Skip to content

Commit

Permalink
Merge pull request #818 from mskcc/develop
Browse files Browse the repository at this point in the history 
Release/1.3.3
  • Loading branch information
@gongyixiao
gongyixiao authored Aug 5, 2020
2 parents cd57ffc + 3f30bde commit eaaebed
Showing 1 changed file with 64 additions and 81 deletions.
145 changes: 64 additions & 81 deletions pipeline.nf
View file
Original file line number Diff line number Diff line change
Expand Up @@ -2931,26 +2931,26 @@ if ( !params.mapping && !params.bamMapping ){
.set {aggregateList}
inputSomaticAggregateMaf = aggregateList.finalMaf4Aggregate.transpose().groupTuple(by:[2])
inputSomaticAggregateNetMHC = aggregateList.NetMhcStats4Aggregate.transpose().groupTuple(by:[2])
inputPurity4Aggregate = aggregateList.FacetsPurity4Aggregate.transpose().groupTuple(by:[2])
inputHisens4Aggregate = aggregateList.FacetsHisens4Aggregate.transpose().groupTuple(by:[2])
inputOutLog4Aggregate = aggregateList.FacetsOutLog4Aggregate.transpose().groupTuple(by:[2])
inputArmLev4Aggregate = aggregateList.FacetsArmLev4Aggregate.transpose().groupTuple(by:[2])
inputGeneLev4Aggregate = aggregateList.FacetsGeneLev4Aggregate.transpose().groupTuple(by:[2])
inputFacetsQC4CohortMultiQC = aggregateList.FacetsQC4Aggregate.transpose().groupTuple(by:[2])
inputSomaticAggregateSv = aggregateList.dellyMantaCombined4Aggregate.transpose().groupTuple(by:[2])
inputSomaticAggregateSvTbi = aggregateList.dellyMantaCombinedTbi4Aggregate.transpose().groupTuple(by:[2])
inputPredictHLA4Aggregate = aggregateList.predictHLA4Aggregate.transpose().groupTuple(by:[2])
inputIntCPN4Aggregate = aggregateList.intCPN4Aggregate.transpose().groupTuple(by:[2])
inputPurity4Aggregate = aggregateList.FacetsPurity4Aggregate.transpose().groupTuple(by:[2]).map{[it[2], it[4]]}
inputHisens4Aggregate = aggregateList.FacetsHisens4Aggregate.transpose().groupTuple(by:[2]).map{[it[2], it[4]]}
inputOutLog4Aggregate = aggregateList.FacetsOutLog4Aggregate.transpose().groupTuple(by:[2]).map{[it[2], it[4]]}
inputArmLev4Aggregate = aggregateList.FacetsArmLev4Aggregate.transpose().groupTuple(by:[2]).map{[it[2], it[4]]}
inputGeneLev4Aggregate = aggregateList.FacetsGeneLev4Aggregate.transpose().groupTuple(by:[2]).map{[it[2], it[4]]}
inputFacetsQC4CohortMultiQC = aggregateList.FacetsQC4Aggregate.transpose().groupTuple(by:[2]).map{[it[2], it[4], it[5]]}
inputSomaticAggregateSv = aggregateList.dellyMantaCombined4Aggregate.transpose().groupTuple(by:[2]).map{[it[2], it[4]]}
inputSomaticAggregateSvTbi = aggregateList.dellyMantaCombinedTbi4Aggregate.transpose().groupTuple(by:[2]).map{[it[2], it[4]]}
inputPredictHLA4Aggregate = aggregateList.predictHLA4Aggregate.transpose().groupTuple(by:[2]).map{[it[2], it[4]]}
inputIntCPN4Aggregate = aggregateList.intCPN4Aggregate.transpose().groupTuple(by:[2]).map{[it[2], it[4]]}
inputSomaticAggregateMetadata = aggregateList.MetaData4Aggregate.transpose().groupTuple(by:[2])
