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cosmetic change. 

git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@5481 348d0f76-0448-11de-a6fe-93d51630548a
This commit is contained in:
carneiro 2011-03-21 15:46:04 +00:00
parent d9202f2764
commit 1198a90ac7
1 changed files with 6 additions and 62 deletions
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68
scala/qscript/core/MethodsDevelopmentCallingPipeline.scala
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@ -249,6 +249,7 @@ class MethodsDevelopmentCallingPipeline extends QScript {
// 3.) Variant Quality Score Recalibration - Generate Recalibration table
class VQSR(t: Target, goldStandard: Boolean) extends ContrastiveRecalibrator with UNIVERSAL_GATK_ARGS {
this.memoryLimit = Some(6)
this.reference_sequence = t.reference
this.intervalsString ++= List(t.intervals)
this.rodBind :+= RodBind("input", "VCF", if ( goldStandard ) { t.goldStandard_VCF } else { t.rawVCF } )
this.rodBind :+= RodBind("hapmap", "VCF", t.hapmapFile)
@ -265,82 +266,25 @@ class MethodsDevelopmentCallingPipeline extends QScript {
this.recal_file = if ( goldStandard ) { t.goldStandardRecalFile } else { t.recalFile }
this.allPoly = true
this.tranche ++= List("0.1", "0.5", "0.7", "1.0", "1.1", "1.2", "1.5", "1.6", "1.7", "1.8", "1.9", "2.0", "2.1", "2.2", "2.5","3.0", "5.0", "10.0")
this.analysisName = t.name + "_VQSR"
this.jobName = queueLogDir + t.name + ".VQSR"
}
// 4.) Apply the recalibration table to the appropriate tranches
class applyVQSR (t: Target, goldStandard: Boolean) extends ApplyRecalibration with UNIVERSAL_GATK_ARGS {
this.memoryLimit = Some(4)
this.reference_sequence = t.reference
this.intervalsString ++= List(t.intervals)
this.rodBind :+= RodBind("input", "VCF", if ( goldStandard ) { t.goldStandard_VCF } else { t.rawVCF } )
this.tranches_file = if ( goldStandard ) { t.goldStandardTranchesFile } else { t.tranchesFile}
this.recal_file = if ( goldStandard ) { t.goldStandardRecalFile } else { t.recalFile }
this.fdr_filter_level = Some(2.0)
this.out = t.recalibratedVCF
this.analysisName = t.name + "_AVQSR"
this.jobName = queueLogDir + t.name + ".applyVQSR"
}
/*
* Obsolete
// 3.) VQSR part1 Generate Gaussian clusters based on truth sites
class GenerateClusters(t: Target, goldStandard: Boolean) extends GenerateVariantClusters with UNIVERSAL_GATK_ARGS {
val name: String = if ( goldStandard ) { t.goldStandardName } else { t.name }
this.reference_sequence = t.reference
this.rodBind :+= RodBind("hapmap", "VCF", t.hapmapFile)
if( t.hapmapFile.contains("b37") )
this.rodBind :+= RodBind("1kg", "VCF", omni_b37)
else if( t.hapmapFile.contains("b36") )
this.rodBind :+= RodBind("1kg", "VCF", omni_b36)
this.rodBind :+= RodBind("input", "VCF", if ( goldStandard ) { t.goldStandard_VCF } else { t.filteredVCF } )
this.clusterFile = if ( goldStandard ) { t.goldStandardClusterFile } else { t.clusterFile }
this.use_annotation ++= List("QD", "SB", "HaplotypeScore", "HRun")
this.intervalsString ++= List(t.intervals)
this.qual = Some(100) // clustering parameters to be updated soon pending new experimentation results
this.std = Some(3.5)
this.mG = Some(8)
this.ignoreFilter ++= FiltersToIgnore
this.analysisName = name + "_GVC"
this.jobName = queueLogDir + t.name + ".cluster"
if (t.dbsnpFile.endsWith(".rod"))
this.DBSNP = new File(t.dbsnpFile)
else if (t.dbsnpFile.endsWith(".vcf"))
this.rodBind :+= RodBind("dbsnp", "VCF", t.dbsnpFile)
this.trustAllPolymorphic = true
}
// 4.) VQSR part2 Calculate new LOD for all input SNPs by evaluating the Gaussian clusters
class VariantRecalibratorNRS(t: Target, goldStandard: Boolean) extends VariantRecalibrator with UNIVERSAL_GATK_ARGS {
val name: String = if ( goldStandard ) { t.goldStandardName } else { t.name }
this.reference_sequence = t.reference
if( t.hapmapFile.contains("b37") ) {
this.rodBind :+= RodBind("1kg", "VCF", omni_b37)
this.rodBind :+= RodBind("truthOmni", "VCF", omni_b37)
} else if( t.hapmapFile.contains("b36") ) {
this.rodBind :+= RodBind("1kg", "VCF", omni_b36)
this.rodBind :+= RodBind("truthOmni", "VCF", omni_b36)
}
this.rodBind :+= RodBind("hapmap", "VCF", t.hapmapFile)
this.rodBind :+= RodBind("truthHapMap", "VCF", t.hapmapFile)
this.rodBind :+= RodBind("input", "VCF", if ( goldStandard ) { t.goldStandard_VCF } else { t.filteredVCF } )
this.clusterFile = if ( goldStandard ) { t.goldStandardClusterFile } else { t.clusterFile }
this.analysisName = name + "_VR"
this.intervalsString ++= List(t.intervals)
this.ignoreFilter ++= FiltersToIgnore
this.ignoreFilter ++= List("HARD_TO_VALIDATE")
if (t.dbsnpFile.endsWith(".rod"))
this.DBSNP = new File(t.dbsnpFile)
else if (t.dbsnpFile.endsWith(".vcf"))
this.rodBind :+= RodBind("dbsnp", "VCF", t.dbsnpFile)
this.sm = Some(org.broadinstitute.sting.gatk.walkers.variantrecalibration.VariantRecalibrator.SelectionMetricType.TRUTH_SENSITIVITY)
this.tranche ++= List("0.1", "0.5", "0.7", "1.0", "3.0", "5.0", "10.0", "100.0")
this.out = if ( goldStandard ) { t.goldStandardTsRecalibratedVCF } else { t.tsRecalibratedVCF }
this.tranchesFile = if ( goldStandard ) { t.goldStandardTsTranchesFile } else { t.tsTranchesFile }
this.jobName = queueLogDir + t.name + ".nrs"
this.trustAllPolymorphic = true
}
*/
// 5.) Variant Cut filter out the variants marked by recalibration to the 99% tranche
class VariantCut(t: Target) extends ApplyVariantCuts with UNIVERSAL_GATK_ARGS {
@ -350,12 +294,12 @@ class MethodsDevelopmentCallingPipeline extends QScript {
this.out = t.cutVCF
this.tranchesFile = t.tranchesFile
this.fdr_filter_level = Some(t.trancheTarget)
this.analysisName = t.name + "_VC"
this.jobName = queueLogDir + t.name + ".cut"
if (t.dbsnpFile.endsWith(".rod"))
this.DBSNP = new File(t.dbsnpFile)
else if (t.dbsnpFile.endsWith(".vcf"))
this.rodBind :+= RodBind("dbsnp", "VCF", t.dbsnpFile)
this.analysisName = t.name + "_VC"
this.jobName = queueLogDir + t.name + ".cut"
}
// 6.) Variant Evaluation Base(OPTIONAL)