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MARGI_heatmap.r
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library(data.table)
library(GenomicRanges)
library(GenomicAlignments)
library(circlize)
library(ComplexHeatmap)
library(AnnotationDbi)
library(karyoploteR)
library(chicane)
library(GenomicInteractions)
library(Gviz)
library(plyr)
library(GenomicFeatures)
##################################################################################################
make_complex_heatmap_margi <- function(
chrSize_file="/dataOS/rcalandrelli/phase_separation/4DNFI823LSII.hg38.mainonly.chrom.sizes",
sample="test", # sample name
contact_matrix_file, # contact matrix
sparse=T, # T if the contact matrix is sparse, F if dense
chr_row, # chr on the rows (RNA end)
chr_col, # chr on the columns (DNA end)
bin_size, # bin size or resolution
select_coord=NA, # to select a portion of the matrix input c(start_row_coord, end_row_coord, start_col_coord, end_col_coord)
contacts_cutoffs=c(0,NA), # minimum and maximum contact value cutoffs. Leave NA to do not have any max cutoff
log_contacts=F, # to plot the log of the contacts
my_colorbar=c("white","red"), # colorbar colors
Gr_row_annotation=NA, # Granges object for annotation track on the rows
Gr_col_annotation=NA, # Granges object for annotation track on the columns
annotation_type="", # set to "genes" to select only protein coding genesß
Gr_stripes_row=NA, # set True to add horizontal stripes over the heatmap corresponding to the row annotations
Gr_stripes_col=NA, # set True to add vertical stripes over the heatmap corresponding to the column annotations
compartments_file_path=NA,
tads_file_path=NA,
loops_file_path=NA,
EP_loops_file=NA,
feature_color = "#dbdeff",
color_tads=T, # set color of the features on the heatmap
normalized=F,
norm_raw_ratio=F,
RNA_domain_coord = NA
){
options(scipen=999)
########## Load genome data
chrSize = read.table(chrSize_file)
Gr_genome <- GRanges(
seqnames = Rle(as.character(chrSize$V1)),
ranges = IRanges(rep(1,nrow(chrSize)), end = as.numeric(chrSize$V2), names = c(1:nrow(chrSize))),
strand = Rle(strand('*')))
seqlengths(Gr_genome) <- as.numeric(chrSize$V2)
########## Tile genome and make genomic windows for selected chromosomes
genome_window <- tileGenome(seqinfo(Gr_genome), tilewidth = bin_size, cut.last.tile.in.chrom = T)
chr_row_genome_window = genome_window[seqnames(genome_window)==chr_row]
chr_col_genome_window = genome_window[seqnames(genome_window)==chr_col]
########## Load contact matrix
if (sparse == T){
temp = data.frame(fread(contact_matrix_file))
contact_matrix = matrix(0, nrow = length(chr_row_genome_window), ncol = length(chr_col_genome_window))
contact_matrix[as.matrix(temp[,c("RNA_end_bins","DNA_end_bins")])] = temp$x
} else {
contact_matrix = data.frame(fread(contact_matrix_file))
contact_matrix = contact_matrix[,-1]
}
rownames(contact_matrix) = seq(1,nrow(contact_matrix)) # ???
# Normalize contact matrix by colSums. Each entry is divided by the sum of RNAs attached to that DNA locus.
if (normalized == T){
contact_matrix = sweep(contact_matrix, 2, colSums(contact_matrix), FUN = '/') * 100
contact_matrix[which(is.na(contact_matrix), arr.ind = T)] = 0
}
if (norm_raw_ratio == T){
contact_matrix_norm = sweep(contact_matrix, 2, colSums(contact_matrix), FUN = '/')
contact_matrix_norm[which(is.na(contact_matrix_norm), arr.ind = T)] = 0
contact_matrix_norm_scale = (contact_matrix_norm - min(contact_matrix_norm)) / (max(contact_matrix_norm)-min(contact_matrix_norm))
contact_matrix_scale = (contact_matrix - min(contact_matrix)) / (max(contact_matrix)-min(contact_matrix))
contact_matrix_ratio = contact_matrix_norm_scale / contact_matrix_scale
contact_matrix_ratio[which(is.na(contact_matrix_ratio), arr.ind = T)] = 0
contact_matrix_ratio = log2(contact_matrix_ratio)
contact_matrix_ratio[which(is.infinite(contact_matrix_ratio), arr.ind = T)] = 0
contact_matrix = contact_matrix_ratio
}
########## Load compartment file if declared
if (!is.na(compartments_file_path)){
compartment = read.table(compartments_file_path, header = T)
compartment = compartment[which(compartment$chr == chr_col),]
compartment = cbind(compartment,compartment[,3])
compartment[,4][which(compartment[,4]<0)] = "#0cad01"
compartment[,4][which(compartment[,4]>=0)] = "#E41A1C"
colnames(compartment)[4] = "color"
compartment_ha = HeatmapAnnotation(eigen = anno_barplot(compartment$eigen,
bar_width = 1,
height = unit(1, "cm"),
gp = gpar(fill = compartment$color)),
which = "column")
}
########## Load TAD file if declared
if (!is.na(tads_file_path)){
# tads_file = read.table(paste0(tads_file_path,"/TADs_",chr_row,"/50000_blocks.bedpe"))[,c(1:3)]
# Gr_tads = GRanges(
# seqnames = Rle(paste0("chr",tads_file$V1)),
# ranges = IRanges(as.numeric(tads_file$V2), end = as.numeric(tads_file$V3), names = c(1:nrow(tads_file))),
# strand = Rle(strand('*')))
# Gr_tads = Gr_tads[seqnames(Gr_tads) == chr_row]
tads_file = read.table(tads_file_path, header = T)