inputGermlineAggregateMaf = aggregateList.mafFile4AggregateGermline.transpose().groupTuple(by:[2])
inputGermlineAggregateSv = aggregateList.dellyMantaCombined4AggregateGermline.transpose().groupTuple(by:[1]).map{ [it[0].unique(), it[1], it[5].unique()]}
inputGermlineAggregateSvTbi = aggregateList.dellyMantaCombinedTbi4AggregateGermline.transpose().groupTuple(by:[1]).map{ [it[0].unique(), it[1], it[5].unique()]}
inputAlfredIgnoreY = aggregateList.alfredIgnoreYTumor.unique().combine(aggregateList.alfredIgnoreYNormal.unique(), by:[0,1,2]).transpose().groupTuple(by:[0]).map{ [it[0], it[1], it[2], it[3].unique(), it[4].unique()]}
inputAlfredIgnoreN = aggregateList.alfredIgnoreNTumor.unique().combine(aggregateList.alfredIgnoreNNormal.unique(), by:[0,1,2]).transpose().groupTuple(by:[0]).map{ [it[0], it[1], it[2], it[3].unique(), it[4].unique()]}
inputHsMetrics = aggregateList.hsMetricsTumor.unique().combine(aggregateList.hsMetricsNormal.unique(), by:[0,1,2]).transpose().groupTuple(by:[0]).map{ [it[0], it[1], it[2], it[3].unique(), it[4].unique()]}
aggregateList.conpairConcord4Aggregate.transpose().groupTuple(by:[2]).into{inputConpairConcord4Aggregate; inputConpairConcord4MultiQC}
aggregateList.conpairContami4Aggregate.transpose().groupTuple(by:[2]).into{inputConpairContami4Aggregate; inputConpairContami4MultiQC}
aggregateList.fastpTumor.unique().combine(aggregateList.fastpNormal.unique(), by:[0,1,2]).transpose().groupTuple(by:[0]).map{ [it[0], it[1], it[2], it[3].unique(), it[4].unique()]}.set{inputFastP4MultiQC}
inputGermlineAggregateSv = aggregateList.dellyMantaCombined4AggregateGermline.transpose().groupTuple(by:[1]).map{[it[1], it[5].unique()]}
inputGermlineAggregateSvTbi = aggregateList.dellyMantaCombinedTbi4AggregateGermline.transpose().groupTuple(by:[1]).map{[it[1], it[5].unique()]}
inputAlfredIgnoreY = aggregateList.alfredIgnoreYTumor.unique().combine(aggregateList.alfredIgnoreYNormal.unique(), by:[0,1,2]).transpose().groupTuple(by:[0]).map{ [it[0], it[3].unique(), it[4].unique()]}
inputAlfredIgnoreN = aggregateList.alfredIgnoreNTumor.unique().combine(aggregateList.alfredIgnoreNNormal.unique(), by:[0,1,2]).transpose().groupTuple(by:[0]).map{ [it[0], it[3].unique(), it[4].unique()]}
inputHsMetrics = aggregateList.hsMetricsTumor.unique().combine(aggregateList.hsMetricsNormal.unique(), by:[0,1,2]).transpose().groupTuple(by:[0]).map{ [it[0], it[3].unique(), it[4].unique()]}
aggregateList.conpairConcord4Aggregate.transpose().groupTuple(by:[2]).map{[it[2], it[4]]}.into{inputConpairConcord4Aggregate; inputConpairConcord4MultiQC}
aggregateList.conpairContami4Aggregate.transpose().groupTuple(by:[2]).map{[it[2], it[4]]}.into{inputConpairContami4Aggregate; inputConpairContami4MultiQC}
aggregateList.fastpTumor.unique().combine(aggregateList.fastpNormal.unique(), by:[0,1,2]).transpose().groupTuple(by:[0]).map{ [it[0], it[3].unique(), it[4].unique()]}.set{inputFastP4MultiQC}

