363 lines
14 KiB
Plaintext
Executable File
363 lines
14 KiB
Plaintext
Executable File
import org.broadinstitute.sting.datasources.pipeline.Pipeline
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import org.broadinstitute.sting.gatk.DownsampleType
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import org.broadinstitute.sting.gatk.walkers.genotyper.GenotypeCalculationModel.Model
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import org.broadinstitute.sting.queue.extensions.gatk._
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import org.broadinstitute.sting.queue.extensions.picard.PicardBamJarFunction
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import org.broadinstitute.sting.queue.extensions.samtools._
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import org.broadinstitute.sting.queue.{QException, QScript}
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import collection.JavaConversions._
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import org.broadinstitute.sting.utils.yaml.YamlUtils
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class fullCallingPipeline extends QScript {
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qscript =>
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@Argument(doc="contigIntervals", shortName="contigIntervals")
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var contigIntervals: File = _
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@Argument(doc="numContigs", shortName="numContigs")
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var numContigs: Int = _
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@Argument(fullName="pipeline_yaml", shortName="PY", doc="Pipeline YAML file")
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var pipelineYamlFile: File = _
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@Input(doc="trigger", shortName="trigger", required=false)
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var trigger: File = _
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@Input(doc="compCEU",shortName="ceu",required=false)
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var comp1KGCEU: File = _
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@Input(doc="refseqTable", shortName="refseqTable")
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var refseqTable: File = _
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@Input(doc="dbsnpTable", shortName="dbsnpTable")
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var dbsnpTable: File = _
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@Input(doc="Picard FixMateInformation.jar. At the Broad this can be found at /seq/software/picard/current/bin/FixMateInformation.jar. Outside the broad see http://picard.sourceforge.net/")
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var picardFixMatesJar: File = _
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@Input(doc="gatk jar")
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var gatkJar: File = _
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@Input(doc="SNP cluster filter -- number SNPs",shortName="snpsInCluster",required=false)
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var snpsInCluster = 4
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@Input(doc="SNP cluster filter -- window size",shortName="snpClusterWindow",required=false)
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var snpClusterWindow = 7
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@Input(doc="target titv for recalibration",shortName="titv",required=false)
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var target_titv = 2.1
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@Input(doc="downsampling coverage",shortName="dcov",required=false)
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var downsampling_coverage = 200
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@Input(doc="Number of jobs to scatter unifeid genotyper",shortName="snpScatter",required=false)
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var num_snp_scatter_jobs = 50
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@Input(doc="Number of jobs to scatter indel genotyper",shortName="indelScatter",required=false)
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var num_indel_scatter_jobs = 5
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@Input(doc="ADPR script")
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var adprScript: File = _
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@Input(doc="Sequencing maching name (for use by adpr)")
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var machine: String = _
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@Input(doc="Sequencing experiement type (for use by adpr)--Whole_Exome, Whole_Genome, or Hybrid_Selection")
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var protocol: String = _
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private var pipeline: Pipeline = _
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trait CommandLineGATKArgs extends CommandLineGATK {
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this.intervals = qscript.pipeline.getProject.getIntervalList
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this.jarFile = qscript.gatkJar
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this.reference_sequence = qscript.pipeline.getProject.getReferenceFile
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}
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// ------------ SETUP THE PIPELINE ----------- //
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def script = {
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pipeline = YamlUtils.load(classOf[Pipeline], qscript.pipelineYamlFile)
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val projectBase: String = qscript.pipeline.getProject.getName
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val cleanedBase: String = projectBase + ".cleaned"
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val uncleanedBase: String = projectBase + ".uncleaned"
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// there are commands that use all the bam files
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val recalibratedSamples = qscript.pipeline.getSamples
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.filter(_.getBamFiles.contains("recalibrated"))
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val adprRScript = qscript.adprScript
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val seq = qscript.machine
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val expKind = qscript.protocol
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for ( sample <- recalibratedSamples ) {
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// put unclean bams in unclean genotypers
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// in advance, create the extension files
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val bam = sample.getBamFiles.get("recalibrated")
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if (!sample.getBamFiles.contains("cleaned"))
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sample.getBamFiles.put("cleaned", swapExt(bam,"bam","cleaned.bam"))
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val cleaned_bam = sample.getBamFiles.get("cleaned")
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val indel_targets = swapExt(bam,"bam","realigner_targets.interval_list")
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// create the cleaning commands
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val targetCreator = new RealignerTargetCreator with CommandLineGATKArgs
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targetCreator.analysisName = "CreateTargets_"+bam.getName
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targetCreator.input_file :+= bam
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targetCreator.out = indel_targets
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val realigner = new IndelRealigner with CommandLineGATKArgs
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realigner.analysisName = "RealignBam_"+bam.getName
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realigner.input_file = targetCreator.input_file
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realigner.intervals = qscript.contigIntervals
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realigner.targetIntervals = new java.io.File(targetCreator.out.getAbsolutePath)
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realigner.scatterCount = qscript.numContigs
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// may need to explicitly run fix mates
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var fixMates = new PicardBamJarFunction {
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// Declare inputs/outputs for dependency tracking.
