400 lines
19 KiB
Plaintext
Executable File
400 lines
19 KiB
Plaintext
Executable File
import org.broadinstitute.sting.commandline.ArgumentSource
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import org.broadinstitute.sting.datasources.pipeline.Pipeline
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import org.broadinstitute.sting.gatk.walkers.genotyper.GenotypeCalculationModel.Model
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import org.broadinstitute.sting.gatk.DownsampleType
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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.function.scattergather.{GatherFunction, CloneFunction, ScatterFunction}
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import org.broadinstitute.sting.queue.util.IOUtils
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import org.broadinstitute.sting.queue.QScript
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import collection.JavaConversions._
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import org.broadinstitute.sting.utils.interval.IntervalUtils
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import org.broadinstitute.sting.utils.yaml.YamlUtils
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import org.broadinstitute.sting.utils.report.VE2ReportFactory.VE2TemplateType
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class fullCallingPipeline extends QScript {
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qscript =>
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@Argument(doc="the YAML file specifying inputs, interval lists, reference sequence, etc.", shortName="Y")
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var yamlFile: File = _
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@Input(doc="path to trigger track (for UnifiedGenotyper)", shortName="trigger", required=false)
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var trigger: File = _
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@Input(doc="path to refseqTable (for GenomicAnnotator)", shortName="refseqTable")
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var refseqTable: File = _
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@Input(doc="path to Picard FixMateInformation.jar. See http://picard.sourceforge.net/ .", required=false)
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var picardFixMatesJar: File = new java.io.File("/seq/software/picard/current/bin/FixMateInformation.jar")
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@Input(doc="path to GATK jar")
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var gatkJar: File = _
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@Input(doc="target Ti/Tv ratio for recalibration", shortName="titv", required=true)
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var target_titv: Float = _
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@Input(doc="per-sample downsampling level",shortName="dcov",required=false)
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var downsampling_coverage = 300
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@Input(doc="level of parallelism for IndelRealigner. By default is set to 1.", shortName="cleanerScatter", required=false)
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var num_cleaner_scatter_jobs = 1
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@Input(doc="level of parallelism for UnifiedGenotyper. By default is set to 20.", shortName="snpScatter", required=false)
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var num_snp_scatter_jobs = 20
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//@Input(doc="level of parallelism for IndelGenotyperV2", shortName="indelScatter", required=false)
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//var num_indel_scatter_jobs = 5
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@Input(doc="Skip indel-cleaning for BAM files (for testing only)", shortName="skipCleaning", required=false)
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var skip_cleaning = false
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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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@Argument(doc="Job queue for large memory jobs (>4 to 16GB)", shortName="bigMemQueue", required=false)
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var big_mem_queue: String = _
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@Argument(doc="Job queue for short run jobs (<1hr)", shortName="shortJobQueue", required=false)
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var short_job_queue: String = _
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private var pipeline: Pipeline = _
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trait CommandLineGATKArgs extends CommandLineGATK {
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this.intervals = List(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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this.memoryLimit = Some(4)
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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.yamlFile)
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val projectBase: String = qscript.pipeline.getProject.getName
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if (qscript.skip_cleaning) {
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//endToEnd(projectBase + ".uncleaned", "recalibrated", adprRscript, seq, expKind)
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endToEnd(projectBase + ".uncleaned", "recalibrated")
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} else {
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// there are commands that use all the bam files
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val recalibratedSamples = qscript.pipeline.getSamples.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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// get contigs (needed for indel cleaning parallelism)
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val contigs = IntervalUtils.distinctContigs(
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qscript.pipeline.getProject.getReferenceFile,
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List(qscript.pipeline.getProject.getIntervalList.getAbsolutePath)).toList
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for ( sample <- recalibratedSamples ) {
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val sampleId = sample.getId
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// put unclean bams in unclean genotypers 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("CleanedBams", bam,"bam","cleaned.bam"))
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}
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val cleaned_bam = sample.getBamFiles.get("cleaned")
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val indel_targets = swapExt("CleanedBams/IntermediateFiles/"+sampleId, 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.jobOutputFile = new File(".queue/logs/Cleaning/%s/RealignerTargetCreator.out".format(sampleId))
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targetCreator.jobName = "CreateTargets_"+sampleId
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targetCreator.analysisName = "CreateTargets_"+sampleId
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targetCreator.input_file :+= bam
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targetCreator.out = indel_targets
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targetCreator.memoryLimit = Some(2)
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targetCreator.isIntermediate = true
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val realigner = new IndelRealigner with CommandLineGATKArgs
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realigner.jobOutputFile = new File(".queue/logs/Cleaning/%s/IndelRealigner.out".format(sampleId))
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realigner.analysisName = "RealignBam_"+sampleId
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realigner.input_file = targetCreator.input_file
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realigner.targetIntervals = targetCreator.out
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realigner.intervals = Nil
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realigner.intervalsString = Nil
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realigner.scatterCount = num_cleaner_scatter_jobs min contigs.size
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realigner.DBSNP = qscript.pipeline.getProject.getDbsnpFile
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realigner.rodBind :+= RodBind("indels", "VCF", swapExt(realigner.reference_sequence.getParentFile, realigner.reference_sequence, "fasta", "1kg_pilot_indels.vcf"))
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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.intervalsString = contigs
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realigner.out = cleaned_bam
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// While gathering run fix mates.