}
else if(!(runAggregate == false)) {
Expand Down Expand Up @@ -3001,22 +3001,22 @@ else if(!(runAggregate == false)) {
if (runSomatic){
inputSomaticAggregateMaf = cohortSomaticAggregateMaf.combine(finalMaf4Aggregate, by:[1,2]).groupTuple(by:[2])
inputSomaticAggregateNetMHC = cohortSomaticAggregateNetMHC.combine(NetMhcStats4Aggregate, by:[1,2]).groupTuple(by:[2])
inputPurity4Aggregate = cohortSomaticAggregateFacets.combine(FacetsPurity4Aggregate, by:[1,2]).groupTuple(by:[2])
inputHisens4Aggregate = cohortSomaticAggregateFacets1.combine(FacetsHisens4Aggregate, by:[1,2]).groupTuple(by:[2])
inputOutLog4Aggregate = cohortSomaticAggregateFacets2.combine(FacetsOutLog4Aggregate, by:[1,2]).groupTuple(by:[2])
inputArmLev4Aggregate = cohortSomaticAggregateFacets3.combine(FacetsArmLev4Aggregate, by:[1,2]).groupTuple(by:[2])
inputGeneLev4Aggregate = cohortSomaticAggregateFacets4.combine(FacetsGeneLev4Aggregate, by:[1,2]).groupTuple(by:[2])
inputFacetsQC4CohortMultiQC = cohortSomaticAggregateFacets5.combine(FacetsQC4Aggregate,by:[1,2]).groupTuple(by:[2])
inputSomaticAggregateSv = cohortSomaticAggregateSv.combine(dellyMantaCombined4Aggregate, by:[1,2]).groupTuple(by:[2])
inputSomaticAggregateSvTbi = cohortSomaticAggregateSv1.combine(dellyMantaCombinedTbi4Aggregate, by:[1,2]).groupTuple(by:[2])
inputPredictHLA4Aggregate = cohortSomaticAggregateLOHHLA.combine(predictHLA4Aggregate, by:[1,2]).groupTuple(by:[2])
inputIntCPN4Aggregate = cohortSomaticAggregateLOHHLA1.combine(intCPN4Aggregate, by:[1,2]).groupTuple(by:[2])
inputPurity4Aggregate = cohortSomaticAggregateFacets.combine(FacetsPurity4Aggregate, by:[1,2]).groupTuple(by:[2]).map{[it[2], it[4]]}
inputHisens4Aggregate = cohortSomaticAggregateFacets1.combine(FacetsHisens4Aggregate, by:[1,2]).groupTuple(by:[2]).map{[it[2], it[4]]}
inputOutLog4Aggregate = cohortSomaticAggregateFacets2.combine(FacetsOutLog4Aggregate, by:[1,2]).groupTuple(by:[2]).map{[it[2], it[4]]}
inputArmLev4Aggregate = cohortSomaticAggregateFacets3.combine(FacetsArmLev4Aggregate, by:[1,2]).groupTuple(by:[2]).map{[it[2], it[4]]}
inputGeneLev4Aggregate = cohortSomaticAggregateFacets4.combine(FacetsGeneLev4Aggregate, by:[1,2]).groupTuple(by:[2]).map{[it[2], it[4]]}
inputFacetsQC4CohortMultiQC = cohortSomaticAggregateFacets5.combine(FacetsQC4Aggregate,by:[1,2]).groupTuple(by:[2]).map{[it[2], it[4], it[5]]}
inputSomaticAggregateSv = cohortSomaticAggregateSv.combine(dellyMantaCombined4Aggregate, by:[1,2]).groupTuple(by:[2]).map{[it[2], it[4]]}
inputSomaticAggregateSvTbi = cohortSomaticAggregateSv1.combine(dellyMantaCombinedTbi4Aggregate, by:[1,2]).groupTuple(by:[2]).map{[it[2], it[4]]}
inputPredictHLA4Aggregate = cohortSomaticAggregateLOHHLA.combine(predictHLA4Aggregate, by:[1,2]).groupTuple(by:[2]).map{[it[2], it[4]]}
inputIntCPN4Aggregate = cohortSomaticAggregateLOHHLA1.combine(intCPN4Aggregate, by:[1,2]).groupTuple(by:[2]).map{[it[2], it[4]]}
inputSomaticAggregateMetadata = cohortSomaticAggregateMetadata.combine(MetaData4Aggregate, by:[1,2]).groupTuple(by:[2])

