Fix header issues when combining SV counts from multiple VCFs

inputs/values/dockers.json

@@ -33,4 +33,4 @@
   "sv_utils_docker": "us.gcr.io/broad-dsde-methods/gatk-sv/sv-utils:2023-02-01-v0.26.8-beta-9b25c72d",
   "gq_recalibrator_docker": "us.gcr.io/broad-dsde-methods/tbrookin/gatk:0a7e1d86f",
   "str": "us.gcr.io/broad-dsde-methods/vjalili/str:5994670"
-}
+}

src/sv-pipeline/scripts/downstream_analysis_and_filtering/sum_svcounts_perSample.R

@@ -4,29 +4,32 @@
 # in final_outlier_sample_filter.wdl
 
 
-###Set parameters & read arguments
+### Set parameters & read arguments
 options(stringsAsFactors=F, scipen=1000)
 args <- commandArgs(trailingOnly=TRUE)
 INFILE <- args[1]
 OUTFILE <- args[2]
 
-###Read input data & reformat
+### Read input data & reformat
 dat <- read.table(INFILE, header=F, check.names=F, sep="\t", comment.char="")
-if(dat[1, 1] %in% c("sample", "#sample")){
-  dat <- dat[-c(1), ]
+drop.rows <- which(dat[, 1] %in% c("sample", "#sample"))
+if(length(drop.rows) > 0){
+  dat <- dat[-drop.rows, ]
 }
 colnames(dat) <- c("sample", "svtype", "count", "chrom")[1:ncol(dat)]
+dat$count <- as.numeric(dat$count)
 samples <- as.character(unique(dat$sample))
 svtypes <- as.character(unique(dat$svtype))
 
-###Get sum of counts per sample per svtype
+### Get sum of counts per sample per svtype
 summed.res <- do.call("rbind", lapply(samples, function(sample){
-  return(do.call("rbind", lapply(svtypes, function(svtype){
-    return(data.frame("sample"=sample,
+  do.call("rbind", lapply(svtypes, function(svtype){
+    data.frame("sample"=sample,
                "svtype"=svtype,
-               "count"=sum(dat[which(dat$sample==sample & dat$svtype==svtype), ]$count,na.rm=T)))
-  })))
+               "count"=sum(dat[which(dat$sample==sample & dat$svtype==svtype), ]$count,
+                           na.rm=T))
+  }))
 }))
 
-###Write summed results to outfile
+### Write summed results to outfile
 write.table(summed.res, OUTFILE, col.names=T, row.names=F, sep="\t", quote=F)

wdl/FilterOutlierSamples.wdl

@@ -16,7 +16,8 @@ workflow FilterOutlierSamples {
     String? vcf_identifier  # required (enter algorithm here) if providing outlier_cutoff_table, otherwise used in some file prefixes
     String? bcftools_preprocessing_options
     Boolean plot_counts = false
-    Array[Pair[String, File]]? sample_subsets # if provided, will identify outliers separately within each subset. Expected format is array of pairs, where pair.left is the subset name and pair.right is a text file with all relevant sample IDs
+    Array[String]? sample_subset_prefixes # if provided, will identify outliers separately within each subset
+    Array[String]? sample_subset_lists # if provided, will identify outliers separately within each subset
     String sv_pipeline_docker
     String sv_base_mini_docker
     String linux_docker
@@ -28,9 +29,15 @@ workflow FilterOutlierSamples {
     RuntimeAttr? runtime_attr_filter_samples
     RuntimeAttr? runtime_attr_ids_from_vcf
     RuntimeAttr? runtime_attr_count_svs
+    RuntimeAttr? runtime_attr_combine_counts
     RuntimeAttr? runtime_attr_plot_svcounts
   }
 
+  if (defined(sample_subset_prefixes) && defined(sample_subset_lists)) {
+    Array[Pair[String, File]]? sample_subsets = zip(select_first([sample_subset_prefixes]), 
+                                                    select_first([sample_subset_lists]))
+  }
+
   call identify_outliers.IdentifyOutlierSamples {
     input:
       vcfs = vcfs,
@@ -51,6 +58,7 @@ workflow FilterOutlierSamples {
       runtime_attr_cat_outliers = runtime_attr_cat_outliers,
       runtime_attr_subset_counts = runtime_attr_subset_counts,
       runtime_attr_count_svs = runtime_attr_count_svs,
+      runtime_attr_combine_counts = runtime_attr_combine_counts,
       runtime_attr_plot_svcounts = runtime_attr_plot_svcounts
   }
 

wdl/IdentifyOutlierSamples.wdl

@@ -28,6 +28,7 @@ workflow IdentifyOutlierSamples {
     RuntimeAttr? runtime_attr_cat_outliers
     RuntimeAttr? runtime_attr_subset_counts
     RuntimeAttr? runtime_attr_count_svs
+    RuntimeAttr? runtime_attr_combine_counts
     RuntimeAttr? runtime_attr_plot_svcounts
   }
 
@@ -41,7 +42,7 @@ workflow IdentifyOutlierSamples {
         runtime_attr_override = runtime_attr_ids_from_vcf
     }
   }
-  Array[Pair[String, File]] subsets_to_eval = select_first([sample_subsets, [("ALL", select_first([GetSamplesList.out_file]))]])
+  Array[Pair[String, File]] subsets_to_eval = select_first([sample_subsets, [("ALL", select_all([GetSamplesList.out_file]))]])
 
   # Collect SV counts for each VCF in parallel unless sv_counts is provided
   if (!defined(sv_counts)) {
@@ -75,7 +76,8 @@ workflow IdentifyOutlierSamples {
       input:
         svcounts = CountPerVcf.sv_counts,
         prefix = prefix,
-        sv_pipeline_docker = sv_pipeline_docker
+        sv_pipeline_docker = sv_pipeline_docker,
+        runtime_attr_override = runtime_attr_combine_counts
     }
   }
   File final_counts = select_first([sv_counts, Combine.summed_svcounts])