NDR <- NDR.rec
         message("Using a novel discovery rate (NDR) of: ", NDR)
-    }
-    else{
-        if(abs(NDR.rec-NDR)>=0.1){
+    } else if(abs(NDR.rec-NDR)>=0.1){
             message(paste0("For your combination of sample and reference annotations we recommend an NDR of ", NDR.rec,
             ". You are currently using an NDR threshold of ", NDR, 
             ". A higher NDR is suited for samples where the reference annotations are poor and more novel transcripts are expected,", 
             "whereas a lower NDR is suited for samples with already high quality annotations"))
-        }
     }
     return(NDR)
 }
 
-recommendNDR.onAnnotations = function(annotations, prefix = "Bambu", baselineFDR = 0.1, defaultModels2 = defaultModels2){
-    mcols = mcols(annotations)[!is.na(mcols(annotations)$maxTxScore),]
-    equal = !grepl(prefix, mcols$TXNAME)
+recommendNDR.onAnnotations <- function(annotations, prefix = "Bambu", baselineFDR = 0.1, defaultModels2 = defaultModels2){
+    mcols <- mcols(annotations)[!is.na(mcols(annotations)$maxTxScore),]
+    equal <- !grepl(prefix, mcols$TXNAME)
     #add envirnment so poly() works
     attr(defaultModels2$lmNDR[["terms"]], ".Environment") <- new.env(parent = parent.env(globalenv()))
-    baseline = predict(defaultModels2$lmNDR, newdata=data.frame(NDR=baselineFDR))
-    attr(defaultModels2$lmNDR[["terms"]], ".Environment") = c()
-    score = mcols$maxTxScore.noFit
-    NDRscores = calculateNDR(score, equal)
-    NDR.rec = predict(lm(NDRscores~poly(score,3,raw=TRUE)), newdata=data.frame(score=baseline))
-    NDR.rec = round(NDR.rec,3)
+    baseline <- predict(defaultModels2$lmNDR, newdata=data.frame(NDR=baselineFDR))
+    attr(defaultModels2$lmNDR[["terms"]], ".Environment") <- c()
+    score <- mcols$maxTxScore.noFit
+    NDRscores <- calculateNDR(score, equal)
+    NDR.rec <- predict(lm(NDRscores~poly(score,3,raw=TRUE)), newdata=data.frame(score=baseline))
+    NDR.rec <- round(NDR.rec,3)
     return(NDR.rec)
 }
 
@@ -216,25 +214,27 @@ recommendNDR.onAnnotations = function(annotations, prefix = "Bambu", baselineFDR
 #' @noRd
 calculateNDROnTranscripts <- function(combinedTranscripts, useTxScore = FALSE){
       # calculate and filter by NDR
-    equal = combinedTranscripts$readClassType == "equal:compatible"
-    equal[is.na(equal)] = FALSE
+    equal <- combinedTranscripts$readClassType == "equal:compatible"
+    equal[is.na(equal)] <- FALSE
     if(sum(equal, na.rm = TRUE)<50 | sum(!equal, na.rm = TRUE)<50 | useTxScore){
-          combinedTranscripts$NDR = 1 - combinedTranscripts$maxTxScore
+          combinedTranscripts$NDR <- 1 - combinedTranscripts$maxTxScore
           if(!useTxScore) message("WARNING - Less than 50 TRUE or FALSE read classes ",
             "for NDR precision stabilization.")
           message("NDR will be approximated as: (1 - Transcript Model Prediction Score)")
-    } else combinedTranscripts$NDR = calculateNDR(combinedTranscripts$maxTxScore, equal)
-    combinedTranscripts$NDR[combinedTranscripts$maxTxScore==-1] = 1
+    } else {
+        combinedTranscripts$NDR <- calculateNDR(combinedTranscripts$maxTxScore, equal)
+    }
+    combinedTranscripts$NDR[combinedTranscripts$maxTxScore==-1] <- 1
     return(combinedTranscripts)
 }
 
 #' calculates the minimum NDR for each score 
 #' @noRd
-calculateNDR = function(score, labels){
-    scoreOrder = order(score, decreasing = TRUE) 
-    labels = labels[scoreOrder]
-    NDR = cumsum(!labels)/(seq_len(length(labels))) #calculate NDR
-    NDR = rev(cummin(rev(NDR))) #flatten NDR so its never higher than a lower ranked RC
+calculateNDR <- function(score, labels){
+    scoreOrder <- order(score, decreasing = TRUE) 
+    labels <- labels[scoreOrder]
+    NDR <- cumsum(!labels)/(seq_len(length(labels))) #calculate NDR
+    NDR <- rev(cummin(rev(NDR))) #flatten NDR so its never higher than a lower ranked RC
     return(NDR[order(scoreOrder)]) #return to original order
 }
 
