// // Run profiling // include { MALT_RUN } from '../../modules/nf-core/modules/malt/run/main' include { KRAKEN2_KRAKEN2 } from '../../modules/nf-core/modules/kraken2/kraken2/main' include { CENTRIFUGE_CENTRIFUGE } from '../../modules/nf-core/modules/centrifuge/centrifuge/main' include { METAPHLAN3 } from '../../modules/nf-core/modules/metaphlan3/main' include { KAIJU_KAIJU } from '../../modules/nf-core/modules/kaiju/kaiju/main' workflow PROFILING { take: reads // [ [ meta ], [ reads ] ] databases // [ [ meta ], path ] main: ch_versions = Channel.empty() ch_multiqc_files = Channel.empty() /* COMBINE READS WITH POSSIBLE DATABASES */ // e.g. output [DUMP: reads_plus_db] [['id':'2612', 'run_accession':'combined', 'instrument_platform':'ILLUMINA', 'single_end':1], /2612.merged.fastq.gz, ['tool':'malt', 'db_name':'mal95', 'db_params':'"-id 90"'], /malt90] ch_input_for_profiling = reads .map { meta, reads -> def meta_new = meta.clone() pairtype = meta_new['single_end'] ? '_se' : '_pe' meta_new['id'] = meta_new['id'] + pairtype [meta_new, reads] } .combine(databases) .branch { malt: it[2]['tool'] == 'malt' kraken2: it[2]['tool'] == 'kraken2' metaphlan3: it[2]['tool'] == 'metaphlan3' centrifuge: it[2]['tool'] == 'centrifuge' kaiju: it[2]['tool'] == 'kaiju' unknown: true } /* PREPARE PROFILER INPUT CHANNELS */ // Each tool as a slightly different input structure and generally separate // input channels for reads vs databases. We restructure the channel tuple // for each tool and make liberal use of multiMap to keep reads/databases // channel element order in sync with each other // MALT: We groupTuple to have all samples in one channel for MALT as database // loading takes a long time, so we only want to run it once per database // TODO document somewhere we only accept illumina short reads for MALT? ch_input_for_malt = ch_input_for_profiling.malt .filter { it[0]['instrument_platform'] == 'ILLUMINA' } .map { it -> def temp_meta = [ id: it[2]['db_name']] + it[2] def db = it[3] [ temp_meta, it[1], db ] } .groupTuple(by: [0,2]) .multiMap { it -> reads: [ it[0], it[1].flatten() ] db: it[2] } // All subsequent tools can easily run on a per-sample basis ch_input_for_kraken2 = ch_input_for_profiling.kraken2 .multiMap { it -> reads: [ it[0] + it[2], it[1] ] db: it[3] } ch_input_for_centrifuge = ch_input_for_profiling.centrifuge .multiMap { it -> reads: [ it[0] + it[2], it[1] ] db: it[3] } ch_input_for_metaphlan3 = ch_input_for_profiling.metaphlan3 .multiMap { it -> reads: [it[0] + it[2], it[1]] db: it[3] } ch_input_for_kaiju = ch_input_for_profiling.kaiju .multiMap { it -> reads: [it[0] + it[2], it[1]] db: it[3] } /* RUN PROFILING */ if ( params.run_malt ) { MALT_RUN ( ch_input_for_malt.reads, params.malt_mode, ch_input_for_malt.db ) ch_multiqc_files = ch_multiqc_files.mix( MALT_RUN.out.log.collect{it[1]}.ifEmpty([]) ) ch_versions = ch_versions.mix( MALT_RUN.out.versions.first() ) } if ( params.run_kraken2 ) { KRAKEN2_KRAKEN2 ( ch_input_for_kraken2.reads, ch_input_for_kraken2.db ) ch_multiqc_files = ch_multiqc_files.mix( KRAKEN2_KRAKEN2.out.txt.collect{it[1]}.ifEmpty([]) ) ch_versions = ch_versions.mix( KRAKEN2_KRAKEN2.out.versions.first() ) } if ( params.run_centrifuge ) { CENTRIFUGE_CENTRIFUGE ( ch_input_for_centrifuge.reads, ch_input_for_centrifuge.db, params.centrifuge_save_unaligned, params.centrifuge_save_aligned, params.centrifuge_sam_format ) ch_versions = ch_versions.mix( CENTRIFUGE_CENTRIFUGE.out.versions.first() ) } if ( params.run_metaphlan3 ) { METAPHLAN3 ( ch_input_for_metaphlan3.reads, ch_input_for_metaphlan3.db ) ch_versions = ch_versions.mix( METAPHLAN3.out.versions.first() ) } if ( params.run_kaiju ) { KAIJU_KAIJU ( ch_input_for_kaiju.reads, ch_input_for_kaiju.db ) ch_versions = ch_versions.mix( KAIJU_KAIJU.out.versions.first() ) } emit: // TODO work out if there is enough standardisation of output to export as one? //output = ch_filtered_reads // channel: [ val(meta), [ reads ] ] versions = ch_versions // channel: [ versions.yml ] mqc = ch_multiqc_files }