use subworkflows/local/bam_bedgraph_bigwig_bedtools_ucsc from nf-core…

…/atacseq

subworkflows/local/bam_bedgraph_bigwig_bedtools_ucsc.nf

@@ -0,0 +1,42 @@
+
+//
+// Convert BAM to normalised bigWig via bedGraph using BEDTools and UCSC
+//
+
+include { BEDTOOLS_GENOMECOV    } from '../../modules/local/bedtools_genomecov'
+include { UCSC_BEDGRAPHTOBIGWIG } from '../../modules/nf-core/ucsc/bedgraphtobigwig/main'
+
+workflow BAM_BEDGRAPH_BIGWIG_BEDTOOLS_UCSC {
+    take:
+    ch_bam_flagstat // channel: [ val(meta), [bam], [flagstat] ]
+    ch_chrom_sizes  // channel: [ bed ]
+
+    main:
+
+    ch_versions = Channel.empty()
+
+    //
+    // Create bedGraph coverage track
+    //
+    BEDTOOLS_GENOMECOV (
+        ch_bam_flagstat
+    )
+    ch_versions = ch_versions.mix(BEDTOOLS_GENOMECOV.out.versions.first())
+
+    //
+    // Create bigWig coverage tracks
+    //
+    UCSC_BEDGRAPHTOBIGWIG (
+        BEDTOOLS_GENOMECOV.out.bedgraph,
+        ch_chrom_sizes
+    )
+    ch_versions = ch_versions.mix(UCSC_BEDGRAPHTOBIGWIG.out.versions.first())
+
+    emit:
+    bedgraph     = BEDTOOLS_GENOMECOV.out.bedgraph      // channel: [ val(meta), [ bedgraph ] ]
+    scale_factor = BEDTOOLS_GENOMECOV.out.scale_factor  // channel: [ val(meta), [ txt ] ]
+
+    bigwig       = UCSC_BEDGRAPHTOBIGWIG.out.bigwig     // channel: [ val(meta), [ bigwig ] ]
+
+    versions     = ch_versions                          // channel: [ versions.yml ]
+}