@@ -245,8 +245,9 @@ calculateNDR = function(score, labels){
 #' @noRd
 makeExonsIntronsSpliced <- function(transcriptsTibble,annotationSeqLevels){
   if(all(is.na(transcriptsTibble$intronStarts))){
-      intronsByReadClass = GRangesList()}
-  else {    intronsByReadClass <- makeGRangesListFromFeatureFragments(
+      intronsByReadClass <- GRangesList()
+  } else {    
+      intronsByReadClass <- makeGRangesListFromFeatureFragments(
         seqnames = transcriptsTibble$chr,
         fragmentStarts = transcriptsTibble$intronStarts,
         fragmentEnds = transcriptsTibble$intronEnds,
@@ -686,7 +687,7 @@ combindRowDataWithRanges <- function(rowDataCombinedFiltered, exonRangesCombined
 #' @noRd
 combineWithAnnotations <- function(rowDataCombinedFiltered, 
                                         extendedAnnotationRanges,annotationGrangesList, prefix){
-    equalRanges = rowDataCombinedFiltered[!(rowDataCombinedFiltered$novelTranscript),]
+    equalRanges <- rowDataCombinedFiltered[!(rowDataCombinedFiltered$novelTranscript),]
     #remove extended ranges that are already present in annotation
     extendedAnnotationRanges <- extendedAnnotationRanges[rowDataCombinedFiltered$novelTranscript]
     annotationRangesToMerge <- annotationGrangesList
@@ -700,12 +701,12 @@ combineWithAnnotations <- function(rowDataCombinedFiltered,
         mcols(annotationRangesToMerge)$maxTxScore.noFit <- NA
         mcols(extendedAnnotationRanges) <- mcols(extendedAnnotationRanges)[,colnames(mcols(extendedAnnotationRanges))]
         #copy over stats to annotations from read classes
-        mcols(annotationRangesToMerge[equalRanges$TXNAME])$NDR = equalRanges$NDR
-        mcols(annotationRangesToMerge[equalRanges$TXNAME])$maxTxScore = equalRanges$maxTxScore
-        mcols(annotationRangesToMerge[equalRanges$TXNAME])$readCount = equalRanges$readCount
-        mcols(annotationRangesToMerge[equalRanges$TXNAME])$relReadCount = equalRanges$relReadCount
-        mcols(annotationRangesToMerge[equalRanges$TXNAME])$maxTxScore = equalRanges$maxTxScore
-        mcols(annotationRangesToMerge[equalRanges$TXNAME])$maxTxScore.noFit = equalRanges$maxTxScore.noFit
+        mcols(annotationRangesToMerge[equalRanges$TXNAME])$NDR <- equalRanges$NDR
+        mcols(annotationRangesToMerge[equalRanges$TXNAME])$maxTxScore <- equalRanges$maxTxScore
+        mcols(annotationRangesToMerge[equalRanges$TXNAME])$readCount <- equalRanges$readCount
+        mcols(annotationRangesToMerge[equalRanges$TXNAME])$relReadCount <- equalRanges$relReadCount
+        mcols(annotationRangesToMerge[equalRanges$TXNAME])$maxTxScore <- equalRanges$maxTxScore
+        mcols(annotationRangesToMerge[equalRanges$TXNAME])$maxTxScore.noFit <- equalRanges$maxTxScore.noFit
         #mcols(annotationRangesToMerge[equalRanges$TXNAME])$relSubsetCount = equalRanges$relSubsetCount
     }
     if (length(extendedAnnotationRanges)) {
@@ -717,7 +718,7 @@ combineWithAnnotations <- function(rowDataCombinedFiltered,
     }else{
       extendedAnnotationRanges <- annotationRangesToMerge
       mcols(extendedAnnotationRanges)$txid <- seq_along(extendedAnnotationRanges)
-      mcols(extendedAnnotationRanges)$relReadCount = NA
+      mcols(extendedAnnotationRanges)$relReadCount <- NA
       #mcols(extendedAnnotationRanges)$relSubsetCount = NA
     }
   return(extendedAnnotationRanges)
@@ -725,8 +726,8 @@ combineWithAnnotations <- function(rowDataCombinedFiltered,
 
 #' calculate relative subset read count after filtering (increase speed, subsets are not considered here)'
 #' @noRd
-calculateRelSubsetCount = function(extendedAnnotationRanges, minEq, min.readFractionByEqClass){
-  filter = !is.na(mcols(extendedAnnotationRanges)$readCount)
+calculateRelSubsetCount <- function(extendedAnnotationRanges, minEq, min.readFractionByEqClass){
+  filter <- !is.na(mcols(extendedAnnotationRanges)$readCount)
   mcols(extendedAnnotationRanges)$relSubsetCount <- NA
   mcols(extendedAnnotationRanges)$relSubsetCount[filter] <- 
     mcols(extendedAnnotationRanges)$readCount[filter]/
@@ -834,7 +835,7 @@ addGeneIdsToReadClassTable <- function(readClassTable, distTable,
 #' @details 
 #' @return extendedAnnotations with a new NDR threshold
 #' @export
-setNDR = function(extendedAnnotations, NDR = NULL, includeRef = FALSE, prefix = 'Bambu', baselineFDR = 0.1, defaultModels2 = defaultModels){
+setNDR <- function(extendedAnnotations, NDR = NULL, includeRef = FALSE, prefix = 'Bambu', baselineFDR = 0.1, defaultModels2 = defaultModels){
     #Check to see if the annotations/gtf are dervived from Bambu
     if(is.null(mcols(extendedAnnotations)$NDR)){
         warning("Annotations were not extended by Bambu (or the wrong prefix was provided). NDR can not be set")
@@ -846,76 +847,79 @@ setNDR = function(extendedAnnotations, NDR = NULL, includeRef = FALSE, prefix =
 
     #recommend an NDR (needed when users read in Bambu GTF)
     if(is.null(NDR)){
-        tempAnno = c(extendedAnnotations, metadata(extendedAnnotations)$lowConfidenceTranscripts)
-        NDR = recommendNDR.onAnnotations(tempAnno, prefix = prefix, baselineFDR = baselineFDR, defaultModels2 = defaultModels2)
+        tempAnno <- c(extendedAnnotations, metadata(extendedAnnotations)$lowConfidenceTranscripts)
+        NDR <- recommendNDR.onAnnotations(tempAnno, prefix = prefix, baselineFDR = baselineFDR, defaultModels2 = defaultModels2)
         message("Recommending a novel discovery rate (NDR) of: ", NDR)
     }
 
