bug-fix SpliceAI_delta_score removal (#136)

* bug-fix SpliceAI_delta_score getting added to necessary_columns_present if SpliceAI_pred is in vep_file

* changed way in which necessary_columns_present is obtained s.t. SpliceAI_delta_score is not omitted

* changed test data to reflect correct dtype for consequence columns

* changed link for deepripe in docs, since website seems to be down

---------

Co-authored-by: Marcel Mück <mueckm1@gmail.com>
Co-authored-by: Mück <m991k@b260-pc003.inet.dkfz-heidelberg.de>

deeprvat/annotations/annotations.py

@@ -1781,7 +1781,6 @@ def process_vep(
     necessary_columns = ["chrom", "pos", "ref", "alt", "Gene", "Consequence"] + list(
         types_mapping.keys()
     )
-    necessary_columns_present = [i for i in necessary_columns if i in vep_file.columns]
     if "SpliceAI_pred" in vep_file.columns:
         vep_file["SpliceAI_delta_score"] = vep_file["SpliceAI_pred"].apply(
             calculate_scores_max
@@ -1801,6 +1800,7 @@ def process_vep(
         vep_file[mask.columns] = mask
     else:
         raise ValueError("'Consequence' column expected to be in VEP output")
+    necessary_columns_present = [i for i in necessary_columns if i in vep_file.columns]
     vep_file = vep_file[list(set(necessary_columns_present + all_consequences))]
 
     types_present = dict(

docs/annotations.md

@@ -1,6 +1,6 @@
 # DeepRVAT annotation pipeline
 
-This pipeline is based on [snakemake](https://snakemake.readthedocs.io/en/stable/). It uses [bcftools + samstools](https://www.htslib.org/), as well as [perl](https://www.perl.org/), [deepRiPe](https://ohlerlab.mdc-berlin.de/software/DeepRiPe_140/) and [deepSEA](http://deepsea.princeton.edu/) as well as [VEP](http://www.ensembl.org/info/docs/tools/vep/index.html), including plugins for [primateAI](https://github.com/Illumina/PrimateAI) and  [spliceAI](https://github.com/Illumina/SpliceAI). DeepRiPe annotations were acquired using [faatpipe repository by HealthML](https://github.com/HealthML/faatpipe)[[1]](#reference-1-target) and DeepSea annotations were calculated using [kipoi-veff2](https://github.com/kipoi/kipoi-veff2)[[2]](#reference-2-target), abSplice scores were computed using [abSplice](https://github.com/gagneurlab/absplice/)[[3]](#reference-3-target). The pipeline was tested on linux and macOS.
+This pipeline is based on [snakemake](https://snakemake.readthedocs.io/en/stable/). It uses [bcftools + samstools](https://www.htslib.org/), as well as [perl](https://www.perl.org/), [deepRiPe](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7050519/) and [deepSEA](http://deepsea.princeton.edu/) as well as [VEP](http://www.ensembl.org/info/docs/tools/vep/index.html), including plugins for [primateAI](https://github.com/Illumina/PrimateAI) and  [spliceAI](https://github.com/Illumina/SpliceAI). DeepRiPe annotations were acquired using [faatpipe repository by HealthML](https://github.com/HealthML/faatpipe)[[1]](#reference-1-target) and DeepSea annotations were calculated using [kipoi-veff2](https://github.com/kipoi/kipoi-veff2)[[2]](#reference-2-target), abSplice scores were computed using [abSplice](https://github.com/gagneurlab/absplice/)[[3]](#reference-3-target). The pipeline was tested on linux and macOS.
 
 ![dag](_static/annotations_rulegraph.svg)