if (runGermline){
inputGermlineAggregateMaf = cohortGermlineAggregateMaf.combine(mafFile4AggregateGermline, by:[1,2]).groupTuple(by:[2])
inputGermlineAggregateSv = cohortGermlineAggregateSv.combine(dellyMantaCombined4AggregateGermline, by:[2]).groupTuple(by:[1]).map{ [it[0].unique(), it[1], it[5].unique()]}
inputGermlineAggregateSvTbi = cohortGermlineAggregateSv1.combine(dellyMantaCombinedTbi4AggregateGermline, by:[2]).groupTuple(by:[1]).map{ [it[0].unique(), it[1], it[5].unique()]}
inputGermlineAggregateSv = cohortGermlineAggregateSv.combine(dellyMantaCombined4AggregateGermline, by:[2]).groupTuple(by:[1]).map{[it[1], it[5].unique()]}
inputGermlineAggregateSvTbi = cohortGermlineAggregateSv1.combine(dellyMantaCombinedTbi4AggregateGermline, by:[2]).groupTuple(by:[1]).map{[it[1], it[5].unique()]}
}
}

Expand Down Expand Up @@ -3053,7 +3053,7 @@ else if(!(runAggregate == false)) {
def fileTumor = item[3].unique()
def fileNormal = item[4].unique()

[cohort, idTumors, idNormals, fileTumor, fileNormal]
[cohort, fileTumor, fileNormal]
}
.unique()
.set{alfredIgnoreY}
Expand All @@ -3080,7 +3080,7 @@ else if(!(runAggregate == false)) {
def fileTumor = item[3].unique()
def fileNormal = item[4].unique()

[cohort, idTumors, idNormals, fileTumor, fileNormal]
[cohort, fileTumor, fileNormal]
}
.unique()
.set{alfredIgnoreN}
Expand Down Expand Up @@ -3108,7 +3108,7 @@ else if(!(runAggregate == false)) {
def fileTumor = item[3].unique()
def fileNormal = item[4].unique()

[cohort, idTumors, idNormals, fileTumor, fileNormal]
[cohort, fileTumor, fileNormal]
}
.unique()
.set{hsMetrics}
Expand All @@ -3134,7 +3134,7 @@ else if(!(runAggregate == false)) {
def fileTumor = item[3].flatten().unique()
def fileNormal = item[4].flatten().unique()

[cohort, idTumors, idNormals, fileTumor, fileNormal]
[cohort, fileTumor, fileNormal]
}
.unique()
.set{fastPMetrics}
Expand All @@ -3143,8 +3143,8 @@ else if(!(runAggregate == false)) {
inputHsMetrics = hsMetrics
inputFastP4MultiQC = fastPMetrics
if (pairingQc){
cohortQcConpairAggregate.combine(conpairConcord4Aggregate, by:[1,2]).groupTuple(by:[2]).into{inputConpairConcord4Aggregate; inputConpairConcord4MultiQC}
cohortQcConpairAggregate1.combine(conpairContami4Aggregate, by:[1,2]).groupTuple(by:[2]).into{inputConpairContami4Aggregate; inputConpairContami4MultiQC}
cohortQcConpairAggregate.combine(conpairConcord4Aggregate, by:[1,2]).groupTuple(by:[2]).map{[it[2], it[4]]}.into{inputConpairConcord4Aggregate; inputConpairConcord4MultiQC}
cohortQcConpairAggregate1.combine(conpairContami4Aggregate, by:[1,2]).groupTuple(by:[2]).map{[it[2], it[4]]}.into{inputConpairContami4Aggregate; inputConpairContami4MultiQC}
}
}
}
Expand Down Expand Up @@ -3209,18 +3209,20 @@ process SomaticAggregateNetMHC {
"""
}