     #If reference annotations should be filtered too (note that reference annotations with no read support arn't filtered)
     if(includeRef){
-        toRemove = (!is.na(mcols(extendedAnnotations)$NDR) & mcols(extendedAnnotations)$NDR > NDR)
-        toAdd = !is.na(mcols(metadata(extendedAnnotations)$lowConfidenceTranscripts)$NDR) & 
+        toRemove <- (!is.na(mcols(extendedAnnotations)$NDR) & mcols(extendedAnnotations)$NDR > NDR)
+        toAdd <- !is.na(mcols(metadata(extendedAnnotations)$lowConfidenceTranscripts)$NDR) & 
             mcols(metadata(extendedAnnotations)$lowConfidenceTranscripts)$NDR <= NDR  
     } else {
-        toRemove = (mcols(extendedAnnotations)$NDR > NDR & 
+        toRemove <- (mcols(extendedAnnotations)$NDR > NDR & 
             grepl(prefix, mcols(extendedAnnotations)$TXNAME))
-        toAdd = (mcols(metadata(extendedAnnotations)$lowConfidenceTranscripts)$NDR <= NDR & 
+        toAdd <- (mcols(metadata(extendedAnnotations)$lowConfidenceTranscripts)$NDR <= NDR & 
             grepl(prefix, mcols(metadata(extendedAnnotations)$lowConfidenceTranscripts)$TXNAME))     
     }
   
-  temp = c(metadata(extendedAnnotations)$lowConfidenceTranscripts[!toAdd], extendedAnnotations[toRemove])
-  extendedAnnotations = c(extendedAnnotations[!toRemove], metadata(extendedAnnotations)$lowConfidenceTranscripts[toAdd])
-  metadata(extendedAnnotations)$lowConfidenceTranscripts = temp
+  temp <- c(metadata(extendedAnnotations)$lowConfidenceTranscripts[!toAdd], extendedAnnotations[toRemove])
+  extendedAnnotations <- c(extendedAnnotations[!toRemove], metadata(extendedAnnotations)$lowConfidenceTranscripts[toAdd])
+  metadata(extendedAnnotations)$lowConfidenceTranscripts <- temp
 
   mcols(extendedAnnotations)$txid <- seq_along(extendedAnnotations)
   minEqClasses <- getMinimumEqClassByTx(extendedAnnotations)
   mcols(extendedAnnotations)$eqClassById <- minEqClasses$eqClassById
   
-  metadata(extendedAnnotations)$NDRthreshold = NDR
+  metadata(extendedAnnotations)$NDRthreshold <- NDR
 
   return(extendedAnnotations)
 }
 
+
+#' Extend annotations by clusters (work in progress?)
+#' @noRd
 isore.extendAnnotations.clusters <- function(readClassList, annotations, clusters, NDR, isoreParameters, stranded, bpParameters, fusionMode, verbose = FALSE){
     message("--- Start extending annotations for clusters ---")
     #if clustering is a csv, create a list with the barcodes for each cluster
     #csv must have two cols with heading barcode, cluster
     if(!is.list(clusters)){
-        clusters = read.csv(clusters)
-        clusters = clusters %>% group_by(cluster) %>% summarise(barcodes = list(barcode))
-        clusters = clusters$cluster
-        clusters = clusters$barcodes
-        names(clusters) = clusters
+        clusters <- read.csv(clusters)
+        clusters <- clusters %>% group_by(cluster) %>% summarise(barcodes = list(barcode))
+        clusters <- clusters$cluster
+        clusters <- clusters$barcodes
+        names(clusters) <- clusters
     }
-    annotations.clusters = list()
-    rcfs.clusters = list()
-    clusters.rc = splitReadClassFilesByRC(readClassList[[1]])
-    txScores = c()
+    annotations.clusters <- list()
+    rcfs.clusters <- list()
+    clusters.rc <- splitReadClassFilesByRC(readClassList[[1]])
+    txScores <- c()
     for(i in seq_along(clusters)){
         print(names(clusters)[i])
         ###TODO need to account for the sample name here which is added to the barcode
-        index = match(clusters[[i]],gsub('demultiplexed','',metadata(readClassList[[1]])$samples)) 
-        index = index[!is.na(index)]
+        index <- match(clusters[[i]],gsub('demultiplexed','',metadata(readClassList[[1]])$samples)) 
+        index <- index[!is.na(index)]
         print(length(index))
         if(length(index)<20) next
-        rcf.counts = clusters.rc[,index]
-        rcf.filt = readClassList[[1]][rowSums(rcf.counts)>0,]
-        rowData(rcf.filt)$readCount = rowSums(rcf.counts)[rowSums(rcf.counts)>0]
-        countsTBL = calculateGeneProportion(counts=mcols(rcf.filt)$readCount,
+        rcf.counts <- clusters.rc[,index]
+        rcf.filt <- readClassList[[1]][rowSums(rcf.counts)>0,]
+        rowData(rcf.filt)$readCount <- rowSums(rcf.counts)[rowSums(rcf.counts)>0]
+        countsTBL <- calculateGeneProportion(counts=mcols(rcf.filt)$readCount,
                                             geneIds=mcols(rcf.filt)$GENEID)
-        rowData(rcf.filt)$geneReadProp = countsTBL$geneReadProp
-        rowData(rcf.filt)$geneReadCount = countsTBL$geneReadCount
-        rowData(rcf.filt)$startSD = 0
-        rowData(rcf.filt)$endSD = 0
-        rowData(rcf.filt)$readCount.posStrand = 0
-        thresholdIndex = which(rowData(rcf.filt)$readCount>=isoreParameters$min.readCount)
-        model = trainBambu(rcf.filt, verbose = verbose, min.readCount = isoreParameters$min.readCount)
-        txScore = getTranscriptScore(rowData(rcf.filt)[thresholdIndex,], model,
+        rowData(rcf.filt)$geneReadProp <- countsTBL$geneReadProp
+        rowData(rcf.filt)$geneReadCount <- countsTBL$geneReadCount
+        rowData(rcf.filt)$startSD <- 0
+        rowData(rcf.filt)$endSD <- 0
+        rowData(rcf.filt)$readCount.posStrand <- 0
+        thresholdIndex <- which(rowData(rcf.filt)$readCount>=isoreParameters$min.readCount)
+        model <- trainBambu(rcf.filt, verbose = verbose, min.readCount = isoreParameters$min.readCount)
+        txScore <- getTranscriptScore(rowData(rcf.filt)[thresholdIndex,], model,
                                 defaultModels)
-        rowData(rcf.filt)$txScore = rep(NA,nrow(rcf.filt))
-        rowData(rcf.filt)$txScore[thresholdIndex] = txScore
+        rowData(rcf.filt)$txScore <- rep(NA,nrow(rcf.filt))
+        rowData(rcf.filt)$txScore[thresholdIndex] <- txScore
         #txScores = cbind(txScores, rowData(rcf.filt)$txScore)
-        rcfs.clusters[[names(clusters)[i]]] = rcf.filt
+        rcfs.clusters[[names(clusters)[i]]] <- rcf.filt
         annotations.clusters[[names(clusters)[i]]] <- bambu.extendAnnotations(list(rcf.filt), annotations, NDR,
                                 isoreParameters, stranded, bpParameters, fusionMode, verbose)
     }

