300 lines
18 KiB
Scala
300 lines
18 KiB
Scala
|
import org.broadinstitute.sting.gatk.CommandLineGATK
|
||
|
import org.broadinstitute.sting.queue.extensions.gatk._
|
||
|
|
import org.broadinstitute.sting.queue.QScript
|
||
|
import org.broadinstitute.sting.gatk.phonehome.GATKRunReport
|
||
|
|
|
||
|
|
class MethodsDevelopmentCallingPipeline extends QScript {
|
||
|
|
qscript =>
|
||
|
|
|
||
|
|
@Argument(shortName="gatk", doc="gatk jar file", required=true)
|
||
|
|
var gatkJarFile: File = _
|
||
|
|
|
||
|
|
@Argument(shortName="outputDir", doc="output directory", required=true)
|
||
|
|
var outputDir: String = "./"
|
||
|
|
|
||
|
|
@Argument(shortName="skipCalling", doc="If true, skip the calling part of the pipeline and only run VQSR on preset, gold standard VCF files", required=false)
|
||
|
|
var skipCalling: Boolean = false
|
||
|
|
|
||
|
|
@Argument(shortName="dataset", doc="selects the datasets to run. If not provided, all datasets will be used", required=false)
|
||
|
|
var datasets: List[String] = Nil
|
||
|
|
|
||
|
|
@Argument(shortName="skipGoldStandard", doc="runs the pipeline with the goldstandard VCF files for comparison", required=false)
|
||
|
|
var skipGoldStandard: Boolean = false
|
||
|
|
|
||
|
|
@Argument(shortName="noBAQ", doc="turns off BAQ calculation", required=false)
|
||
|
|
var noBAQ: Boolean = false
|
||
|
|
|
||
|
|
@Argument(shortName="noMASK", doc="turns off MASK calculation", required=false)
|
||
|
|
var noMASK: Boolean = false
|
||
|
|
|
||
|
|
@Argument(shortName="eval", doc="adds the VariantEval walker to the pipeline", required=false)
|
||
|
|
var eval: Boolean = false
|
||
|
|
|
||
|
|
@Argument(shortName="noCut", doc="adds the ApplyVariantCut walker to the pipeline", required=false)
|
||
|
|
var noCut: Boolean = false
|
||
|
|
|
||
|
|
@Argument(shortName="LOCAL_ET", doc="Doesn't use the AWS S3 storage for ET option", required=false)
|
||
|
|
var LOCAL_ET: Boolean = false
|
||
|
|
|
||
|
|
trait UNIVERSAL_GATK_ARGS extends CommandLineGATK {
|
||
|
|
logging_level = "INFO";
|
||
|
|
jarFile = gatkJarFile;
|
||
|
|
memoryLimit = Some(3);
|
||
|
|
phone_home = Some(if ( LOCAL_ET ) GATKRunReport.PhoneHomeOption.STANDARD else GATKRunReport.PhoneHomeOption.AWS_S3)
|
||
|
|
}
|
||
|
|
|
||
|
|
class Target(
|
||
|
|
val baseName: String,
|
||
|
|
val reference: File,
|
||
|
|
val dbsnpFile: String,
|
||
|
|
val hapmapFile: String,
|
||
|
|
val maskFile: String,
|
||
|
|
val bamList: File,
|
||
|
|
val goldStandard_VCF: File,
|
||
|
|
val intervals: String,
|
||
|
|
val titvTarget: Double,
|
||
|
|
val isLowpass: Boolean) {
|
||
|
|
val name = qscript.outputDir + baseName
|
||
|
|
val clusterFile = new File(name + ".clusters")
|
||
|
|
val rawVCF = new File(name + ".raw.vcf")
|
||
|
|
val filteredVCF = new File(name + ".filtered.vcf")
|
||
|
|
val titvRecalibratedVCF = new File(name + ".titv.recalibrated.vcf")
|
||
|
|
val titvTranchesFile = new File(name + ".titv.tranches")
|
||
|
|
val tsRecalibratedVCF = new File(name + ".ts.recalibrated.vcf")
|
||
|
|