Gr_tads = GRanges(
seqnames = Rle(tads_file$seqnames),
ranges = IRanges(as.numeric(tads_file$start), end = as.numeric(tads_file$end), names = c(1:nrow(tads_file))),
strand = Rle(strand('*')),
label = as.character(tads_file$label))
Gr_tads = Gr_tads[seqnames(Gr_tads) == chr_row]
overlaps = findOverlaps(Gr_tads, chr_row_genome_window)
start_tad_bin = c()
end_tad_bin = c()
for (i in 1:length(Gr_tads)){
temp_tad = subjectHits(overlaps[which(queryHits(overlaps)==i),])
start_tad_bin = c(start_tad_bin,temp_tad[1])
end_tad_bin = c(end_tad_bin,temp_tad[length(temp_tad)])
}
# df_tad_bin = data.frame(start_tad_bin, end_tad_bin)
# for (i in 1:nrow(df_tad_bin)){
# start_tad = df_tad_bin[i,1]
# end_tad = df_tad_bin[i,2]
# contact_matrix[start_tad:end_tad,start_tad] = -2
# contact_matrix[start_tad:end_tad,end_tad] = -2
# contact_matrix[start_tad,start_tad:end_tad] = -2
# contact_matrix[end_tad,start_tad:end_tad] = -2
# }
label_bin = mcols(Gr_tads)[,"label"]
df_tad_bin = data.frame(start_tad_bin, end_tad_bin, label_bin)
for (i in 1:nrow(df_tad_bin)){
# In this way start boundary overlaps the square border, while the end boundary is included within the square. This makes the visualization good
# reducing the square overlaps
start_tad = df_tad_bin[i,1]
end_tad = df_tad_bin[i,2]
if (color_tads == T){
if (df_tad_bin[i,3] == "enrichment"){
contact_matrix[start_tad:end_tad,start_tad] = -3
contact_matrix[start_tad:end_tad,end_tad] = -3
contact_matrix[start_tad,start_tad:end_tad] = -3
contact_matrix[end_tad,start_tad:end_tad] = -3
}
else if (df_tad_bin[i,3] == "depletion"){
contact_matrix[start_tad:end_tad,start_tad] = -2
contact_matrix[start_tad:end_tad,end_tad] = -2
contact_matrix[start_tad,start_tad:end_tad] = -2
contact_matrix[end_tad,start_tad:end_tad] = -2
} else {
contact_matrix[start_tad:end_tad,start_tad] = -6
contact_matrix[start_tad:end_tad,end_tad] = -6
contact_matrix[start_tad,start_tad:end_tad] = -6
contact_matrix[end_tad,start_tad:end_tad] = -6
}
} else {
if (df_tad_bin[i,3] == "enrichment"){
contact_matrix[start_tad:end_tad,start_tad] = -6
contact_matrix[start_tad:end_tad,end_tad] = -6
contact_matrix[start_tad,start_tad:end_tad] = -6
contact_matrix[end_tad,start_tad:end_tad] = -6
}
else if (df_tad_bin[i,3] == "depletion"){
contact_matrix[start_tad:end_tad,start_tad] = -6
contact_matrix[start_tad:end_tad,end_tad] = -6
contact_matrix[start_tad,start_tad:end_tad] = -6
contact_matrix[end_tad,start_tad:end_tad] = -6
} else {
contact_matrix[start_tad:end_tad,start_tad] = -6
contact_matrix[start_tad:end_tad,end_tad] = -6
contact_matrix[start_tad,start_tad:end_tad] = -6
contact_matrix[end_tad,start_tad:end_tad] = -6
}
}
}
}
########## Load loop file if declared
if (!is.na(loops_file_path)){
loops_file = read.table(paste0(loops_file_path,"/merged_loops.bedpe"))[,c(1:6)]
Gr_loops_RNA = GRanges(
seqnames = Rle(paste0("chr",loops_file$V1)),
ranges = IRanges(as.numeric(loops_file$V2), end = as.numeric(loops_file$V3), names = c(1:nrow(loops_file))),
strand = Rle(strand('*')))
Gr_loops_RNA = Gr_loops_RNA[seqnames(Gr_loops_RNA) == chr_row]
Gr_loops_DNA = GRanges(
seqnames = Rle(paste0("chr",loops_file$V4)),
ranges = IRanges(as.numeric(loops_file$V5), end = as.numeric(loops_file$V6), names = c(1:nrow(loops_file))),
strand = Rle(strand('*')))
Gr_loops_DNA = Gr_loops_DNA[seqnames(Gr_loops_DNA) == chr_row]
overlaps_RNA = findOverlaps(Gr_loops_RNA, chr_row_genome_window)
overlaps_DNA = findOverlaps(Gr_loops_DNA, chr_col_genome_window)
start_loop_bin_row = c()
end_loop_bin_row = c()
for (i in 1:length(Gr_loops_RNA)){
temp_loop = subjectHits(overlaps_RNA[which(queryHits(overlaps_RNA)==i),])
start_loop_bin_row = c(start_loop_bin_row, temp_loop[1])
end_loop_bin_row = c(end_loop_bin_row, temp_loop[length(temp_loop)])
}
start_loop_bin_col = c()
end_loop_bin_col = c()
for (i in 1:length(Gr_loops_DNA)){
temp_loop = subjectHits(overlaps_DNA[which(queryHits(overlaps_DNA)==i),])
start_loop_bin_col = c(start_loop_bin_col, temp_loop[1])
end_loop_bin_col = c(end_loop_bin_col, temp_loop[length(temp_loop)])
}
df_loop_bin = data.frame(start_loop_bin_row, end_loop_bin_row, start_loop_bin_col, end_loop_bin_col)
for (i in 1:nrow(df_loop_bin)){
# In this way the dot is exactly over the loop
start_loop_row = df_loop_bin[i,1]
end_loop_row = ifelse(df_loop_bin[i,2] > df_loop_bin[i,1], df_loop_bin[i,2] - 1, df_loop_bin[i,2])
start_loop_col = df_loop_bin[i,3]
end_loop_col = ifelse(df_loop_bin[i,4] > df_loop_bin[i,3], df_loop_bin[i,4] - 1, df_loop_bin[i,4])
contact_matrix[start_loop_row:end_loop_row,start_loop_col] = -3
contact_matrix[start_loop_row:end_loop_row,end_loop_col] = -3