From 3d645e112ce1208e2c145959998144329096584b Mon Sep 17 00:00:00 2001
From: Chen Ying 
Date: Thu, 23 Jan 2025 11:03:35 +0800
Subject: [PATCH 182/189] fix bug when clusters is provided as CharacterList
 produced as recommended in readme

---
 R/bambu.R | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/R/bambu.R b/R/bambu.R
index 536354c3..bc68727b 100644
--- a/R/bambu.R
+++ b/R/bambu.R
@@ -268,7 +268,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL,
             #load in the barcode clustering from file if provided
             iter <- seq_len(ncol(metadata(quantData_i)$countMatrix)) # iter is integer
             if(!is.null(clusters)){
-                if(!is.list(clusters)){
+                if(class(clusters)!="CompressedCharacterList"){ # !is.list(clusters) is FALSE for CompressedCharacterList 
                     clusterMaps <- NULL
                     for(j in seq_along(metadata(quantData_i)$sampleNames)){ #load in a file per sample name provided
                         clusterMap <- fread(clusters[[j]], header = FALSE, 
@@ -289,7 +289,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL,
                     if(length(quantData)>1){
                         iter <- clusters[[i]] #lowMemory mode
                     }else{
-                        iter <- do.call(c,clusters)
+                        iter <- clusters#do.call(c,clusters)
                     }
                 }
             }

From f25f2d3c94446cf32f18a28dca85b10155010805 Mon Sep 17 00:00:00 2001
From: Chen Ying 
Date: Thu, 23 Jan 2025 11:06:21 +0800
Subject: [PATCH 183/189] fix bug for reading in spatial files

---
 R/bambu_utilityFunctions.R | 17 +++++++++++++----
 1 file changed, 13 insertions(+), 4 deletions(-)

diff --git a/R/bambu_utilityFunctions.R b/R/bambu_utilityFunctions.R
index 03f92434..bc148c71 100644
--- a/R/bambu_utilityFunctions.R
+++ b/R/bambu_utilityFunctions.R
@@ -304,8 +304,14 @@ generateColData <- function(sampleNames, clusters, demultiplexed, spatial){
         ColData$x_coordinate <- NA
         ColData$y_coordinate <- NA
         if(length(spatial)==1){
-            bc_coords <- DataFrame(read.table(gzfile(spatial),
-                col.names = c("Barcode", "x_coordinate", "y_coordinate")))
+            # the following line takes a regular delimited file as input
+            # it can either has header or without header
+            # it can also be compressed 
+            bc_coords <- fread(spatial, 
+                col.names = c("Barcode", "x_coordinate", "y_coordinate"),
+                data.table = FALSE)
+                # DataFrame(read.table(gzfile(spatial),
+                # col.names = c("Barcode", "x_coordinate", "y_coordinate")))
             bcMatch <- match(ColData$Barcode, bc_coords$Barcode)
             ColData$x_coordinate <- bc_coords$x_coordinate[bcMatch]
             ColData$y_coordinate <- bc_coords$y_coordinate[bcMatch]
@@ -313,8 +319,11 @@ generateColData <- function(sampleNames, clusters, demultiplexed, spatial){
             spatial.unique <- unique(spatial)
             for(whitelist in spatial.unique){
                 i <- which(spatial.unique==whitelist)
-                bc_coords <- DataFrame(read.table(gzfile(whitelist), 
-                    col.names = c("Barcode", "x_coordinate", "y_coordinate")))
+                bc_coords <- fread(whitelist, 
+                                   col.names = c("Barcode", "x_coordinate", "y_coordinate"),
+                                   data.table = FALSE)
+                    # DataFrame(read.table(gzfile(whitelist), 
+                    # col.names = c("Barcode", "x_coordinate", "y_coordinate")))
                 bcSampleIndex <- ColData$sampleName %in% sampleNames[i]
                 bcMatch <- match(ColData$Barcode[bcSampleIndex], bc_coords$Barcode)
                 ColData$x_coordinate[bcSampleIndex] <- bc_coords$x_coordinate[bcMatch]