inputPurity4Aggregate.join(inputHisens4Aggregate, by:[0])
.join(inputOutLog4Aggregate, by:[0])
.join(inputArmLev4Aggregate, by:[0])
.join(inputGeneLev4Aggregate, by:[0])
.set{inputSomaticAggregateFacets}

process SomaticAggregateFacets {

tag {cohort}

publishDir "${params.outDir}/cohort_level/${cohort}", mode: params.publishDirMode

input:
set idTumors, idNormals, cohort, placeHolder, file(purity) from inputPurity4Aggregate
set idTumors, idNormals, cohort, placeHolder, file(Hisens) from inputHisens4Aggregate
set idTumors, idNormals, cohort, placeHolder, file(outLog) from inputOutLog4Aggregate
set idTumors, idNormals, cohort, placeHolder, file(armLev) from inputArmLev4Aggregate
set idTumors, idNormals, cohort, placeHolder, file(geneLev) from inputGeneLev4Aggregate
set cohort, file(purity), file(Hisens), file(outLog), file(armLev), file(geneLev) from inputSomaticAggregateFacets

output:
set file("cna_hisens_run_segmentation.seg"), file("cna_purity_run_segmentation.seg"), file("cna_armlevel.txt"), file("cna_genelevel.txt"), file("cna_facets_run_info.txt") into FacetsAnnotationAggregatedOutput
Expand All @@ -3246,15 +3248,17 @@ process SomaticAggregateFacets {
"""
}

inputSomaticAggregateSv.join(inputSomaticAggregateSvTbi)
.set{inputSomaticAggregateSv}

process SomaticAggregateSv {

tag {cohort}

publishDir "${params.outDir}/cohort_level/${cohort}", mode: params.publishDirMode

input:
set idTumors, idNormals, cohort, placeHolder, file(dellyMantaVcf) from inputSomaticAggregateSv
set idTumors, idNormals, cohort, placeHolder, file(dellyMantaVcfTbi) from inputSomaticAggregateSvTbi
set cohort, file(dellyMantaVcf), file(dellyMantaVcfTbi) from inputSomaticAggregateSv

output:
file("sv_somatic.vcf.{gz,gz.tbi}") into svAggregatedOutput
Expand Down Expand Up @@ -3287,15 +3291,17 @@ process SomaticAggregateSv {
"""
}

inputPredictHLA4Aggregate.join(inputIntCPN4Aggregate)
.set{inputSomaticAggregateLOHHLA}

process SomaticAggregateLOHHLA {

tag {cohort}

publishDir "${params.outDir}/cohort_level/${cohort}", mode: params.publishDirMode

input:
set idTumors, idNormals, cohort, placeHolder, file(preditHLA) from inputPredictHLA4Aggregate
set idTumors, idNormals, cohort, placeHolder, file(intCPN) from inputIntCPN4Aggregate
set cohort, file(preditHLA), file(intCPN) from inputSomaticAggregateLOHHLA

output:
file("DNA.IntegerCPN_CI.txt") into lohhlaDNAIntegerCPNOutput
Expand Down Expand Up @@ -3380,15 +3386,17 @@ process GermlineAggregateMaf {
}

// --- Aggregate per-sample germline data, SVs
inputGermlineAggregateSv.join(inputGermlineAggregateSvTbi)
.set{inputGermlineAggregateSv}

process GermlineAggregateSv {

tag {cohort}

publishDir "${params.outDir}/cohort_level/${cohort}", mode: params.publishDirMode

input:
set idNormals, cohort, file(dellyMantaVcf) from inputGermlineAggregateSv
set idNormals, cohort, file(dellyMantaVcfTbi) from inputGermlineAggregateSvTbi
set cohort, file(dellyMantaVcf), file(dellyMantaVcfTbi) from inputGermlineAggregateSv

output:
file("sv_germline.vcf.{gz,gz.tbi}") into svAggregatedGermlineOutput
Expand Down Expand Up @@ -3429,16 +3437,18 @@ inputHsMetrics.into{inputHsMetrics; inputHsMetrics4MultiQC}
inputAlfredIgnoreY.into{inputAlfredIgnoreY; inputAlfredIgnoreY4MultiQC }
inputAlfredIgnoreN.into{inputAlfredIgnoreN; inputAlfredIgnoreN4MultiQC }