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realigner.setupScatterFunction = {
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case scatter: ScatterFunction =>
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scatter.commandDirectory = new File("CleanedBams/IntermediateFiles/%s/ScatterGather".format(sampleId))
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scatter.jobOutputFile = new File(".queue/logs/Cleaning/%s/Scatter.out".format(sampleId))
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}
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realigner.setupCloneFunction = {
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case (clone: CloneFunction, index: Int) =>
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clone.commandDirectory = new File("CleanedBams/IntermediateFiles/%s/ScatterGather/Scatter_%s".format(sampleId, index))
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clone.jobOutputFile = new File(".queue/logs/Cleaning/%s/Scatter_%s.out".format(sampleId, index))
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}
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realigner.setupGatherFunction = {
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case (gather: BamGatherFunction, source: ArgumentSource) =>
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gather.commandDirectory = new File("CleanedBams/IntermediateFiles/%s/ScatterGather/Gather_%s".format(sampleId, source.field.getName))
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gather.jobOutputFile = new File(".queue/logs/Cleaning/%s/FixMates.out".format(sampleId))
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gather.memoryLimit = Some(6)
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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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case (gather: GatherFunction, source: ArgumentSource) =>
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gather.commandDirectory = new File("CleanedBams/IntermediateFiles/%s/ScatterGather/Gather_%s".format(sampleId, source.field.getName))
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gather.jobOutputFile = new File(".queue/logs/Cleaning/%s/Gather_%s.out".format(sampleId, source.field.getName))
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}
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add(targetCreator,realigner)
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} else {
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realigner.out = swapExt("CleanedBams/IntermediateFiles/"+sampleId,bam,"bam","unfixed.cleaned.bam")
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realigner.isIntermediate = true
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// Explicitly run fix mates if the function won't be scattered.