From 55a445ba94ac89200a8eb5510199289cbb8438d7 Mon Sep 17 00:00:00 2001
From: Chen Ying 
Date: Thu, 23 Jan 2025 11:08:04 +0800
Subject: [PATCH 184/189] fix the problem of not using unspliced SEs in default
 settings when min.txScore.singleExon == 1

---
 R/bambu-extendAnnotations-utilityCombine.R | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/R/bambu-extendAnnotations-utilityCombine.R b/R/bambu-extendAnnotations-utilityCombine.R
index 2836c2eb..4a644451 100644
--- a/R/bambu-extendAnnotations-utilityCombine.R
+++ b/R/bambu-extendAnnotations-utilityCombine.R
@@ -19,9 +19,9 @@ isore.combineTranscriptCandidates <- function(readClassList,
         min.readCount, min.readFractionByGene, 
         min.txScore.multiExon, min.txScore.singleExon, verbose) %>% data.table()
     combinedSplicedTranscripts[,confidenceType := "highConfidenceJunctionReads"]
-    # when single exon min score is 1, skip unspliced transcripts combination 
-    # by right, estimated txScore will not reach 1 
-    if (min.txScore.singleExon == 1) 
+    # when single exon min score is greater than 1, skip unspliced transcripts combination
+    # this is a very customized config, useful when data is very big 
+    if (min.txScore.singleExon > 1) 
         return(combinedSplicedTranscripts)
     combinedUnsplicedTranscripts <- 
         combineUnsplicedTranscriptModels(readClassList, bpParameters, 

From b56390588b45ed3f13393cc0590ef6aa77e80fa7 Mon Sep 17 00:00:00 2001
From: Chen Ying 
Date: Thu, 23 Jan 2025 11:08:36 +0800
Subject: [PATCH 185/189] update function documentation

---
 R/bambu-extendAnnotations-utilityExtend.R | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/R/bambu-extendAnnotations-utilityExtend.R b/R/bambu-extendAnnotations-utilityExtend.R
index 8d20ba7c..d65d70ea 100644
--- a/R/bambu-extendAnnotations-utilityExtend.R
+++ b/R/bambu-extendAnnotations-utilityExtend.R
@@ -878,7 +878,7 @@ setNDR <- function(extendedAnnotations, NDR = NULL, includeRef = FALSE, prefix =
 }
 
 
-#' Extend annotations by clusters (work in progress?)
+#' Extend annotations by clusters
 #' @noRd
 isore.extendAnnotations.clusters <- function(readClassList, annotations, clusters, NDR, isoreParameters, stranded, bpParameters, fusionMode, verbose = FALSE){
     message("--- Start extending annotations for clusters ---")

From b3fed7cbd9caaf5819a1f5513609483eb8400fea Mon Sep 17 00:00:00 2001
From: Chen Ying 
Date: Thu, 23 Jan 2025 11:22:15 +0800
Subject: [PATCH 186/189] update example code for clustercells with bug fix and
 update advanced option paper link

---
 README.md | 44 ++++++++++++++++++++++----------------------
 1 file changed, 22 insertions(+), 22 deletions(-)

diff --git a/README.md b/README.md
index 6e710ec6..5f9f81b7 100755
--- a/README.md
+++ b/README.md
@@ -292,7 +292,7 @@ There is a single-cell and spatial pipeline starting from fastq or demultiplexed
 For advanced users see the #[Custom single-cell and spatial analysis](#Custom-Single-Cell-and-Spatial) section under advanced options
 
 ### *Bambu* Advanced Options
-Below we include several advanced options and use-cases for *bambu*. We recommend reading and understanding the [paper](https://www.biorxiv.org/content/10.1101/2022.11.14.516358v1) before attempting to use these features.
+Below we include several advanced options and use-cases for *bambu*. We recommend reading and understanding the [paper](https://doi.org/10.1038/s41592-023-01908-w) before attempting to use these features.
 
 ### Using a pretrained model
 
@@ -410,12 +410,12 @@ In situations where training is not or cannot be performed, and the default mode
 
 ```rscript
 # first train the model using a related annotated dataset from .bam
-se = bambu(reads = sample1.bam, annotations = annotations, genome = fa.file, discovery = FALSE, quant = FALSE, opt.discovery = list(returnModel = TRUE)) # note that discovery and quant need to be set to FALSE, alternatively you can have them set to TRUE and retrieve the model from the rcFile as long as returnModel = TRUE ([see here](#Storing-and-using-preprocessed-files-rcFiles)).
+se <- bambu(reads = sample1.bam, annotations = annotations, genome = fa.file, discovery = FALSE, quant = FALSE, opt.discovery = list(returnModel = TRUE)) # note that discovery and quant need to be set to FALSE, alternatively you can have them set to TRUE and retrieve the model from the rcFile as long as returnModel = TRUE ([see here](#Storing-and-using-preprocessed-files-rcFiles)).
 newDefaultModel = metadata(se[[1]])$model # [[1]] will select the model trained on the first sample
 
 # alternatively train the model using an rcFile
 rcFile <- readRDS(pathToRcFile)
-newDefaultModel = trainBambu(rcFile)
+newDefaultModel <- trainBambu(rcFile)
 
 # use the trained model on another sample
 # sample2.bam and fa.file2 represent the aligned reads and genome for the poorly annotated sample
@@ -493,7 +493,7 @@ Optional:
 **barcodesToFilter**: A string vector indicating barcodes to be filtered out.  
     
 
 ```rscript
-readClassFile = bambu(reads = samples, annotations = annotations, genome = fa.file, ncore = 1, discovery = FALSE, quant = FALSE, demultiplexed = barcode_maps, verbose = TRUE, assignDist = FALSE, lowMemory = as.logical("$params.lowMemory"), yieldSize = 10000000, sampleNames = ids, cleanReads = as.logical($cleanReads), dedupUMI = as.logical($deduplicateUMIs))
+readClassFile <- bambu(reads = samples, annotations = annotations, genome = fa.file, ncore = 1, discovery = FALSE, quant = FALSE, demultiplexed = barcode_maps, verbose = TRUE, assignDist = FALSE, lowMemory = as.logical("$params.lowMemory"), yieldSize = 10000000, sampleNames = ids, cleanReads = as.logical($cleanReads), dedupUMI = as.logical($deduplicateUMIs))
 ```
 
 #### Transcript Discovery:
@@ -501,17 +501,17 @@ readClassFile = bambu(reads = samples, annotations = annotations, genome = fa.fi
 Transript discovery can be run as usual as typically bulk-level discovery is suitable. However cluster-level transcript discovery can be preformed using the clusters argument which can be redone done after clustering. 
 
