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Separate conditions, remove some left-over dumps

This commit is contained in:
James Fellows Yates 2023-01-24 13:20:58 +01:00
parent 0358489be0
commit 14826d5205
2 changed files with 6 additions and 5 deletions

View file

@ -40,7 +40,7 @@ workflow DB_CHECK {
}
//Filter the channel to run untar on DBs of tools actually using
ch_input_untar = ch_dbs_for_untar.untar.dump()
ch_input_untar = ch_dbs_for_untar.untar
.filter { params.run_kraken2 && it[0]['tool'] == 'kraken2' || params.run_centrifuge && it[0]['tool'] == 'centrifuge' || params.run_bracken && it[0]['tool'] == 'bracken' || params.run_kaiju && it[0]['tool'] == 'kaiju' || params.run_krakenuniq && it [0]['tool'] == 'krakenuniq' || params.run_malt && it[0]['tool'] == 'malt' || params.run_metaphlan3 && it[0]['tool'] == 'metaphlan3' }
UNTAR (ch_input_untar)
ch_versions = ch_versions.mix(UNTAR.out.versions.first())

View file

@ -202,8 +202,10 @@ workflow PROFILING {
ch_input_for_metaphlan3 = ch_input_for_profiling.metaphlan3
.filter{
if (it[0].is_fasta || it[0].instrument_platform == 'OXFORD_NANOPORE' ) log.warn "[nf-core/taxprofiler] MetaPhlAn3 currently does not accept FASTA files as input and/or has not been evaluated for Nanopore data. Skipping MetaPhlAn3 for sample ${it[0].id}."
!(it[0].is_fasta || it[0].instrument_platform == 'OXFORD_NANOPORE')
if (it[0].is_fasta) log.warn "[nf-core/taxprofiler] MetaPhlAn3 currently does not accept FASTA files as input. Skipping MetaPhlAn3 for sample ${it[0].id}."
!it[0].is_fasta
if (it[0].instrument_platform == 'OXFORD_NANOPORE') log.warn "[nf-core/taxprofiler] MetaPhlAn3 has not been evaluated for Nanopore data. Skipping MetaPhlAn3 for sample ${it[0].id}."
!it[0].instrument_platform == 'OXFORD_NANOPORE'
}
.multiMap {
it ->
@ -278,14 +280,13 @@ workflow PROFILING {
[[id: db_meta.db_name, single_end: meta.single_end], reads, db_meta, db]
}
.groupTuple(by: [0,2,3])
.dump(tag: "krakenuniq_premultimap")
.multiMap {
single_meta, reads, db_meta, db ->
reads: [ single_meta + db_meta, reads.flatten() ]
db: db
}
// Hardcode to _always_ produce the report file (which is our basic otput, and goes into)
KRAKENUNIQ_PRELOADEDKRAKENUNIQ ( ch_input_for_krakenuniq.reads.dump(tag: "krakenuniq_input"), ch_input_for_krakenuniq.db.dump(tag: "krakenuniq_db"), params.krakenuniq_ram_chunk_size, params.krakenuniq_save_reads, true, params.krakenuniq_save_readclassifications )
KRAKENUNIQ_PRELOADEDKRAKENUNIQ ( ch_input_for_krakenuniq.reads, ch_input_for_krakenuniq.db, params.krakenuniq_ram_chunk_size, params.krakenuniq_save_reads, true, params.krakenuniq_save_readclassifications )
ch_multiqc_files = ch_multiqc_files.mix( KRAKENUNIQ_PRELOADEDKRAKENUNIQ.out.report )
ch_versions = ch_versions.mix( KRAKENUNIQ_PRELOADEDKRAKENUNIQ.out.versions.first() )
ch_raw_classifications = ch_raw_classifications.mix( KRAKENUNIQ_PRELOADEDKRAKENUNIQ.out.classified_assignment )