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@Input(doc="unfixed bam") var unfixed: File = _
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@Output(doc="fixed bam") var fixed: File = _
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def inputBams = List(unfixed)
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def outputBam = fixed
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}
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// realigner.out = cleaned_bam
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// realigner.scatterClass = classOf[ContigScatterFunction]
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// realigner.setupGatherFunction = { case (f: BamGatherFunction, _) => f.jarFile = qscript.picardFixMatesJar }
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// realigner.jobQueue = "week"
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// if scatter count is > 1, do standard scatter gather, if not, explicitly set up fix mates
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if (realigner.scatterCount > 1) {
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realigner.out = cleaned_bam
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// While gathering run fix mates.
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realigner.scatterClass = classOf[ContigScatterFunction]
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realigner.setupGatherFunction = {
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case (gather: BamGatherFunction, _) =>
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gather.memoryLimit = Some(4)
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gather.jarFile = qscript.picardFixMatesJar
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// Don't pass this AS=true to fix mates!
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gather.assumeSorted = None
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}
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} else {
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realigner.out = swapExt(bam,"bam","unfixed.cleaned.bam")
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// Explicitly run fix mates if the function won't be scattered.
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fixMates.memoryLimit = Some(4)
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fixMates.jarFile = qscript.picardFixMatesJar
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fixMates.unfixed = realigner.out
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fixMates.fixed = cleaned_bam
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fixMates.analysisName = "FixMates_"+bam.getName
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// Add the fix mates explicitly
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}
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var samtoolsindex = new SamtoolsIndexFunction
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samtoolsindex.bamFile = cleaned_bam
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samtoolsindex.analysisName = "index_"+cleaned_bam.getName
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// COMMENT THIS NEXT BLOCK TO SKIP CLEANING
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if ( realigner.scatterCount > 1 )
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add(targetCreator,realigner,samtoolsindex)
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else
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add(targetCreator,realigner,fixMates,samtoolsindex)
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}
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val recalibratedBamFiles = recalibratedSamples
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.map(_.getBamFiles.get("recalibrated"))
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.toList
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val cleanBamFiles = qscript.pipeline.getSamples
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.filter(_.getBamFiles.contains("cleaned"))
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.map(_.getBamFiles.get("cleaned"))
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.toList
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// actually make calls
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endToEnd(uncleanedBase,recalibratedBamFiles, adprRscript, seq, expKind)
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// COMMENT THIS NEXT LINE TO AVOID CALLING ON CLEANED FILES
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endToEnd(cleanedBase,cleanBamFiles, adprRscript, seq, expKind)
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}
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def endToEnd(base: String, bamFiles: List[File], adprthing: File, seqinfo: String, exptype: String) = {
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// step through the un-indel-cleaned graph:
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// 1a. call snps and indels
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val snps = new UnifiedGenotyper with CommandLineGATKArgs
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snps.analysisName = base+"_SNP_calls"
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snps.input_file = bamFiles
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snps.group :+= "Standard"
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snps.out = new File(base+".vcf")
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snps.standard_min_confidence_threshold_for_emitting = Some(10)
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snps.min_mapping_quality_score = Some(20)
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snps.min_base_quality_score = Some(20)
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snps.downsample_to_coverage = Some(200)
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//snps.annotation :+= "QualByDepthV2"
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if (qscript.trigger != null) {
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snps.trigger_min_confidence_threshold_for_calling = Some(30)
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snps.rodBind :+= RodBind("trigger", "VCF", qscript.trigger)
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// TODO: triggers need to get a name for comp-ing them if not dbSNP?