 ```rscript
-extendedAnno = bambu(reads = readClassFile, annotations = annotations, genome = fa.file, ncore = 1, discovery = TRUE, quant = FALSE, demultiplexed = TRUE, verbose = FALSE, assignDist = FALSE)
+extendedAnno <- bambu(reads = readClassFile, annotations = annotations, genome = fa.file, ncore = 1, discovery = TRUE, quant = FALSE, demultiplexed = TRUE, verbose = FALSE, assignDist = FALSE)
 ```
 
 #### Read Class Assignment:
 
 This step was previously performed together with the quantification, but can be done seperately so that the arguments can be passed to the quantification seperately with different clustering. If you only want barcode level gene counts or unique transcript counts you can stop here and do not need to proceed to the EM quantification.
 
-**spatial**: This should be a path to your barcode whitelist that also contians the x and y coordinates as extra columns. 
+**spatial**: This should be a path to your barcode whitelist that also contains the x and y coordinates as extra columns. If provided, the file should contain 3 columns with or without header, where the first column is the barcode, and the second and third column contains the x and y coordinates information accordingly. Compressed file format is accepted as well.
 
 ```rscript
-quantData = bambu(reads = readClassFile, annotations = extendedAnno, genome = fa.file, ncore = 1, discovery = FALSE, quant = FALSE, demultiplexed = TRUE, verbose = FALSE, opt.em = list(degradationBias = FALSE), assignDist = TRUE, spatial = spatial)
+quantData <- bambu(reads = readClassFile, annotations = extendedAnno, genome = fa.file, ncore = 1, discovery = FALSE, quant = FALSE, demultiplexed = TRUE, verbose = FALSE, opt.em = list(degradationBias = FALSE), assignDist = TRUE, spatial = spatial)
 ```
 
 #### EM quantification:
@@ -522,7 +522,7 @@ If you plan to run this step with multiple processes we recommend restarting you
 
 **quantData**:  This is the summerized experiement output from the Read Class Assignment step
    
 
-**clusters**:  This is an optional argument which is either a path to a csv containing the barcode to cluster assignments or a list
    
+**clusters**:  This is an optional argument which is either a path to a csv containing the barcode to cluster assignments or a CharacterList which can be produced using the code below.
    
 
 **opt.em = list(degradationBias=FALSE)**: We recommend including this argument if you are doing barcode level EM quantification to greatly improve runtime with only a small reduction in quantification accuracy. 
 
@@ -530,19 +530,19 @@ If you plan to run this step with multiple processes we recommend restarting you
 #use Seurat to generate clusters from gene counts
 library(Seurat)
 
-clusterCells = function(counts, resolution = 0.8, dim = 15){
+clusterCells <- function(counts, resolution = 0.8, dim = 15){
   
   cellMix <- CreateSeuratObject(counts = counts, 
                                 project = "cellMix", min.cells = 1)#, min.features = 200)
   #cellMix <- subset(cellMix, subset = nFeature_RNA > nFeature_RNA_threshold & nFeature_RNA < nFeature_RNA_threshold_max)
-  #nFeature_RNA_threshold = 1000, nFeature_RNA_threshold_max = 9000,
+  #nFeature_RNA_threshold <- 1000, nFeature_RNA_threshold_max = 9000,
   cellMix <- NormalizeData(cellMix, normalization.method = "LogNormalize", scale.factor = 10000)
   cellMix <- FindVariableFeatures(cellMix, selection.method = "vst", nfeatures = 2500)
   all.genes <- rownames(cellMix)
   cellMix <- ScaleData(cellMix, features = all.genes)
-  npcs = ifelse(ncol(counts)>50, 50, ncol(counts)-1)
+  npcs <- ifelse(ncol(counts)>50, 50, ncol(counts)-1)
   cellMix <- RunPCA(cellMix, features = VariableFeatures(object = cellMix), npcs = npcs)
-  dim = ifelse(dim >= dim(cellMix@reductions$pca)[2], dim, dim(cellMix@reductions$pca)[2])
+  dim <- ifelse(dim >= dim(cellMix@reductions$pca)[2], dim(cellMix@reductions$pca)[2],dim) # if data dimension is small, otherwise, cap dimension at 15
   cellMix <- FindNeighbors(cellMix, dims = 1:dim)
   cellMix <- FindClusters(cellMix, resolution = resolution)
   cellMix <- RunUMAP(cellMix, dims = 1:dim)
@@ -550,16 +550,16 @@ clusterCells = function(counts, resolution = 0.8, dim = 15){
   return(cellMix)
 }
 
-quantData.gene = transcriptToGeneExpression(quantData)
-counts = assays(quantData.gene)$counts[,1] #selecting first sample
-cellMix = clusterCells(counts, resolution = resolution) #resolution is dependant on sample. For larger clusters: 0.2-0.6, for higher resolution: 0.8-2
-x = setNames(names(cellMix@active.ident), cellMix@active.ident)
-clusters = splitAsList(unname(x), names(x))
+quantData.gene <- transcriptToGeneExpression(quantData)
+counts <- assays(quantData.gene)$counts #selecting first sample
+cellMix <- clusterCells(counts) #resolution can be customized. For larger clusters: 0.2-0.6, for higher resolution: 0.8-2
+x <- setNames(names(cellMix@active.ident), cellMix@active.ident)
+clusters_temp <- splitAsList(unname(x), paste)("cluster",names(x)))#make clusters names start with cluster, for better comprehension
 
 
 
-se = bambu( reads = "placeholder", 
-            annotations = extendedAnno, 
+se <- bambu( reads = NULL, 
+            annotations = rowRanges(quantDatas), 
             genome = "$genome", 
             quantData = quantDatas, 
             assignDist = FALSE, 
@@ -569,7 +569,7 @@ se = bambu( reads = "placeholder",
             demultiplexed = TRUE, 
             verbose = FALSE, 
             opt.em = list(degradationBias = FALSE), 
-            clusters = clusters)
+            clusters = clusters_temp)
 ```
 
