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mrdetect

Workflow for MRdetect, detection of Minimal Residual Disease from paired tumor-plasma sample

Overview

Dependencies

Usage

Cromwell

java -jar cromwell.jar run mrdetect.wdl --inputs inputs.json

Inputs

Required workflow parameters:

Parameter Value Description
tumorSampleName String ID for WGS tumor sample, must match .vcf header
tumorvcf File tumor vcf file, bgzip
tumorvcfindex File tumor vcf index file
reference String genome reference build. Only hg38 supported
instrument String sequencing instrument used (Illumina NovaSeq X Plus or Illumina NovaSeq 6000)

Optional workflow parameters:

Parameter Value Default Description
plasmabam File? None plasma input .bam file
plasmabai File? None plasma input .bai file
plasmaSampleName String? None name for plasma sample (from bam)
full_analysis_mode Boolean true Enable full analysis mode with this flag

Optional task parameters:

Parameter Value Default Description
filterVCF.tumorVCFfilter String "FILTER~'haplotype' FILTER~'clustered_events'
filterVCF.tumorVAF String "0.1" Variant Allele Frequency for tumor VCF
filterVCF.jobMemory Int 64 Memory allocated for this job (GB)
filterVCF.threads Int 4 Requested CPU threads
filterVCF.timeout Int 10 Hours before task timeout
parseControls.jobMemory Int 4 Memory for this task in GB
parseControls.timeout Int 12 Timeout in hours, needed to override imposed limits
detectControl.tumorSampleName String basename(tumorvcf,".vcf") name for tumour sample (from vcf)
detectControl.jobMemory Int 64 Memory allocated for this job (GB)
detectControl.threads Int 4 Requested CPU threads
detectControl.timeout Int 20 Hours before task timeout
detectControl.pickle String "$MRDETECT_ROOT/bin/MRDetectSNV/trained_SVM.pkl" trained pickle for detecting real tumor reads
detectControl.blocklist String "$PWGS_BLOCKLIST_ROOT/blocklist.vcf.gz" list of sites to exclude from analysis, gzipped
detectControl.pullreadsScript String "$MRDETECT_ROOT/bin/pull_reads" pull_reads.py executable
detectControl.qualityscoreScript String "$MRDETECT_ROOT/bin/quality_score" quality_score.py executable
detectControl.filterAndDetectScript String "$MRDETECT_ROOT/bin/filterAndDetect" filterAndDetect.py executable
detectSample.tumorSampleName String basename(tumorvcf,".vcf") name for tumour sample (from vcf)
detectSample.jobMemory Int 64 Memory allocated for this job (GB)
detectSample.threads Int 4 Requested CPU threads
detectSample.timeout Int 20 Hours before task timeout
detectSample.pickle String "$MRDETECT_ROOT/bin/MRDetectSNV/trained_SVM.pkl" trained pickle for detecting real tumor reads
detectSample.blocklist String "$PWGS_BLOCKLIST_ROOT/blocklist.vcf.gz" list of sites to exclude from analysis, gzipped
detectSample.pullreadsScript String "$MRDETECT_ROOT/bin/pull_reads" pull_reads.py executable
detectSample.qualityscoreScript String "$MRDETECT_ROOT/bin/quality_score" quality_score.py executable
detectSample.filterAndDetectScript String "$MRDETECT_ROOT/bin/filterAndDetect" filterAndDetect.py executable
snvDetectionSummary.pvalue String "0.00001" p-value for HBC error rate
snvDetectionSummary.jobMemory Int 20 Memory allocated for this job (GB)
snvDetectionSummary.threads Int 1 Requested CPU threads
snvDetectionSummary.timeout Int 2 Hours before task timeout
snvDetectionSummary.modules String "mrdetect/1.1.1" Required environment modules
snvDetectionSummary.pwgtestscript String "$MRDETECT_ROOT/bin/pwg_test" executable of pwg_test.R