val tsTranchesFile = new File(name + ".ts.tranches")
|
||
|
|
val cutVCF = new File(name + ".cut.vcf")
|
||
|
|
val evalFile = new File(name + ".eval")
|
||
|
|
val goldStandardName = qscript.outputDir + "goldStandard/" + baseName
|
||
|
|
val goldStandardClusterFile = new File(goldStandardName + ".clusters")
|
||
|
|
}
|
||
|
|
|
||
|
|
val hg19 = new File("/seq/references/Homo_sapiens_assembly19/v1/Homo_sapiens_assembly19.fasta")
|
||
|
|
val hg18 = new File("/seq/references/Homo_sapiens_assembly18/v0/Homo_sapiens_assembly18.fasta")
|
||
|
|
val b36 = new File("/humgen/1kg/reference/human_b36_both.fasta")
|
||
|
|
val b37 = new File("/humgen/1kg/reference/human_g1k_v37.fasta")
|
||
|
|
val dbSNP_hg18 = "/humgen/gsa-hpprojects/GATK/data/Comparisons/Validated/dbSNP/dbsnp_130_hg18.rod"
|
||
|
|
val dbSNP_b36 = "/humgen/gsa-hpprojects/GATK/data/Comparisons/Validated/dbSNP/dbsnp_130_b36.rod"
|
||
|
|
val dbSNP_b37 = "/humgen/gsa-hpprojects/GATK/data/Comparisons/Validated/dbSNP/dbsnp_132_b37.leftAligned.vcf"
|
||
|
|
val dbSNP_b37_129 = "/humgen/gsa-hpprojects/GATK/data/Comparisons/Validated/dbSNP/dbsnp_129_b37.rod" // Special case for NA12878 collections that can't use 132 because they are part of it.
|
||
|
|
val hapmap_hg18 = "/humgen/gsa-hpprojects/GATK/data/Comparisons/Validated/HapMap/3.3/sites_r27_nr.hg18_fwd.vcf"
|
||
|
|
val hapmap_b36 = "/humgen/gsa-hpprojects/GATK/data/Comparisons/Validated/HapMap/3.3/sites_r27_nr.b36_fwd.vcf"
|
||
|
|
val hapmap_b37 = "/humgen/gsa-hpprojects/GATK/data/Comparisons/Validated/HapMap/3.3/sites_r27_nr.b37_fwd.vcf"
|
||
|
|
val indelMask_b36 = "/humgen/1kg/processing/pipeline_test_bams/pilot1.dindel.mask.b36.bed"
|
||
|
|
val indelMask_b37 = "/humgen/1kg/processing/pipeline_test_bams/pilot1.dindel.mask.b37.bed"
|
||
|
|
|
||
|
|
// ToDos:
|
||
|
|
// reduce the scope of the datasets so the script is more nimble
|
||
|
|
// figure out how to give names to all the Queue-LSF logs (other than Q-1931@node1434-24.out) so that it is easier to find logs for certain steps
|
||
|
|
// create gold standard BAQ'd bam files, no reason to always do it on the fly
|
||
|
|
|
||
|
|
// Analysis to add at the end of the script:
|
||
|
|
// auto generation of the cluster plots
|
||
|
|
// spike in NA12878 to the exomes and to the lowpass, analysis of how much of her variants are being recovered compared to single sample exome or HiSeq calls
|
||
|
|
// produce Kiran's Venn plots based on comparison between new VCF and gold standard produced VCF
|
||
|
|
|
||
|
|
val lowPass: Boolean = true
|
||
|
|
|
||
|
|
val targetDataSets: Map[String, Target] = Map(
|
||
|
|
"HiSeq" -> new Target("NA12878.HiSeq", hg18, dbSNP_hg18, hapmap_hg18,
|
||
|
|
"/humgen/gsa-hpprojects/dev/depristo/oneOffProjects/1000GenomesProcessingPaper/wgs.v13/HiSeq.WGS.cleaned.indels.10.mask",
|
||
|
|
new File("/humgen/gsa-hpprojects/NA12878Collection/bams/NA12878.HiSeq.WGS.bwa.cleaned.recal.bam"),
|
||
|
|
new File("/home/radon01/depristo/work/oneOffProjects/1000GenomesProcessingPaper/wgs.v13/HiSeq.WGS.cleaned.ug.snpfiltered.indelfiltered.vcf"),