 ### *Bambu* Arguments
@@ -593,7 +593,7 @@ se = bambu( reads = "placeholder",
 | verbose | A logical variable indicating whether processing messages will be printed. |
 | mode | A string that will set other input arguments ['bulk', 'multiplexed', 'fusion', 'debug']
     bulk - 
        processByBam = TRUE
        processByChromsome = FALSE
    multiplexed - 
        demultiplex = TRUE
        cleanReads = TRUE
        opt.em = list(degradationBias = FALSE)
        quant = FALSE
        processByChromosome = TRUE
    fusion - 
        NDR = 1
        fusionMode = TRUE
    debug -
        verbose = TRUE
        trackReads = TRUE
        returnDistTable = TRUE |
 | demultiplexed | A logical variable indicating whether the input bam file is demultiplexed. The barcode and umi either need to be present in the read name or the $BC and $UG tags, defaults to FALSE. Alternatively a path to a csv file can be provided where column 1 is read names, column 2 is barcodes, and column 3 is UMI. |
-| spatial | A path to the barcode whitelist containing X and Y coordinates, defaults to null. |
+| spatial | A path to the barcode whitelist containing X and Y coordinates, defaults to null. If provided, the file should contain 3 columns with or without header, where the first column is the barcode, and the second and third column contains the x and y coordinates information accordingly. Compressed file format is accepted as well.|
 | assignDist | A logical variable indicating whether read class to transcript assignment will be performed, defaults to TRUE. |
 | quantData | Advanced use only. A list of se outputs from the assignDist step. Used only to run quantification |
 | sampleNames | A vector of strings representing the sample name associated with each input bam. bam files with the same sample name will be combined |
@@ -624,7 +624,7 @@ rowRanges(se)
 |column|description|
 |---|---|
 |seqnames|The scaffold name the transcript is found on|
-|ranges|An iRanges object containing the start and end coordinates of the transcript (not stranded)|
+|ranges|An IRanges object containing the start and end coordinates of the transcript (not stranded)|
 |strand|The strand of the transcript (+, -, *)|
 |exon_rank|The exon index of the exons in the transcript starting from the 5’ end of the transcript|
 |exon_endRank|The exon index of the exons in the transcript starting from the 3’ end of the transcript|

From 596897ab1763916d368a95bb1478a9520b832be4 Mon Sep 17 00:00:00 2001
From: lingminhao 
Date: Sun, 26 Jan 2025 10:02:04 +0800
Subject: [PATCH 187/189] rename unused argument

---
 R/prepareDataFromBam.R | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/R/prepareDataFromBam.R b/R/prepareDataFromBam.R
index 98bfb778..8ce5a921 100755
--- a/R/prepareDataFromBam.R
+++ b/R/prepareDataFromBam.R
@@ -71,8 +71,8 @@ prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE,
         if(cleanReads){
             softClip5Prime <- clipFunction(cigarData = GenomicAlignments::cigar(alignmentInfo), grep_pattern = '^(\\d*)[S].*', replace_pattern = '\\1')
             softClip3Prime <- clipFunction(cigarData = GenomicAlignments::cigar(alignmentInfo), grep_pattern = '.*\\D(\\d*)[S]$', replace_pattern = '\\1')
-            hardClip5Prime <- clipFunction(alignData = GenomicAlignments::cigar(alignmentInfo), grep_pattern = '^(\\d*)[H].*', replace_pattern = '\\1')
-            hardClip3Prime <- clipFunction(alignData = GenomicAlignments::cigar(alignmentInfo), grep_pattern = '.*\\D(\\d*)[H]$', replace_pattern = '\\1')
+            hardClip5Prime <- clipFunction(cigarData = GenomicAlignments::cigar(alignmentInfo), grep_pattern = '^(\\d*)[H].*', replace_pattern = '\\1')
+            hardClip3Prime <- clipFunction(cigarData = GenomicAlignments::cigar(alignmentInfo), grep_pattern = '.*\\D(\\d*)[H]$', replace_pattern = '\\1')
             # softClip5Prime <-suppressWarnings(pmax(0,as.numeric(gsub('^(\\d*)[S].*','\\1',GenomicAlignments::cigar(alignmentInfo))), na.rm=T))
             # softClip3Prime <-suppressWarnings(pmax(0,as.numeric(gsub('.*\\D(\\d*)[S]$','\\1',GenomicAlignments::cigar(alignmentInfo))), na.rm=T))
             # hardClip5Prime <-suppressWarnings(pmax(0,as.numeric(gsub('^(\\d*)[H].*','\\1',GenomicAlignments::cigar(alignmentInfo))), na.rm=T))
@@ -154,4 +154,4 @@ prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE,
 clipFunction <- function(cigarData, grep_pattern, replace_pattern){
     return(suppressWarnings(pmax(0,as.numeric(gsub(grep_pattern,replace_pattern,
                                                    cigarData)), na.rm=T)))
-}
\ No newline at end of file
+}