Outputs

Output Type Description Labels
snvDetectionResult File? Result from SNV detection incl sample HBCs vidarr_label: snvDetectionResult
pWGS_svg File? pWGS svg vidarr_label: pWGS_svg
snpcount File number of SNPs in vcf after filtering vidarr_label: snpcount
snvDetectionVAF File? VAF from SNV detection for sample vidarr_label: snvDetectionVAF
final_call File? Final file of mrdetect results vidarr_label: final_call
filteredvcf File? Filtered vcf

Commands

This section lists commands run by the MRDetect workflow.

filterVCF

Performs vcf Filtering, followed by processing of individual MRDetect calls. Filters include removing difficult regions (optional), splitting multiallelic loci into one allele per line, removing indels, removing loci by quality metrics (set by tumorVCFfilter) and finally removing SNPs by VAF (set by tumorVAF).

 		set -euo pipefail
 
 		$BCFTOOLS_ROOT/bin/bcftools view -s ~{tumorSampleName} --regions-file ~{difficultRegions} ~{tumorvcf} |\
 		$BCFTOOLS_ROOT/bin/bcftools norm --multiallelics - --fasta-ref ~{genome} |\
 		$BCFTOOLS_ROOT/bin/bcftools filter -i "TYPE='snps'" |\
 		$BCFTOOLS_ROOT/bin/bcftools filter -e "~{tumorVCFfilter}" |\
 		$BCFTOOLS_ROOT/bin/bcftools filter -i "(FORMAT/AD[0:1])/(FORMAT/AD[0:0]+FORMAT/AD[0:1]) >= ~{tumorVAF}" > ~{tumorSampleName}.SNP.vcf
 
 		awk '$1 !~ "#" {print}' ~{tumorSampleName}.SNP.vcf | wc -l > ~{tumorSampleName}.SNP.count.txt

parseControls

This command processes the list of control files as paired bam/bai files and prints them out for detection.

detectSNVs

MRDetect proceed across three steps. This task is run through for the sample and for all the controls.

1- pull_reads takes any reads in the plasma .bam that corresponds to a SNP in the solid-tumour .vcf.

2- quality_score assesses the likelihood that any read is plasma based on the quality score and the trained pickle.

3- filterAndDetect keeps reads with high plasma likehood and removed those for which SNPs are in the blocklist.

 		set -euo pipefail
 
 		~{pullreadsScript} \
 			--bam ~{plasmabam} \
 			--vcf ~{tumorvcf} \
 			--out PLASMA_VS_TUMOR.tsv
 
 		~{qualityscoreScript} \
 			--pickle-name ~{pickle} \
 			--detections PLASMA_VS_TUMOR.tsv \
 			--output_file PLASMA_VS_TUMOR.svm.tsv
 
 		~{filterAndDetectScript} \
 			--vcfid ~{tumorSampleName} --bamid ~{plasmaSampleName} \
 			--svm PLASMA_VS_TUMOR.svm.tsv \
 			--vcf ~{tumorvcf} \
 			--output ./ \
 			--blocklist ~{blocklist} \
 			--troubleshoot

parseControls

 		python <<CODE
 		import os
 
 		with open(os.environ.get("~{controlFileList}")) as f:
 			for line in f:
 				line = line.rstrip()
 				tmp = line.split("\t")
 				r = tmp[0] + "\t" + tmp[1]
 				print(r)
 		f.close()
 		CODE

snvDetectionSummary

Finally, pwg_test.R will process the controls and the sample to make a final call.

 		set -euo pipefail
 
 		cat ~{sep=' ' controlCalls} | awk '$1 !~ "BAM" {print}' > HBCs.csv
 
 		cat ~{sampleCalls} HBCs.csv > ~{plasmaSampleName}.HBCs.csv
 
 		~{pwgtestscript} \
 			--sampleName ~{plasmaSampleName} \
 			--results ~{plasmaSampleName}.HBCs.csv \
 			--candidateSNVsCountFile ~{snpcount} \
 			--vafFile ~{vafFile} \
 			--pval ~{pvalue}

Support

For support, please file an issue on the Github project or send an email to gsi@oicr.on.ca .

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