contact_matrix[start_loop_row,start_loop_col:end_loop_col] = -3
contact_matrix[end_loop_row,start_loop_col:end_loop_col] = -3
# Plot also loops under the diagonal
contact_matrix[start_loop_col:end_loop_col,start_loop_row] = -3
contact_matrix[start_loop_col:end_loop_col,end_loop_row] = -3
contact_matrix[start_loop_col,start_loop_row:end_loop_row] = -3
contact_matrix[end_loop_col,start_loop_row:end_loop_row] = -3
}
}
########## Load enhancer-promoter loop file if declared
if (!is.na(EP_loops_file)){
loops_file = read.table(EP_loops_file)[,c(1:6,25)]
loops_file = loops_file[which(!is.na(loops_file$V25)),]
Gr_loops_RNA = GRanges(
seqnames = Rle(paste0("chr",loops_file$V1)),
ranges = IRanges(as.numeric(loops_file$V2), end = as.numeric(loops_file$V3), names = c(1:nrow(loops_file))),
strand = Rle(strand('*')),
type=loops_file$V25)
Gr_loops_RNA = Gr_loops_RNA[seqnames(Gr_loops_RNA) == chr_row]
Gr_loops_DNA = GRanges(
seqnames = Rle(paste0("chr",loops_file$V4)),
ranges = IRanges(as.numeric(loops_file$V5), end = as.numeric(loops_file$V6), names = c(1:nrow(loops_file))),
strand = Rle(strand('*')),
type=loops_file$V25)
Gr_loops_DNA = Gr_loops_DNA[seqnames(Gr_loops_DNA) == chr_row]
overlaps_RNA = findOverlaps(Gr_loops_RNA, chr_row_genome_window)
overlaps_DNA = findOverlaps(Gr_loops_DNA, chr_col_genome_window)
start_loop_bin_row = c()
end_loop_bin_row = c()
for (i in 1:length(Gr_loops_RNA)){
temp_loop = subjectHits(overlaps_RNA[which(queryHits(overlaps_RNA)==i),])
start_loop_bin_row = c(start_loop_bin_row, temp_loop[1])
end_loop_bin_row = c(end_loop_bin_row, temp_loop[length(temp_loop)])
}
start_loop_bin_col = c()
end_loop_bin_col = c()
for (i in 1:length(Gr_loops_DNA)){
temp_loop = subjectHits(overlaps_DNA[which(queryHits(overlaps_DNA)==i),])
start_loop_bin_col = c(start_loop_bin_col, temp_loop[1])
end_loop_bin_col = c(end_loop_bin_col, temp_loop[length(temp_loop)])
}
df_loop_bin = data.frame(start_loop_bin_row, end_loop_bin_row, start_loop_bin_col, end_loop_bin_col, mcols(Gr_loops_RNA)["type"])
for (i in 1:nrow(df_loop_bin)){
start_loop_row = df_loop_bin[i,1]
end_loop_row = ifelse(df_loop_bin[i,2] > df_loop_bin[i,1], df_loop_bin[i,2] - 1, df_loop_bin[i,2])
start_loop_col = df_loop_bin[i,3]
end_loop_col = ifelse(df_loop_bin[i,4] > df_loop_bin[i,3], df_loop_bin[i,4] - 1, df_loop_bin[i,4])
value = ifelse(df_loop_bin[i,5] == "enhancer_promoter", -2,
ifelse(df_loop_bin[i,5] == "promoter_enhancer", -4, -5))
contact_matrix[start_loop_row:end_loop_row,start_loop_col] = value
contact_matrix[start_loop_row:end_loop_row,end_loop_col] = value
contact_matrix[start_loop_row,start_loop_col:end_loop_col] = value
contact_matrix[end_loop_row,start_loop_col:end_loop_col] = value
# Plot also loops under the diagonal
value = ifelse(df_loop_bin[i,5] == "enhancer_promoter", -4,
ifelse(df_loop_bin[i,5] == "promoter_enhancer", -2, -5))
contact_matrix[start_loop_col:end_loop_col,start_loop_row] = value
contact_matrix[start_loop_col:end_loop_col,end_loop_row] = value
contact_matrix[start_loop_col,start_loop_row:end_loop_row] = value
contact_matrix[end_loop_col,start_loop_row:end_loop_row] = value
}
}
if (length(nrow(RNA_domain_coord)) > 0){
RNA_domain_coord = RNA_domain_coord[which(RNA_domain_coord$V1 == chr_row),]
for (i in seq_len(nrow(RNA_domain_coord))){
RNA_domain_coord_bin = as.numeric(ceiling(RNA_domain_coord[i,c(2,3,5,6)]/bin_size))
contact_matrix[RNA_domain_coord_bin[1]:RNA_domain_coord_bin[2], RNA_domain_coord_bin[3]] = -3
contact_matrix[RNA_domain_coord_bin[1]:RNA_domain_coord_bin[2], RNA_domain_coord_bin[4]] = -3
contact_matrix[RNA_domain_coord_bin[1], RNA_domain_coord_bin[3]:RNA_domain_coord_bin[4]] = -3
contact_matrix[RNA_domain_coord_bin[2], RNA_domain_coord_bin[3]:RNA_domain_coord_bin[4]] = -3
}
} else if (sum(!is.na(RNA_domain_coord) & length(nrow(RNA_domain_coord)) == 0) == 4) {
RNA_domain_coord_bin = ceiling(RNA_domain_coord/bin_size)
contact_matrix[RNA_domain_coord_bin[1]:RNA_domain_coord_bin[2], RNA_domain_coord_bin[3]] = -3
contact_matrix[RNA_domain_coord_bin[1]:RNA_domain_coord_bin[2], RNA_domain_coord_bin[4]] = -3
contact_matrix[RNA_domain_coord_bin[1], RNA_domain_coord_bin[3]:RNA_domain_coord_bin[4]] = -3
contact_matrix[RNA_domain_coord_bin[2], RNA_domain_coord_bin[3]:RNA_domain_coord_bin[4]] = -3
}
########## Select part of the contact matrix
if (length(select_coord) == 4){
coord_bin = ceiling(select_coord/bin_size)
coord_bin[1] = coord_bin[1] + 1
coord_bin[3] = coord_bin[3] + 1
if (is.na(coord_bin[2])){
coord_bin[2] = ceiling(chrSize[which(chrSize$V1 == chr_row),2] / bin_size)
}
if (is.na(coord_bin[4])){
coord_bin[4] = ceiling(chrSize[which(chrSize$V1 == chr_col),2] / bin_size)
}
contact_matrix = apply(as.matrix(contact_matrix[coord_bin[1]:coord_bin[2],coord_bin[3]:coord_bin[4]]), 2, as.numeric)
rownames(contact_matrix) = seq(1,nrow(contact_matrix)) # ???