|
||
|
|
"/humgen/1kg/processing/pipeline_test_bams/whole_genome_chunked.hg18.intervals", 2.07, !lowPass),
|
||
|
|
"HiSeq19" -> new Target("NA12878.hg19", hg19, dbSNP_b37_129, hapmap_b37, indelMask_b37,
|
||
|
|
new File("/humgen/gsa-hpprojects/NA12878Collection/bams/NA12878.HiSeq.WGS.bwa.cleaned.recal.hg19.bam"),
|
||
|
|
new File("/humgen/gsa-scr1/carneiro/prj/hiseq19/analysis/snps/NA12878.hg19.filtered.vcf"), // ** THIS GOLD STANDARD NEEDS TO BE CORRECTED **
|
||
|
|
"/humgen/1kg/processing/pipeline_test_bams/whole_genome_chunked.hg19.intervals", 2.3, !lowPass), // ** we need a chunked hg19 whole genome intervals file **
|
||
|
|
"FIN" -> new Target("FIN", b37, dbSNP_b37, hapmap_b37, indelMask_b37,
|
||
|
|
new File("/humgen/1kg/processing/pipeline_test_bams/FIN.79sample.Nov2010.chr20.bam"),
|
||
|
|
new File("/humgen/gsa-hpprojects/dev/data/AugChr20Calls_v4_3state/ALL.august.v4.chr20.filtered.vcf"), // ** THIS GOLD STANDARD NEEDS TO BE CORRECTED **
|
||
|
|
"/humgen/1kg/processing/pipeline_test_bams/whole_genome_chunked.chr20.hg19.intervals", 2.3, lowPass),
|
||
|
|
"WEx" -> new Target("NA12878.WEx", hg18, dbSNP_hg18, hapmap_hg18,
|
||
|
|
"/humgen/gsa-hpprojects/dev/depristo/oneOffProjects/1000GenomesProcessingPaper/wgs.v13/GA2.WEx.cleaned.indels.10.mask",
|
||
|
|
new File("/humgen/gsa-hpprojects/NA12878Collection/bams/NA12878.WEx.cleaned.recal.bam"),
|
||
|
|
new File("/home/radon01/depristo/work/oneOffProjects/1000GenomesProcessingPaper/wgs.v13/GA2.WEx.cleaned.ug.snpfiltered.indelfiltered.vcf"),
|
||
|
|
"/seq/references/HybSelOligos/whole_exome_agilent_1.1_refseq_plus_3_boosters/whole_exome_agilent_1.1_refseq_plus_3_boosters.targets.interval_list", 2.6, !lowPass),
|
||
|
|
"TGPWExGdA" -> new Target("1000G.WEx.GdA", b37, dbSNP_b37, hapmap_b37, indelMask_b37,
|
||
|
|
new File("/humgen/1kg/processing/pipeline_test_bams/Barcoded_1000G_WEx_Reduced_Plate_1.cleaned.list"), // BUGBUG: reduce from 60 to 20 people
|
||
|
|
new File("/humgen/gsa-scr1/delangel/NewUG/calls/AugustRelease.filtered_Q50_QD5.0_SB0.0.allSamples.SNPs_hg19.WEx_UG_newUG_MQC.vcf"), // ** THIS GOLD STANDARD NEEDS TO BE CORRECTED **
|
||
|
|
"/seq/references/HybSelOligos/whole_exome_agilent_1.1_refseq_plus_3_boosters/whole_exome_agilent_1.1_refseq_plus_3_boosters.Homo_sapiens_assembly19.targets.interval_list", 2.6, !lowPass),
|
||
|
|
"LowPassN60" -> new Target("lowpass.N60", b36, dbSNP_b36, hapmap_b36, indelMask_b36,
|
||
|
|
new File("/humgen/1kg/analysis/bamsForDataProcessingPapers/lowpass_b36/lowpass.chr20.cleaned.matefixed.bam"), // the bam list to call from
|
||
|
|
new File("/home/radon01/depristo/work/oneOffProjects/VQSRCutByNRS/lowpass.N60.chr20.filtered.vcf"), // the gold standard VCF file to run through the VQSR
|
||
|
|
"/humgen/1kg/processing/pipeline_test_bams/whole_genome_chunked.chr20.b36.intervals", 2.3, lowPass), // chunked interval list to use with Queue's scatter/gather functionality
|
||
|
|
"LowPassAugust" -> new Target("ALL.august.v4", b37, dbSNP_b37, hapmap_b37, indelMask_b37, // BUGBUG: kill this, it is too large