inputAlfredIgnoreY.join(inputAlfredIgnoreN)
.join(inputHsMetrics)
.set{inputQcBamAggregate}

process QcBamAggregate {

tag {cohort}

publishDir "${params.outDir}/cohort_level/${cohort}", mode: params.publishDirMode

input:
set cohort, idTumors, idNormals, file(alfredIgnoreYTumor), file(alfredIgnoreYNoraml) from inputAlfredIgnoreY
set cohort, idTumors, idNormals, file(alfredIgnoreNTumor), file(alfredIgnoreNNoraml) from inputAlfredIgnoreN
set cohort, idTumors, idNormals, file(hsMetricsTumor), file(hsMetricsNoraml) from inputHsMetrics
set cohort, file(alfredIgnoreYTumor), file(alfredIgnoreYNoraml), file(alfredIgnoreNTumor), file(alfredIgnoreNNoraml), file(hsMetricsTumor), file(hsMetricsNoraml) from inputQcBamAggregate

output:
file('alignment_qc.txt') into alignmentQcAggregatedOutput
Expand All @@ -3459,15 +3469,17 @@ process QcBamAggregate {

if (pairingQc){

inputConpairConcord4Aggregate.join(inputConpairContami4Aggregate)
.set{inputQcConpairAggregate}

process QcConpairAggregate {

tag {cohort}

publishDir "${params.outDir}/cohort_level/${cohort}", mode: params.publishDirMode

input:
set idTumors, idNormals, cohort, placeHolder, file(concordFile) from inputConpairConcord4Aggregate
set idTumors, idNormals, cohort, placeHolder, file(contamiFile) from inputConpairContami4Aggregate
set cohort, file(concordFile), file(contamiFile) from inputQcConpairAggregate

output:
set file('concordance_qc.txt'), file('contamination_qc.txt') into conpairAggregatedOutput
Expand All @@ -3489,35 +3501,6 @@ process QcConpairAggregate {
}


inputHsMetrics4MultiQC
.map{cohort, idTumors, idNormals, hsMetricsTumor, hsMetricsNormal ->
[cohort, hsMetricsTumor, hsMetricsNormal]
}.set{inputHsMetrics4MultiQC}
inputFastP4MultiQC
.map{ cohort, idTumors, idNormals, fastPTumor, fastPNormal ->
[cohort, fastPTumor, fastPNormal]
}.set{inputFastP4MultiQC}
inputAlfredIgnoreY4MultiQC
.map{ cohort, idTumors, idNormals, alfredIgnoreYTumor, alfredIgnoreYNormal ->
[cohort, alfredIgnoreYTumor, alfredIgnoreYNormal ]
}.set{inputAlfredIgnoreY4MultiQC}
inputAlfredIgnoreN4MultiQC
.map{ cohort, idTumors, idNormals, alfredIgnoreNTumor, alfredIgnoreNNormal ->
[cohort, alfredIgnoreNTumor, alfredIgnoreNNormal ]
}.set{inputAlfredIgnoreN4MultiQC}
inputConpairConcord4MultiQC
.map{ idTumors, idNormals, cohort, placeHolder, concordFile ->
[cohort, concordFile]
}.set{inputConpairConcord4MultiQC}
inputConpairContami4MultiQC
.map{ idTumors, idNormals, cohort, placeHolder, contamiFile ->
[cohort, contamiFile]
}.set{inputConpairContami4MultiQC}
inputFacetsQC4CohortMultiQC
.map{ idTumors, idNormals, cohort, placeHolder, qcFile, summaryFile ->
[cohort, qcFile, summaryFile]
}.set{inputFacetsQC4CohortMultiQC}

inputHsMetrics4MultiQC
.join(inputFastP4MultiQC,by:0)
.join(inputAlfredIgnoreY4MultiQC,by:0)
Expand Down

0 comments on commit eaaebed

Please sign in to comment.