}
########## Check if making annotation tracks
if (!is.na(Gr_row_annotation[1])){
if (annotation_type == "genes"){
Gr_row_annotation = Gr_row_annotation[mcols(Gr_row_annotation)["GENEBIOTYPE"][,1] == "protein_coding"]
}
row_annotation_bin = unique(queryHits(findOverlaps(chr_row_genome_window,Gr_row_annotation)))
if (length(select_coord) == 4){
row_annotation_bin = row_annotation_bin[which(row_annotation_bin>=coord_bin[1] & row_annotation_bin<= coord_bin[2])] - coord_bin[1]
}
bar_annotation = rep(0,nrow(contact_matrix))
bar_annotation[row_annotation_bin] = 1
# same as rowAnnotation without the "which" parameter
row_ha = HeatmapAnnotation(SE = anno_barplot(x=bar_annotation,
bar_width = 1,
width = unit(0.5, "cm"),
axis = F),
which = "row")
}
if (!is.na(Gr_col_annotation[1])){
if (annotation_type == "genes"){
Gr_col_annotation = Gr_col_annotation[mcols(Gr_col_annotation)["GENEBIOTYPE"][,1] == "protein_coding"]
}
col_annotation_bin = unique(queryHits(findOverlaps(chr_col_genome_window,Gr_col_annotation)))
# Check and subset the annotation if only a part of the matrix was selected
if (length(select_coord) == 4){
col_annotation_bin = col_annotation_bin[which(col_annotation_bin>=coord_bin[3] & col_annotation_bin<= coord_bin[4])] - coord_bin[3]
}
bar_annotation = rep(0,nrow(contact_matrix))
bar_annotation[col_annotation_bin] = 1
# same as columnAnnotation without the "which" parameter
column_ha = HeatmapAnnotation(SE = anno_barplot(bar_annotation,
bar_width = 1,
height = unit(0.5, "cm"),
axis = F),
which = "column")
}
########## Check if making stripes
zero_indexes = as.matrix(which(contact_matrix==0, arr.ind = T))
if (!is.na(Gr_stripes_row[1])){
row_stripe_bin = unique(queryHits(findOverlaps(chr_row_genome_window,Gr_stripes_row)))
if (length(select_coord) == 4){
row_stripe_bin = row_stripe_bin[which(row_stripe_bin>=coord_bin[1] & row_stripe_bin<= coord_bin[2])] - coord_bin[1]
}
contact_matrix[zero_indexes[which(zero_indexes[,1] %in% row_stripe_bin),]] = -1
}
if (!is.na(Gr_stripes_col[1])){
col_stripe_bin = unique(queryHits(findOverlaps(chr_col_genome_window,Gr_stripes_col)))
if (length(select_coord) == 4){
col_stripe_bin = col_stripe_bin[which(col_stripe_bin>=coord_bin[1] & col_stripe_bin<= coord_bin[2])] - coord_bin[1]
}
contact_matrix[zero_indexes[which(zero_indexes[,2] %in% col_stripe_bin),]] = -1
}
#### Log contacts
if (log_contacts == T){
contact_matrix[which(contact_matrix>0, arr.ind = T)] = log(contact_matrix[which(contact_matrix>0, arr.ind = T)])
}
########## Set colorbar
if (norm_raw_ratio == F){
min_cutoff = as.numeric(contacts_cutoffs[1])
if (is.na(contacts_cutoffs[2])){
max_cutoff = max(contact_matrix)
} else if (contacts_cutoffs[2] < 1){
max_cutoff = round(as.numeric(quantile(contact_matrix[contact_matrix > 0], contacts_cutoffs[2])))
} else if (contacts_cutoffs[2] > 1){
max_cutoff = contacts_cutoffs[2]
}
### Custom part to plot Figure STRIPE B
# contact_matrix[23,13] = 8
# contact_matrix[13,23] = 0
#
# contact_matrix[39,10] = -2
# contact_matrix[10,39] = -2
#
# contact_matrix[37,12] = -4
# contact_matrix[12,37] = -4
#
# contact_matrix[38,25] = -5
# contact_matrix[25,38] = -5
col_fun1 = colorRamp2(c(min_cutoff, max_cutoff), my_colorbar)
col_fun = function(x) {
ifelse(x == -1, "#dbdeff",
ifelse(x == -2, "green", # depleted TADs / enhancer_promoter loops
ifelse(x == -3, "blue", # enriched TADs / loops in general
ifelse(x == -4, "#ff00ff", # promoter_enhancer loops
ifelse(x == -5, "#000000", # both promoter_enhancer and vice versa loops
ifelse(x == -6, "#b3b3b3", # neither tads
col_fun1(x)))))))
}
attr(col_fun, "breaks") = c(min_cutoff, max_cutoff)
} else {
col_fun = colorRamp2(c(min(contact_matrix), 0, max(contact_matrix)), c("blue","white","red"))
# col_fun = function(x) {
# col_fun1(x)
# }
#
# attr(col_fun, "breaks") = c(min(contact_matrix), 0, max(contact_matrix))
}
# Set axis labels
# coord_labels_padding_left = 1
# coord_labels_padding_right = 30
# coord_labels_rows = rep("",nrow(contact_matrix))
# coord_labels_columns = rep("",ncol(contact_matrix))
#
# coord_labels_rows[1] = ifelse(is.na(select_coord), 0, select_coord[1])
# coord_labels_rows[nrow(contact_matrix)] = ifelse(is.na(select_coord), end(chr_row_genome_window[length(chr_row_genome_window)]), select_coord[2])
# coord_labels_rows[round(nrow(contact_matrix)/2)] = paste0(chr_row,"\n(RNA)")
#
# coord_labels_columns[1] = ifelse(is.na(select_coord), 0, select_coord[3])
# coord_labels_columns[ncol(contact_matrix)] = ifelse(is.na(select_coord), end(chr_col_genome_window[length(chr_col_genome_window)]), select_coord[4])
# coord_labels_columns[round(ncol(contact_matrix)/2)] = paste0(chr_col,"\n(DNA)")
# Make figure main title
if(length(select_coord) != 1){