|
||
|
|
new File("/humgen/1kg/processing/allPopulations_chr20_august_release.cleaned.merged.bams/ALL.cleaned.merged.list"),
|
||
|
|
new File("/humgen/gsa-hpprojects/dev/data/AugChr20Calls_v4_3state/ALL.august.v4.chr20.filtered.vcf"),
|
||
|
|
"/humgen/1kg/processing/pipeline_test_bams/whole_genome_chunked.chr20.hg19.intervals", 2.3, lowPass),
|
||
|
|
"LowPassEUR363Nov" -> new Target("EUR.nov2010", b37, dbSNP_b37, hapmap_b37, indelMask_b37,
|
||
|
|
new File("/humgen/1kg/processing/pipeline_test_bams/EUR.363sample.Nov2010.chr20.bam"),
|
||
|
|
new File("/humgen/gsa-hpprojects/dev/data/AugChr20Calls_v4_3state/ALL.august.v4.chr20.filtered.vcf"), // ** THIS GOLD STANDARD NEEDS TO BE CORRECTED **
|
||
|
|
"/humgen/1kg/processing/pipeline_test_bams/whole_genome_chunked.chr20.hg19.intervals", 2.3, lowPass),
|
||
|
|
|
||
|
|
"WExTrio" -> new Target("CEUTrio.WEx", hg19, dbSNP_b37_129, hapmap_b37, indelMask_b37,
|
||
|
|
new File("/humgen/gsa-hpprojects/NA12878Collection/bams/CEUTrio.HiSeq.WEx.bwa.cleaned.recal.bam"),
|
||
|
|
new File("/humgen/gsa-scr1/carneiro/prj/trio/analysis/snps/CEUTrio.WEx.filtered.vcf"),
|
||
|
|
"/seq/references/HybSelOligos/whole_exome_agilent_1.1_refseq_plus_3_boosters/whole_exome_agilent_1.1_refseq_plus_3_boosters.Homo_sapiens_assembly19.targets.interval_list", 2.6, !lowPass)
|
||
|
|
)
|
||
|
|
|
||
|
|
|
||
|
|
def script = {
|
||
|
|
|
||
|
|
// Selects the datasets in the -dataset argument and adds them to targets.
|
||
|
|
var targets: List[Target] = List()
|
||
|
|
if (!datasets.isEmpty)
|
||
|
|
for (ds <- datasets)
|
||
|
|
targets ::= targetDataSets(ds) // Could check if ds was mispelled, but this way an exception will be thrown, maybe it's better this way?
|
||
|
|
else // If -dataset is not specified, all datasets are used.
|
||
|
|
for (targetDS <- targetDataSets.valuesIterator) // for Scala 2.7 or older, use targetDataSets.values
|
||
|
|
targets ::= targetDS
|
||
|
|
|
||
|
|
val goldStandard = true
|
||
|
|
for (target <- targets) {
|
||
|
|
if( !skipCalling ) {
|
||
|
|
add(new UnifiedGenotyper(target))
|
||
|
|
add(new VariantFiltration(target))
|
||
|
|
add(new GenerateVariantClusters(target, !goldStandard))
|
||
|
|
add(new VariantRecalibratorTiTv(target, !goldStandard))
|
||
|
|
add(new VariantRecalibratorNRS(target, !goldStandard))
|
||
|
|
if (!noCut) add (new VariantCut(target))
|
||
|
|
if (eval) add(new VariantEvaluation(target))
|
||
|
|
}
|
||
|
|
if ( !skipGoldStandard ) {
|
||
|
|
add(new GenerateVariantClusters(target, goldStandard))
|
||
|
|
add(new VariantRecalibratorTiTv(target, goldStandard))
|
||
|
|
add(new VariantRecalibratorNRS(target, goldStandard))
|
||
|
|
}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
def bai(bam: File) = new File(bam + ".bai")
|
||
|
|
|
||
|
|
val FiltersToIgnore = List("DPFilter", "ABFilter", "ESPStandard", "QualByDepth", "StrandBias", "HomopolymerRun")
|
||
|
|
|
||
|
|
// 1.) Call SNPs with UG
|
||
|
|
class UnifiedGenotyper(t: Target) extends org.broadinstitute.sting.queue.extensions.gatk.UnifiedGenotyper with UNIVERSAL_GATK_ARGS {