From 01562224ca58156b3cd43dc5d99975a3d95be39a Mon Sep 17 00:00:00 2001
From: lingminhao 
Date: Wed, 29 Jan 2025 02:29:40 +0800
Subject: [PATCH 188/189] improve flexibility for BC&UMI parsing

---
 R/prepareDataFromBam.R | 20 +++++++++-----------
 1 file changed, 9 insertions(+), 11 deletions(-)

diff --git a/R/prepareDataFromBam.R b/R/prepareDataFromBam.R
index 8ce5a921..f9f8b414 100755
--- a/R/prepareDataFromBam.R
+++ b/R/prepareDataFromBam.R
@@ -45,19 +45,17 @@ prepareDataFromBam <- function(bamFile, yieldSize = NULL, verbose = FALSE,
         readGrgList[[counter]] <-grglist(alignmentInfo)
         if (!isFALSE(demultiplexed)){ # if demultiplexed is TRUE or a string path 
             if(isTRUE(demultiplexed)){ # if demultiplexed is TRUE
-                mcols(readGrgList[[counter]])$BC <- ifelse(!is.na(mcols(alignmentInfo)$BC), 
-                                                           mcols(alignmentInfo)$BC, 
-                                                           ifelse(grepl("[GACT]_",names(readGrgList[[counter]])), # a checkpoint to see whether BC is contained in the name, with specific format BC_UMI#READNAME
-                                                        gsub("(^[GACT]+(?=_)).*", '\\1', 
-                                                        names(readGrgList[[counter]]), perl = TRUE),
-                                                        NA))
-                mcols(readGrgList[[counter]])$UMI <- ifelse(!is.na(mcols(alignmentInfo)$UG), mcols(alignmentInfo)$UG, 
-                                                            ifelse(grepl("[GACT]#",names(readGrgList[[counter]])), # a checkpoint to see whether UMI is contained in the name, with specific format BC_UMI#READNAME
-                                                        gsub(".*((?<=_)[GACT]*(?=#)).*", '\\1', names(readGrgList[[counter]]), perl = TRUE),
-                                                        NA))
+      
+                mcols(readGrgList[[counter]])$BC <- case_when(grepl("^[^_]+_[^#]+#", names(readGrgList[[counter]]), perl = TRUE) ~ sub("_.*", "", names(readGrgList[[counter]])), # a checkpoint to see whether BC is contained in the name, with specific format BC_UMI#READNAME, 
+                                                              !is.na(mcols(alignmentInfo)$BC) ~ mcols(alignmentInfo)$BC, 
+                                                              TRUE ~ NA) 
+
+                mcols(readGrgList[[counter]])$UMI <- case_when(grepl("^[^_]+_[^#]+#", names(readGrgList[[counter]]), perl = TRUE) ~ sub("^[^_]+_([^#]+)#.*$", "\\1", names(readGrgList[[counter]])), # a checkpoint to see whether UMI is contained in the name, with specific format BC_UMI#READNAME, 
+                                                               !is.na(mcols(alignmentInfo)$UG) ~ mcols(alignmentInfo)$UG, 
+                                                               TRUE ~ NA) 
             } else{ # if demultiplexed is a string path
                 mcols(readGrgList[[counter]])$BC <- NA
-                mcols(readGrgList[[counter]])$UMI <- "NA"
+                mcols(readGrgList[[counter]])$UMI <- NA
                 mcols(readGrgList[[counter]])$BC <- readMap[,2][match(names(readGrgList[[counter]]),readMap[,1])]
                 if(ncol(readMap)>2){
                     mcols(readGrgList[[counter]])$UMI <- readMap[,3][match(names(readGrgList[[counter]]),readMap[,1])]

From b122513e4ce1c15c51d594bbc19b0a906edea87c Mon Sep 17 00:00:00 2001
From: lingminhao 
Date: Wed, 5 Feb 2025 17:03:26 +0800
Subject: [PATCH 189/189] fix bug about CompressedCharacterList

---
 R/bambu.R | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/R/bambu.R b/R/bambu.R
index bc68727b..a42ae236 100644
--- a/R/bambu.R
+++ b/R/bambu.R
@@ -268,7 +268,7 @@ bambu <- function(reads, annotations = NULL, genome = NULL, NDR = NULL,
             #load in the barcode clustering from file if provided
             iter <- seq_len(ncol(metadata(quantData_i)$countMatrix)) # iter is integer
             if(!is.null(clusters)){
-                if(class(clusters)!="CompressedCharacterList"){ # !is.list(clusters) is FALSE for CompressedCharacterList 
+                if(class(clusters[[i]])!="CompressedCharacterList"){ # !is.list(clusters) is FALSE for CompressedCharacterList 
                     clusterMaps <- NULL
                     for(j in seq_along(metadata(quantData_i)$sampleNames)){ #load in a file per sample name provided
                         clusterMap <- fread(clusters[[j]], header = FALSE, 

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