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taxprofiler/subworkflows/local/shortread_adapterremoval.nf

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/*
Process short raw reads with AdapterRemoval
*/
include { ADAPTERREMOVAL as ADAPTERREMOVAL_SINGLE } from '../../modules/nf-core/modules/adapterremoval/main'
include { ADAPTERREMOVAL as ADAPTERREMOVAL_PAIRED } from '../../modules/nf-core/modules/adapterremoval/main'
include { CAT_FASTQ } from '../../modules/nf-core/modules/cat/fastq/main'
workflow SHORTREAD_ADAPTERREMOVAL {
take:
reads // [[meta], [reads]]
main:
ch_versions = Channel.empty()
ch_multiqc_files = Channel.empty()
ch_input_for_adapterremoval = reads
.branch{
single: it[0].single_end
paired: !it[0].single_end
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}
ADAPTERREMOVAL_SINGLE ( ch_input_for_adapterremoval.single, [] )
ADAPTERREMOVAL_PAIRED ( ch_input_for_adapterremoval.paired, [] )
// due to the slightly ugly output implementation of the current AdapterRemoval2 version, each file
// has to be exported in a separate channel, and we must manually recombine when necessary
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if ( params.shortread_clipmerge_mergepairs && !params.shortread_clipmerge_excludeunmerged ) {
ch_adapterremoval_for_cat = ADAPTERREMOVAL_PAIRED.out.collapsed
.mix(
ADAPTERREMOVAL_PAIRED.out.collapsed_truncated,
ADAPTERREMOVAL_PAIRED.out.singles_truncated,
ADAPTERREMOVAL_PAIRED.out.pair1_truncated,
ADAPTERREMOVAL_PAIRED.out.pair2_truncated
)
.map {
meta, reads ->
def meta_new = meta.clone()
meta_new.single_end = true
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[ meta_new, reads ]
}
.groupTuple()
ch_adapterremoval_reads_prepped = CAT_FASTQ ( ch_adapterremoval_for_cat ).reads
.mix( ADAPTERREMOVAL_SINGLE.out.singles_truncated )
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} else if ( params.shortread_clipmerge_mergepairs && params.shortread_clipmerge_excludeunmerged ) {
ch_adapterremoval_for_cat = ADAPTERREMOVAL_PAIRED.out.collapsed
.mix( ADAPTERREMOVAL_PAIRED.out.collapsed_truncated )
.map {
meta, reads ->
def meta_new = meta.clone()
meta_new['single_end'] = true
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[ meta_new, reads ]
}
.groupTuple(by: 0)
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ch_adapterremoval_reads_prepped = CAT_FASTQ ( ch_adapterremoval_for_cat ).reads
.mix( ADAPTERREMOVAL_SINGLE.out.singles_truncated )
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} else {
ch_adapterremoval_reads_prepped = ADAPTERREMOVAL_PAIRED.out.pair1_truncated
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.join( ADAPTERREMOVAL_PAIRED.out.pair2_truncated )
.groupTuple()
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.map { meta, pair1, pair2 ->
[ meta, [ pair1, pair2 ].flatten() ]
}
.mix( ADAPTERREMOVAL_SINGLE.out.singles_truncated )
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}
ch_processed_reads = ch_adapterremoval_reads_prepped
ch_versions = ch_versions.mix( ADAPTERREMOVAL_SINGLE.out.versions.first() )
ch_versions = ch_versions.mix( ADAPTERREMOVAL_PAIRED.out.versions.first() )
ch_multiqc_files = ch_multiqc_files.mix( ADAPTERREMOVAL_PAIRED.out.log.collect{it[1]}, ADAPTERREMOVAL_SINGLE.out.log.collect{it[1]} )
emit:
reads = ch_processed_reads // channel: [ val(meta), [ reads ] ]
versions = ch_versions // channel: [ versions.yml ]
mqc = ch_multiqc_files
}