|
||
|
|
this.reference_sequence = t.reference
|
||
|
|
this.intervalsString ++= List(t.intervals)
|
||
|
|
this.scatterCount = 63 // the smallest interval list has 63 intervals, one for each Mb on chr20
|
||
|
|
this.dcov = Some( if ( t.isLowpass ) { 50 } else { 250 } )
|
||
|
|
this.stand_call_conf = Some( if ( t.isLowpass ) { 4.0 } else { 30.0 } )
|
||
|
|
this.stand_emit_conf = Some( if ( t.isLowpass ) { 4.0 } else { 30.0 } )
|
||
|
|
this.input_file :+= t.bamList
|
||
|
|
this.out = t.rawVCF
|
||
|
|
this.baq = Some( if (noBAQ) {org.broadinstitute.sting.utils.baq.BAQ.CalculationMode.OFF} else {org.broadinstitute.sting.utils.baq.BAQ.CalculationMode.RECALCULATE})
|
||
|
|
this.analysisName = t.name + "_UG"
|
||
|
|
if (t.dbsnpFile.endsWith(".rod"))
|
||
|
|
this.DBSNP = new File(t.dbsnpFile)
|
||
|
|
else if (t.dbsnpFile.endsWith(".vcf"))
|
||
|
|
this.rodBind :+= RodBind("dbsnp", "VCF", t.dbsnpFile)
|
||
|
|
}
|
||
|
|
|
||
|
|
// 2.) Filter SNPs
|
||
|
|
class VariantFiltration(t: Target) extends org.broadinstitute.sting.queue.extensions.gatk.VariantFiltration with UNIVERSAL_GATK_ARGS {
|
||
|
|
this.reference_sequence = t.reference
|
||
|
|
this.intervalsString ++= List(t.intervals)
|
||
|
|
this.scatterCount = 10
|
||
|
|
this.variantVCF = t.rawVCF
|
||
|
|
this.out = t.filteredVCF
|
||
|
|
this.filterName ++= List("HARD_TO_VALIDATE")
|
||
|
|
this.filterExpression ++= List("\"MQ0 >= 4 && (MQ0 / (1.0 * DP)) > 0.1\"")
|
||
|
|
this.analysisName = t.name + "_VF"
|
||
|
|
if (!noMASK) {
|
||
|
|
this.rodBind :+= RodBind("mask", "Bed", t.maskFile)
|
||
|
|
this.maskName = "InDel"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
// 3.) VQSR part1 Generate Gaussian clusters based on truth sites
|
||
|
|
class GenerateVariantClusters(t: Target, goldStandard: Boolean) extends org.broadinstitute.sting.queue.extensions.gatk.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", "/humgen/gsa-hpprojects/GATK/data/Comparisons/Unvalidated/1kg_pilot1_projectCalls/ALL.low_coverage.2010_07.hg19.vcf")
|
||
|
|
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.analysisName = name + "_GVC"
|
||
|
|
this.intervalsString ++= List(t.intervals)
|
||
|
|
this.qual = Some(350) // clustering parameters to be updated soon pending new experimentation results
|
||
|
|
this.std = Some(3.5)
|
||
|
|
this.mG = Some(10)
|
||
|
|
this.ignoreFilter ++= FiltersToIgnore
|
||
|
|
if (t.dbsnpFile.endsWith(".rod"))
|
||
|
|
this.DBSNP = new File(t.dbsnpFile)
|
||
|
|
else if (t.dbsnpFile.endsWith(".vcf"))
|
||
|
|
this.rodBind :+= RodBind("dbsnp", "VCF", t.dbsnpFile)
|
||
|
|
}
|
||
|
|
|
||
|
|
// 4.) VQSR part2 Calculate new LOD for all input SNPs by evaluating the Gaussian clusters
|
||
|
|
class VariantRecalibratorBase(t: Target, goldStandard: Boolean) extends org.broadinstitute.sting.queue.extensions.gatk.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", "/humgen/gsa-hpprojects/GATK/data/Comparisons/Unvalidated/1kg_pilot1_projectCalls/ALL.low_coverage.2010_07.hg19.vcf")
|
||
|
|