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snps.rodBind :+= RodBind( "compTrigger", "VCF", qscript.trigger )
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}
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// todo -- add generalize comp inputs
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if ( qscript.comp1KGCEU != null ) {
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snps.rodBind :+= RodBind( "comp1KG_CEU", "VCF", qscript.comp1KGCEU )
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}
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snps.scatterCount = qscript.num_snp_scatter_jobs
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// indel genotyper does one sample at a time
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var indelCallFiles = List.empty[RodBind]
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var indelGenotypers = List.empty[IndelGenotyperV2 with CommandLineGATKArgs]
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var loopNo = 0
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var priority = ""
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for ( bam <- bamFiles ) {
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var indel = new IndelGenotyperV2 with CommandLineGATKArgs
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indel.analysisName = "IndelGenotyper_"+bam.getName
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indel.input_file :+= bam
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indel.out = swapExt(bam,".bam",".indels.vcf")
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indel.downsample_to_coverage = Some(500)
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indelCallFiles :+= RodBind("v"+loopNo.toString, "VCF", indel.out)
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indel.scatterCount = qscript.num_indel_scatter_jobs
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indelGenotypers :+= indel
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if ( loopNo == 0 ) {
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priority = "v0"
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} else {
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priority += ",v"+loopNo.toString
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}
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loopNo += 1
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}
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val mergeIndels = new CombineVariants with CommandLineGATKArgs
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mergeIndels.out = new TaggedFile(qscript.pipeline.getProject.getName+".indels.vcf","vcf")
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mergeIndels.genotypemergeoption = Some(org.broadinstitute.sting.gatk.contexts.variantcontext.VariantContextUtils.GenotypeMergeType.UNIQUIFY)
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mergeIndels.priority = priority
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mergeIndels.variantmergeoption = Some(org.broadinstitute.sting.gatk.contexts.variantcontext.VariantContextUtils.VariantMergeType.UNION)
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mergeIndels.rodBind = indelCallFiles
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mergeIndels.analysisName = base+"_MergeIndels"
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// 1b. genomically annotate SNPs -- no longer slow
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val annotated = new GenomicAnnotator with CommandLineGATKArgs
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annotated.rodBind :+= RodBind("variant", "VCF", snps.out)
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annotated.rodBind :+= RodBind("refseq", "AnnotatorInputTable", qscript.refseqTable)
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annotated.rodBind :+= RodBind("dbsnp", "AnnotatorInputTable", qscript.dbsnpTable)
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annotated.out = swapExt(snps.out,".vcf",".annotated.vcf")
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annotated.select :+= "dbsnp.name,dbsnp.refUCSC,dbsnp.strand,dbsnp.observed,dbsnp.avHet"
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annotated.rodToIntervalTrackName = "variant"
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annotated.analysisName = base+"_GenomicAnnotator"
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// 2.a filter on cluster and near indels
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val masker = new VariantFiltration with CommandLineGATKArgs
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masker.variantVCF = annotated.out
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masker.rodBind :+= RodBind("mask", "VCF", mergeIndels.out)
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masker.maskName = "NearIndel"
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masker.clusterWindowSize = Some(qscript.snpClusterWindow)
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masker.clusterSize = Some(qscript.snpsInCluster)
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masker.out = swapExt(annotated.out,".vcf",".indel.masked.vcf")
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masker.analysisName = base+"_Cluster_and_Indel_filter"
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// 2.b hand filter with standard filter
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val handFilter = new VariantFiltration with CommandLineGATKArgs
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handFilter.variantVCF = masker.out
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handFilter.rodBind :+= RodBind("mask", "VCF", mergeIndels.out)
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handFilter.filterName ++= List("StrandBias","AlleleBalance","QualByDepth","HomopolymerRun")
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handFilter.filterExpression ++= List("\"SB>=0.10\"","\"AB>=0.75\"","\"QD<5.0\"","\"HRun>=4\"")
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handFilter.out = swapExt(annotated.out,".vcf",".handfiltered.vcf")
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handFilter.analysisName = base+"_HandFilter"
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// 3.i generate gaussian clusters on the masked vcf
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// todo -- args for annotations?