if (is.na(select_coord[2])){
select_coord[2] = chrSize[which(chrSize$V1 == chr_row),2]
}
if (is.na(select_coord[4])){
select_coord[4] = chrSize[which(chrSize$V1 == chr_col),2]
}
}
title_1 = paste0(sample, "\n")
title_2 = ifelse(length(select_coord) == 1,
paste0(chr_row,":0-",end(chr_row_genome_window[length(chr_row_genome_window)])),
paste0(chr_row,":",select_coord[1],"-",select_coord[2]))
if (chr_row != chr_col){
title_3 = ifelse(length(select_coord) == 1,
paste0("\n",chr_col,":0-",end(chr_col_genome_window[length(chr_col_genome_window)])),
paste0("\n",chr_col,":",select_coord[3],"-",select_coord[4]))
} else {
title_3 = ""
}
main_title = paste0(title_1, title_2, title_3)
coord_fontsize = 12
if (is.na(Gr_row_annotation[1]) & is.na(Gr_col_annotation[1])){
p<-Heatmap(contact_matrix,
cluster_rows = FALSE, cluster_columns = FALSE, border = T,
col = col_fun,
show_row_names = F,
show_column_names = F,
#right_annotation = row_ha,
#bottom_annotation = column_ha,
na_col = feature_color,
# row_labels = coord_labels_rows, row_names_gp = gpar(fontsize = coord_fontsize),
# column_labels = coord_labels_columns, column_names_gp = gpar(fontsize = coord_fontsize),
# row_names_side = "left",
# column_names_side = "top",
column_title = main_title,
heatmap_legend_param = list(title = ""))
# draw(p, heatmap_legend_list = list(Legend(at = c(-2, -1),
# labels = c("Enrich", "Deplet", "Neither"),
# legend_gp = gpar(fill = c("green", "blue", "yellow")))))
}
else if (!is.na(Gr_row_annotation[1]) & is.na(Gr_col_annotation[1])){
p<-Heatmap(contact_matrix,
cluster_rows = FALSE, cluster_columns = FALSE, border = T,
col = col_fun,
show_row_names = F,
show_column_names = F,
right_annotation = row_ha,
#bottom_annotation = column_ha,
na_col = feature_color,
row_names_side = "left",
column_names_side = "top",
# row_labels = coord_labels_rows, row_names_gp = gpar(fontsize = coord_fontsize),
# column_labels = coord_labels_columns, column_names_gp = gpar(fontsize = coord_fontsize),
column_title = main_title,
heatmap_legend_param = list(title = ""))
}
else if (is.na(Gr_row_annotation[1]) & !is.na(Gr_col_annotation[1])){
p<-Heatmap(contact_matrix,
cluster_rows = FALSE, cluster_columns = FALSE, border = T,
col = col_fun,
show_row_names = F,
show_column_names = F,
#right_annotation = row_ha,
bottom_annotation = column_ha,
na_col = feature_color,
row_names_side = "left",
column_names_side = "top",
# row_labels = coord_labels_rows, row_names_gp = gpar(fontsize = coord_fontsize),
# column_labels = coord_labels_columns, column_names_gp = gpar(fontsize = coord_fontsize),
column_title = main_title,
heatmap_legend_param = list(title = ""))
}
else if(!is.na(Gr_row_annotation[1]) & !is.na(Gr_col_annotation[1])){
p<-Heatmap(contact_matrix,
cluster_rows = FALSE, cluster_columns = FALSE, border = T,
col = col_fun,
show_row_names = F,
show_column_names = F,
right_annotation = row_ha,
bottom_annotation = column_ha,
na_col = feature_color,
row_names_side = "left",
column_names_side = "top",
# row_labels = coord_labels_rows, row_names_gp = gpar(fontsize = coord_fontsize),
# column_labels = coord_labels_columns, column_names_gp = gpar(fontsize = coord_fontsize),
column_title = main_title,
heatmap_legend_param = list(title = ""))
}
if (!is.na(compartments_file_path)){
p<-Heatmap(contact_matrix,
cluster_rows = FALSE, cluster_columns = FALSE, border = T,
col = col_fun,
show_row_names = F,
show_column_names = F,
#right_annotation = row_ha,
bottom_annotation = compartment_ha,
na_col = feature_color,
row_names_side = "left",
column_names_side = "top",
# row_labels = coord_labels_rows, row_names_gp = gpar(fontsize = coord_fontsize),
# column_labels = coord_labels_columns, column_names_gp = gpar(fontsize = coord_fontsize),
column_title = main_title,
heatmap_legend_param = list(title = ""))
}
return(p)
}
############ Test function
chrSize_file="/dataOS/rcalandrelli/phase_separation/4DNFI823LSII.hg38.mainonly.chrom.sizes"
sample="test"
contact_matrix_file="/dataOS/rcalandrelli/phase_separation/MARGI/contact_data/iMARGI_H1_control/500000_filter1k/chr11_chr11.txt"