this.rodBind :+= RodBind("hapmap", "VCF", t.hapmapFile)
|
||
|
|
this.rodBind :+= RodBind("truth", "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")
|
||
|
|
this.target_titv = Some(t.titvTarget)
|
||
|
|
if (t.dbsnpFile.endsWith(".rod"))
|
||
|
|
this.DBSNP = new File(t.dbsnpFile)
|
||
|
|
else if (t.dbsnpFile.endsWith(".vcf"))
|
||
|
|
this.rodBind :+= RodBind("dbsnp", "VCF", t.dbsnpFile)
|
||
|
|
}
|
||
|
|
|
||
|
|
// 4a.) Choose VQSR tranches based on novel ti/tv
|
||
|
|
class VariantRecalibratorTiTv(t: Target, goldStandard: Boolean) extends VariantRecalibratorBase(t, goldStandard) {
|
||
|
|
this.tranche ++= List("0.1", "1.0", "10.0", "100.0")
|
||
|
|
this.out = t.titvRecalibratedVCF
|
||
|
|
this.tranchesFile = t.titvTranchesFile
|
||
|
|
}
|
||
|
|
|
||
|
|
// 4b.) Choose VQSR tranches based on sensitivity to truth set
|
||
|
|
class VariantRecalibratorNRS(t: Target, goldStandard: Boolean) extends VariantRecalibratorBase(t, goldStandard) {
|
||
|
|
this.sm = Some(org.broadinstitute.sting.gatk.walkers.variantrecalibration.VariantRecalibrator.SelectionMetricType.TRUTH_SENSITIVITY)
|
||
|
|
this.tranche ++= List("0.1", "1.0", "10.0", "100.0")
|
||
|
|
this.out = t.tsRecalibratedVCF
|
||
|
|
this.priorDBSNP = Some(2.0)
|
||
|
|
this.priorHapMap = Some(2.0)
|
||
|
|
this.prior1KG = Some(2.0)
|
||
|
|
this.tranchesFile = t.tsTranchesFile
|
||
|
|
}
|
||
|
|
|
||
|
|
// 5.) Variant Cut (OPTIONAL!) filter out the variants marked by recalibration to the 99% tranche
|
||
|
|
class VariantCut(t: Target) extends org.broadinstitute.sting.queue.extensions.gatk.ApplyVariantCuts with UNIVERSAL_GATK_ARGS {
|
||
|
|
this.reference_sequence = t.reference
|
||
|
|
this.rodBind :+= RodBind("input", "VCF", t.tsRecalibratedVCF )
|
||
|
|
this.analysisName = t.name + "_VC"
|
||
|
|
this.intervalsString ++= List(t.intervals)
|
||
|
|
this.out = t.cutVCF
|
||
|
|
this.tranchesFile = t.tsTranchesFile
|
||
|
|
this.fdr_filter_level = Some(1.0)
|
||
|
|
if (t.dbsnpFile.endsWith(".rod"))
|
||
|
|
this.DBSNP = new File(t.dbsnpFile)
|
||
|
|
else if (t.dbsnpFile.endsWith(".vcf"))
|
||
|
|
this.rodBind :+= RodBind("dbsnp", "VCF", t.dbsnpFile)
|
||
|
|
}
|
||
|
|
|
||
|
|
// 6.) Variant Evaluation (OPTIONAL!) based on the sensitivity recalibrated vcf
|
||
|
|
class VariantEvaluation(t: Target) extends org.broadinstitute.sting.queue.extensions.gatk.VariantEval with UNIVERSAL_GATK_ARGS {
|
||
|
|
val name: String = t.name
|
||
|
|
this.reference_sequence = t.reference
|
||
|
|
this.rodBind :+= RodBind("comphapmap", "VCF", t.hapmapFile)
|
||
|
|
this.rodBind :+= RodBind("eval", "VCF", if (!noCut) {t.cutVCF} else {t.tsRecalibratedVCF} )
|
||
|
|
this.analysisName = name + "_VE"
|
||
|
|
this.intervalsString ++= List(t.intervals)
|
||
|
|
this.EV ++= List("GenotypeConcordance")
|
||
|
|
this.out = t.evalFile
|
||
|
|
if (t.dbsnpFile.endsWith(".rod"))
|
||
|
|
this.DBSNP = new File(t.dbsnpFile)
|
||
|
|
else if (t.dbsnpFile.endsWith(".vcf"))
|
||
|
|
this.rodBind :+= RodBind("dbsnp", "VCF", t.dbsnpFile)
|
||
|
|
}
|
||
|
|
}
|