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// todo -- args for resources (properties file)
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val clusters = new GenerateVariantClusters with CommandLineGATKArgs
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clusters.rodBind :+= RodBind("input", "VCF", masker.out)
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clusters.DBSNP = qscript.pipeline.getProject.getDbsnpFile
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val clusters_clusterFile = swapExt(new File(snps.out.getAbsolutePath),".vcf",".cluster")
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clusters.clusterFile = clusters_clusterFile
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clusters.memoryLimit = Some(4)
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clusters.jobQueue = "gsa"
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clusters.use_annotation ++= List("QD", "SB", "HaplotypeScore", "HRun")
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clusters.analysisName = base+"_Cluster"
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// 3.ii apply gaussian clusters to the masked vcf
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val recalibrate = new VariantRecalibrator with CommandLineGATKArgs
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recalibrate.clusterFile = clusters.clusterFile
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recalibrate.DBSNP = qscript.pipeline.getProject.getDbsnpFile
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recalibrate.rodBind :+= RodBind("input", "VCF", masker.out)
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recalibrate.out = swapExt(masker.out,".vcf",".recalibrated.vcf")
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recalibrate.target_titv = qscript.target_titv
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recalibrate.report_dat_file = swapExt(masker.out,".vcf",".recalibrate.dat")
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recalibrate.tranches_file = swapExt(masker.out,".vcf",".recalibrate.tranches")
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recalibrate.analysisName = base+"_VariantRecalibrator"
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// 3.iii apply variant cuts to the clusters
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val cut = new ApplyVariantCuts with CommandLineGATKArgs
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cut.rodBind :+= RodBind("input", "VCF", recalibrate.out)
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cut.out = swapExt(recalibrate.out,".vcf",".tranched.vcf")
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cut.tranches_file = recalibrate.tranches_file
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// todo -- fdr inputs, etc
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cut.fdr_filter_level = Some(1)
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cut.analysisName = base+"_ApplyVariantCuts"
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// 4. Variant eval the cut and the hand-filtered vcf files
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val eval = new VariantEval with CommandLineGATKArgs
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eval.rodBind :+= RodBind("evalOptimized", "VCF", cut.out)
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eval.rodBind :+= RodBind("evalHandFiltered", "VCF", handFilter.out)
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eval.evalModule ++= List("CountFunctionalClasses", "CompOverlap", "CountVariants", "TiTvVariantEvaluator")
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eval.reportLocation = new File(base+".eval")
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eval.reportType = "R"
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eval.analysisName = base+"_VariantEval"
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add(snps)
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// 5. Run the ADPR and make pretty stuff
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val adpr = new CommandLineFunction{
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@Input(doc="Dependent files") var dependents: File = _
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@Output(doc="Automated Data processing report") var out: File = _
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var setname: String
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var protocol: String
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var sequencer: String
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var scriptloc: File
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def commandLine = "Rscript %s %s %s %s"
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.format(scriptloc, setname, protocol, sequencer)
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}
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adpr.setname = base
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adpr.scriptloc = adprthing
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adpr.sequencer = seqinfo
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adpr.protocol = exptype
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adpr.dependents = eval.reportLocation
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adpr.out = new File(base + "_adpr.pdf")
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adpr.analysisName = base + "_ADPR"
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//In order for ADPR to finish successfully, a squid file for both the lane and sample level data needs to be
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// produced, reformatted and named <projectBase>_lanes.txt or <projectBase>_samps.txt, respectively. These files
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// to be in the working directory. When database access is ready, this and the protocol and sequencer parameters of
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//the r script will go away.
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for ( igv2 <- indelGenotypers ) {
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add(igv2)
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}
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add(mergeIndels,annotated,masker,handFilter,clusters,recalibrate,cut,eval,adpr)
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}
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}
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