sparse=T
chr_row="chr11"
chr_col="chr11"
bin_size=500000
select_coord=NA
contacts_cutoffs=c(0,NA)
my_colorbar=c("white","red")
Gr_row_annotation=NA
Gr_col_annotation=NA
Gr_stripes_row=NA
Gr_stripes_col=NA
compartments_file_path="/dataOS/rcalandrelli/phase_separation/HiC/compartments/H1_control_500000.txt"
tads_file_path = NA #"/dataOS/rcalandrelli/phase_separation/TADs/H1_control_merged/")
loops_file_path = NA #"/dataOS/rcalandrelli/phase_separation/loops/hiccups_H1_control_merged"
feature_color = "#dbdeff"
my_sample = "iMARGI_H1_control_1"
all_imargi_samples = list.dirs(path = "/dataOS/rcalandrelli/phase_separation/MARGI/data", full.names = F, recursive = F)
############ Compartments heatmap plots with the same colorbar scale as control (0, 800)
plot_list = list()
k = 1
for (my_sample in all_imargi_samples[1:4]){
temp = gsub("iMARGI_","",my_sample)
my_cutoffs = c(0,400)
p1 <- make_complex_heatmap_margi(
chrSize_file="/dataOS/rcalandrelli/phase_separation/4DNFI823LSII.hg38.mainonly.chrom.sizes",
sample=my_sample,
contact_matrix_file=paste0("/dataOS/rcalandrelli/phase_separation/MARGI/contact_data/",my_sample,"/500000_filter1k/chr1_chr1.txt"),
sparse=T,
chr_row="chr1",
chr_col="chr1",
bin_size=500000,
select_coord=NA,
contacts_cutoffs=my_cutoffs,
my_colorbar=c("white","red"),
Gr_row_annotation=NA,
Gr_col_annotation=NA,
Gr_stripes_row=NA,
Gr_stripes_col=NA,
compartments_file_path=paste0("/dataOS/rcalandrelli/phase_separation/HiC/compartments/",temp,"_500000.txt"),
tads_file_path = NA,
loops_file_path = NA,
feature_color = "blue")
plot_list[[k]] = p1
k = k + 1
}
plot_list_grob = lapply(plot_list, as.grob)
#png("/dataOS/rcalandrelli/phase_separation/MARGI/compartments/heatmaps/chr11_margi_compartment_heatmaps_800.png", width = 12, height = 12, units = "in", res = 200)
png("/dataOS/rcalandrelli/phase_separation/MARGI/compartments/heatmaps/chr1_margi_compartment_heatmaps_400.png", width = 12, height = 12, units = "in", res = 200)
plot_grid(plotlist = plot_list_grob, ncol = 2, labels = c("A", "B", "C", "D"))
dev.off()
############ Compartments heatmap plots
plot_list = list()
k = 1
for (my_sample in all_imargi_samples[1:4]){
temp = gsub("iMARGI_","",my_sample)
my_cutoffs = c(0,NA)
p1 <- make_complex_heatmap_margi(
chrSize_file="/dataOS/rcalandrelli/phase_separation/4DNFI823LSII.hg38.mainonly.chrom.sizes",
sample=my_sample,
contact_matrix_file=paste0("/dataOS/rcalandrelli/phase_separation/MARGI/contact_data/",my_sample,"/500000_filter1k/chr11_chr11.txt"),
sparse=T,
chr_row="chr11",
chr_col="chr11",
bin_size=500000,
select_coord=NA,
log_contacts = T,
contacts_cutoffs=my_cutoffs,
my_colorbar=c("white","red"),
Gr_row_annotation=NA,
Gr_col_annotation=NA,
Gr_stripes_row=NA,
Gr_stripes_col=NA,
compartments_file_path=paste0("/dataOS/rcalandrelli/phase_separation/HiC/compartments/",temp,"_500000.txt"),
tads_file_path = NA,
loops_file_path = NA,
feature_color = "blue")
plot_list[[k]] = p1
k = k + 1
}
plot_list_grob = lapply(plot_list, as.grob)
png("/dataOS/rcalandrelli/phase_separation/MARGI/compartments/heatmaps/chr11_margi_compartment_heatmaps_995.png", width = 12, height = 12, units = "in", res = 200)
png("/dataOS/rcalandrelli/phase_separation/MARGI/compartments/heatmaps/chr11_margi_compartment_heatmaps_99.png", width = 12, height = 12, units = "in", res = 200)
png("/dataOS/rcalandrelli/phase_separation/MARGI/compartments/heatmaps/chr11_margi_compartment_heatmaps_999.png", width = 12, height = 12, units = "in", res = 200)
png("/dataOS/rcalandrelli/phase_separation/MARGI/compartments/heatmaps/chr11_margi_compartment_heatmaps_log.png", width = 12, height = 12, units = "in", res = 200)
plot_grid(plotlist = plot_list_grob, ncol = 2, labels = c("A", "B", "C", "D"))
dev.off()
############ TADs heatmap plots
plot_list = list()
k = 1
for (my_sample in all_imargi_samples[1:4]){
my_cutoffs = c(0,0.995)
p1 <- make_complex_heatmap_margi(
chrSize_file="/dataOS/rcalandrelli/phase_separation/4DNFI823LSII.hg38.mainonly.chrom.sizes",
sample=my_sample,
contact_matrix_file=paste0("/dataOS/rcalandrelli/phase_separation/MARGI/contact_data/",my_sample,"/100000_filter1k/chr1_chr1.txt"),
sparse=T,
chr_row="chr1",
chr_col="chr1",
bin_size=100000,
select_coord=NA,
contacts_cutoffs=my_cutoffs,
my_colorbar=c("white","red"),
Gr_row_annotation=NA,
Gr_col_annotation=NA,
Gr_stripes_row=NA,
Gr_stripes_col=NA,