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val 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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fixMates.jobOutputFile = new File(".queue/logs/Cleaning/%s/FixMates.out".format(sampleId))
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fixMates.memoryLimit = Some(6)
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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_"+sampleId
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// Add the fix mates explicitly
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add(targetCreator,realigner,fixMates)
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}
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var samtoolsindex = new SamtoolsIndexFunction
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samtoolsindex.jobOutputFile = new File(".queue/logs/Cleaning/%s/SamtoolsIndex.out".format(sampleId))
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samtoolsindex.bamFile = cleaned_bam
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samtoolsindex.analysisName = "index_cleaned_"+sampleId
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samtoolsindex.jobQueue = qscript.short_job_queue
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add(samtoolsindex)
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}
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//endToEnd(projectBase + ".cleaned", "cleaned", adprRscript, seq, expKind)
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endToEnd(projectBase + ".cleaned", "cleaned")
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}
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}
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//def endToEnd(base: String, bamType: String, adprthing: File, seqinfo: String, exptype: String) = {
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def endToEnd(base: String, bamType: String) = {
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val samples = qscript.pipeline.getSamples.filter(_.getBamFiles.contains(bamType)).toList
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val bamFiles = samples.map(_.getBamFiles.get(bamType))
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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.jobOutputFile = new File(".queue/logs/SNPCalling/UnifiedGenotyper.out")
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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("SnpCalls", 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(qscript.downsampling_coverage)
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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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snps.setupScatterFunction = {
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case scatter: ScatterFunction =>
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scatter.commandDirectory = new File("SnpCalls/ScatterGather")
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scatter.jobOutputFile = new File(".queue/logs/SNPCalling/ScatterGather/Scatter.out")
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}
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snps.setupCloneFunction = {
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case (clone: CloneFunction, index: Int) =>
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clone.commandDirectory = new File("SnpCalls/ScatterGather/Scatter_%s".format(index))
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clone.jobOutputFile = new File(".queue/logs/SNPCalling/ScatterGather/Scatter_%s.out".format(index))
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}
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snps.setupGatherFunction = {
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case (gather: GatherFunction, source: ArgumentSource) =>
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gather.commandDirectory = new File("SnpCalls/ScatterGather/Gather_%s".format(source.field.getName))
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gather.jobOutputFile = new File(".queue/logs/SNPCalling/ScatterGather/Gather_%s.out".format(source.field.getName))
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}
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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 ( sample <- samples ) {
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val sampleId = sample.getId
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val bam = sample.getBamFiles.get(bamType)
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var indel = new IndelGenotyperV2 with CommandLineGATKArgs
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indel.jobOutputFile = new File(".queue/logs/IndelCalling/%s/IndelGenotyperV2.out".format(sampleId))
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indel.analysisName = "IndelGenotyper_"+sampleId
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indel.input_file :+= bam
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indel.out = swapExt("IndelCalls/IntermediateFiles/" + sampleId, bam,".bam",".indels.vcf")
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indel.downsample_to_coverage = Some(qscript.downsampling_coverage)
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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.jobOutputFile = new File(".queue/logs/IndelCalling/CombineVariants.out")
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mergeIndels.out = new TaggedFile("IndelCalls/" + 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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mergeIndels.memoryLimit = Some(16)
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mergeIndels.jobQueue = qscript.big_mem_queue
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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.jobOutputFile = new File(".queue/logs/SNPCalling/GenomicAnnotator.out")
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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("SnpCalls",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.jobOutputFile = new File(".queue/logs/SNPCalling/Masker.out")
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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(10)
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masker.clusterSize = Some(3)
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masker.out = swapExt("SnpCalls",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.jobOutputFile = new File(".queue/logs/SNPCalling/HandFilter.out")
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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("SnpCalls",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.jobOutputFile = new File(".queue/logs/SNPCalling/Clusters.out")
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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("SnpCalls/IntermediateFiles",snps.out,".vcf",".cluster")
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clusters.clusterFile = clusters_clusterFile
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clusters.memoryLimit = Some(6)
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clusters.jobQueue = qscript.big_mem_queue
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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.jobOutputFile = new File(".queue/logs/SNPCalling/Recalibrator.out")
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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("SnpCalls",masker.out,".vcf",".recalibrated.vcf")
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recalibrate.target_titv = qscript.target_titv
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recalibrate.report_dat_file = swapExt("SnpCalls/IntermediateFiles", masker.out,".vcf",".recalibrate.dat")
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recalibrate.tranches_file = swapExt("SnpCalls/IntermediateFiles", 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.jobOutputFile = new File(".queue/logs/SNPCalling/VariantCuts.out")
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cut.rodBind :+= RodBind("input", "VCF", recalibrate.out)
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cut.out = swapExt("SnpCalls",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.jobOutputFile = new File(".queue/logs/SNPCalling/VariantEval.out")
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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("SnpCalls", base+".eval")
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eval.reportType = Option(org.broadinstitute.sting.utils.report.VE2ReportFactory.VE2TemplateType.R)
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eval.analysisName = base+"_VariantEval"
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eval.DBSNP = qscript.pipeline.getProject.getDbsnpFile
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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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//
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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.jobOutputFile = new File(".queue/logs/Reporting/ADPR.out")
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// adpr.out = new File("Reporting", 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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add(mergeIndels,annotated,masker,handFilter,clusters,recalibrate,cut,eval)
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}
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}
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