tads_file_path = NA,#"/dataOS/rcalandrelli/phase_separation/MARGI/tads/iMARGI_H1_control_1/10000_tads_enrich_label.txt",#"/dataOS/rcalandrelli/phase_separation/TADs/H1_control_merged",#/dataOS/rcalandrelli/phase_separation/MARGI/tads/tads_enrich_label.txt",
loops_file_path = NA,#"/dataOS/rcalandrelli/phase_separation/loops/hiccups_H1_control_merged",
feature_color = "blue")#dbdeff")
plot_list[[k]] = p1
k = k + 1
p2 <- make_complex_heatmap_margi(
chrSize_file="/dataOS/rcalandrelli/phase_separation/4DNFI823LSII.hg38.mainonly.chrom.sizes",
sample=my_sample,
contact_matrix_file=paste0("/dataOS/rcalandrelli/phase_separation/MARGI/contact_data/",my_sample,"/100000_filter1k/chr1_chr1.txt"),
sparse=T,
chr_row="chr1",
chr_col="chr1",
bin_size=100000,
select_coord=c(72000000,84000000,72000000,84000000),
contacts_cutoffs=my_cutoffs,
my_colorbar=c("white","red"),
Gr_row_annotation=NA,
Gr_col_annotation=NA,
Gr_stripes_row=NA,
Gr_stripes_col=NA,
tads_file_path = paste0("/dataOS/rcalandrelli/phase_separation/MARGI/tads/",my_sample,"/10000_tads_RNA_enrich_label.txt"),#"/dataOS/rcalandrelli/phase_separation/TADs/H1_control_merged",#/dataOS/rcalandrelli/phase_separation/MARGI/tads/tads_enrich_label.txt",
loops_file_path = NA,#"/dataOS/rcalandrelli/phase_separation/loops/hiccups_H1_control_merged",
feature_color = "blue")#dbdeff")
plot_list[[k]] = p2
k = k + 1
p3 <- make_complex_heatmap_margi(
chrSize_file="/dataOS/rcalandrelli/phase_separation/4DNFI823LSII.hg38.mainonly.chrom.sizes",
sample=my_sample,
contact_matrix_file=paste0("/dataOS/rcalandrelli/phase_separation/MARGI/contact_data/",my_sample,"/50000_filter1k/chr1_chr1.txt"),
sparse=T,
chr_row="chr1",
chr_col="chr1",
bin_size=50000,
select_coord=rep(c(153000000,161000000,),2),
contacts_cutoffs=my_cutoffs,
my_colorbar=c("white","red"),
Gr_row_annotation=NA,
Gr_col_annotation=NA,
Gr_stripes_row=NA,
Gr_stripes_col=NA,
tads_file_path = paste0("/dataOS/rcalandrelli/phase_separation/MARGI/tads/",my_sample,"/10000_tads_RNA_enrich_label.txt"),#"/dataOS/rcalandrelli/phase_separation/TADs/H1_control_merged",#/dataOS/rcalandrelli/phase_separation/MARGI/tads/tads_enrich_label.txt",
loops_file_path = NA,#"/dataOS/rcalandrelli/phase_separation/loops/hiccups_H1_control_merged",
feature_color = "blue")#dbdeff")
plot_list[[k]] = p3
k = k + 1
}
plot_list_grob = lapply(plot_list, as.grob)
#png("/dataOS/rcalandrelli/phase_separation/MARGI/tads/heatmaps/chr1_margi_tad_heatmaps_FULL.png", width = 12, height = 16, units = "in", res = 200)
png("/dataOS/rcalandrelli/phase_separation/MARGI/tads/heatmaps/chr1_margi_tad_heatmaps_995.png", width = 12, height = 16, units = "in", res = 200)
plot_grid(plotlist = plot_list_grob, ncol = 3, labels = c("A",rep("",2), "B",rep("",2), "C",rep("",2), "D",rep("",2)))
dev.off()
############ Loops heatmap plots
plot_list = list()
k = 1
for (my_sample in all_imargi_samples[1:4]){
temp = strsplit(my_sample,"_")[[1]][3]
loop_file_path_temp = paste0("/dataOS/rcalandrelli/phase_separation/HiC/loops/hiccups_H1_",temp,"_merged")
my_cutoffs = c(0,0.995)
my_chr = "chr1"
p1 <- make_complex_heatmap_margi(
chrSize_file="/dataOS/rcalandrelli/phase_separation/4DNFI823LSII.hg38.mainonly.chrom.sizes",
sample=my_sample,
contact_matrix_file=paste0("/dataOS/rcalandrelli/phase_separation/MARGI/contact_data/",my_sample,"/10000_filter1k/",my_chr,"_",my_chr,".txt"),
sparse=T,
chr_row=my_chr,
chr_col=my_chr,
bin_size=10000,
select_coord=rep(c(3000000,4000000),2),
contacts_cutoffs=my_cutoffs,
my_colorbar=c("white","red"),
Gr_row_annotation=NA,
Gr_col_annotation=NA,
Gr_stripes_row=NA,
Gr_stripes_col=NA,
tads_file_path = NA,
loops_file_path = loop_file_path_temp,
feature_color = "blue")
plot_list[[k]] = p1
k = k + 1
p2 <- make_complex_heatmap_margi(
chrSize_file="/dataOS/rcalandrelli/phase_separation/4DNFI823LSII.hg38.mainonly.chrom.sizes",
sample=my_sample,
contact_matrix_file=paste0("/dataOS/rcalandrelli/phase_separation/MARGI/contact_data/",my_sample,"/10000_filter1k/chr20_chr20.txt"),
sparse=T,
chr_row="chr20",
chr_col="chr20",
bin_size=10000,
select_coord=c(37000000,38000000,37000000,38000000),
contacts_cutoffs=my_cutoffs,
my_colorbar=c("white","red"),
Gr_row_annotation=NA,
Gr_col_annotation=NA,
Gr_stripes_row=NA,
Gr_stripes_col=NA,
tads_file_path = NA,
loops_file_path = loop_file_path_temp,
feature_color = "blue")
plot_list[[k]] = p2
k = k + 1
# p3 <- make_complex_heatmap_margi(
# chrSize_file="/dataOS/rcalandrelli/phase_separation/4DNFI823LSII.hg38.mainonly.chrom.sizes",
# sample=my_sample,
# contact_matrix_file=paste0("/dataOS/rcalandrelli/phase_separation/MARGI/contact_data/",my_sample,"/10000_filter1k/chr3_chr3.txt"),
# sparse=T,
# chr_row="chr3",
# chr_col="chr3",
# bin_size=10000,
# select_coord=c(47500000,48500000,47500000,48500000),
# contacts_cutoffs=my_cutoffs,
# my_colorbar=c("white","red"),
# Gr_row_annotation=NA,
# Gr_col_annotation=NA,
# Gr_stripes_row=NA,
# Gr_stripes_col=NA,
# tads_file_path = NA,
# loops_file_path = loop_file_path_temp,
# feature_color = "blue")
#
# plot_list[[k]] = p3
# k = k + 1
}
plot_list_grob = lapply(plot_list, as.grob)
#png("/dataOS/rcalandrelli/phase_separation/MARGI/loops/heatmaps/heatmaps_loops_FULL.png", width = 8, height = 16, units = "in", res = 200)
png("/dataOS/rcalandrelli/phase_separation/MARGI/loops/heatmaps/heatmaps_loops_995.png", width = 8, height = 16, units = "in", res = 200)
#plot_grid(plotlist = plot_list_grob, ncol = 3, labels = c("A","B","C","D","","","E","","","F","",""))
plot_grid(plotlist = plot_list_grob, ncol = 2, labels = c("A","B","C","","D","","E",""))
dev.off()
#### test to find the best looking example
temp_loops = loops_control_EP_ratio[which(loops_control_EP_ratio$density_ratio > 3.7 &
!is.na(loops_control_EP_ratio$density_ratio)),]
rownames(temp_loops) = c(1:nrow(temp_loops))
for (i in 235:nrow(temp_loops)){
print(i)
my_start_row = round_any(temp_loops[i,2], 1000000)
if (my_start_row > temp_loops[i,2]){
my_start_row = my_start_row - 1000000
}
my_end_row = my_start_row + 1000000
my_start_col = round_any(temp_loops[i,5], 1000000)
if (my_start_col > temp_loops[i,5]){
my_start_col = my_start_col - 1000000
}
my_end_col = my_start_col + 1000000
my_start = min(my_start_row, my_start_col)
my_end = max(my_end_row, my_end_col)
plot_list = list()
k = 1
for (my_sample in all_imargi_samples[1:4]){
temp = strsplit(my_sample,"_")[[1]][3]
loop_file_path_temp = paste0("/dataOS/rcalandrelli/phase_separation/HiC/loops/hiccups_H1_",temp,"_merged")
my_cutoffs = c(0,0.995)
my_chr = paste0("chr", temp_loops[i,1])
p1 <- make_complex_heatmap_margi(
chrSize_file="/dataOS/rcalandrelli/phase_separation/4DNFI823LSII.hg38.mainonly.chrom.sizes",
sample=my_sample,
contact_matrix_file=paste0("/dataOS/rcalandrelli/phase_separation/MARGI/contact_data/",my_sample,"/10000_filter1k/",my_chr,"_",my_chr,".txt"),
sparse=T,
chr_row=my_chr,
chr_col=my_chr,
bin_size=10000,
#select_coord=c(my_start, my_end, my_start, my_end),
select_coord=rep(c(46500000, 47500000),2),
contacts_cutoffs=my_cutoffs,
my_colorbar=c("white","red"),
Gr_row_annotation=NA,
Gr_col_annotation=NA,
Gr_stripes_row=NA,
Gr_stripes_col=NA,
tads_file_path = NA,
loops_file_path = loop_file_path_temp,
feature_color = "blue")
plot_list[[k]] = p1
k = k + 1
}
plot_list_grob = lapply(plot_list, as.grob)
a <- plot_grid(plotlist = plot_list_grob, ncol = 2)
png(paste0("/dataOS/rcalandrelli/phase_separation/MARGI/loops/iMARGI_H1_control/pattern_1_all_plots/", i, "_heatmaps_loops_995.png"), width = 8, height = 8, units = "in", res = 200)
print(a)
dev.off()
}
############ Loops heatmap plots to match Figure S-loop-examples
plot_list = list()
k = 1
for (my_sample in all_imargi_samples[1:4]){
temp = strsplit(my_sample,"_")[[1]][3]
loop_file_path_temp = paste0("/dataOS/rcalandrelli/phase_separation/HiC/loops/hiccups_H1_",temp,"_merged")
my_cutoffs = c(0,0.995)
p1 <- make_complex_heatmap_margi(
chrSize_file="/dataOS/rcalandrelli/phase_separation/4DNFI823LSII.hg38.mainonly.chrom.sizes",
sample=my_sample,
contact_matrix_file=paste0("/dataOS/rcalandrelli/phase_separation/MARGI/contact_data/",my_sample,"/10000_filter1k/chr12_chr12.txt"),
sparse=T,
chr_row="chr12",
chr_col="chr12",
bin_size=10000,
select_coord=c(52500000,54000000,52500000,54000000),
contacts_cutoffs=my_cutoffs,
my_colorbar=c("white","red"),
Gr_row_annotation=NA,
Gr_col_annotation=NA,
Gr_stripes_row=NA,
Gr_stripes_col=NA,
tads_file_path = NA,
loops_file_path = NA,
feature_color = "blue")
plot_list[[k]] = p1
k = k + 1
}
plot_list_grob = lapply(plot_list, as.grob)
png("/dataOS/rcalandrelli/phase_separation/MARGI/loops/heatmaps/heatmaps_margi_S-loop-examples1.png", width = 8, height = 8, units = "in", res = 200)
plot_grid(plotlist = plot_list_grob, ncol = 2, labels = c("A","B","C","D"))
dev.off()
############ Loops (with marker enhancer-promoter) heatmap plots
plot_list = list()