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Fix merge conflicts
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CHANGELOG.md

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@@ -10,6 +10,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
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- Bump minimum Nextflow version from `21.10.3` -> `22.10.1`
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- Updated pipeline template to [nf-core/tools 2.7.2](https://github.com/nf-core/tools/releases/tag/2.7.2)
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- [[#729](https://github.com/nf-core/rnaseq/issues/729)] - Add 'auto' option to samplesheet to automatically detect strandedness for samples
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- [[#891](https://github.com/nf-core/rnaseq/issues/891)] - Skip MarkDuplicates when UMIs are used
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- [[#896](https://github.com/nf-core/rnaseq/issues/896)] - Remove `copyTo` call for iGenomes README
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- [[#897](https://github.com/nf-core/rnaseq/issues/897)] - Use `--skip_preseq` by default
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- [[#900](https://github.com/nf-core/rnaseq/issues/900)] - Add `--recursive` option to `fastq_dir_to_samplesheet.py` script

conf/modules.config

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@@ -358,7 +358,7 @@ if (!params.skip_alignment) {
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}
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}
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if (!params.skip_markduplicates) {
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if (!params.skip_markduplicates && !params.with_umi) {
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process {
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withName: '.*:BAM_MARKDUPLICATES_PICARD:PICARD_MARKDUPLICATES' {
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ext.args = '--ASSUME_SORTED true --REMOVE_DUPLICATES false --VALIDATION_STRINGENCY LENIENT --TMP_DIR tmp'
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pattern: '*.bam',
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enabled: (
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params.save_align_intermeds ||
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params.skip_markduplicates ||
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params.with_umi ||
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params.save_umi_intermeds
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)
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]
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pattern: '*.{bai,csi}',
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enabled: (
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params.save_align_intermeds ||
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params.skip_markduplicates ||
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params.with_umi ||
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params.save_umi_intermeds
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)
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]

docs/output.md

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@@ -292,7 +292,7 @@ After extracting the UMI information from the read sequence (see [UMI-tools extr
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</details>
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Unless you are using [UMIs](https://emea.illumina.com/science/sequencing-method-explorer/kits-and-arrays/umi.html) it is not possible to establish whether the fragments you have sequenced from your sample were derived via true biological duplication (i.e. sequencing independent template fragments) or as a result of PCR biases introduced during the library preparation. By default, the pipeline uses [picard MarkDuplicates](https://broadinstitute.github.io/picard/command-line-overview.html#MarkDuplicates) to _mark_ the duplicate reads identified amongst the alignments to allow you to guage the overall level of duplication in your samples. However, for RNA-seq data it is not recommended to physically remove duplicate reads from the alignments (unless you are using UMIs) because you expect a significant level of true biological duplication that arises from the same fragments being sequenced from for example highly expressed genes. You can skip this step via the `--skip_markduplicates` parameter.
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Unless you are using [UMIs](https://emea.illumina.com/science/sequencing-method-explorer/kits-and-arrays/umi.html) it is not possible to establish whether the fragments you have sequenced from your sample were derived via true biological duplication (i.e. sequencing independent template fragments) or as a result of PCR biases introduced during the library preparation. By default, the pipeline uses [picard MarkDuplicates](https://broadinstitute.github.io/picard/command-line-overview.html#MarkDuplicates) to _mark_ the duplicate reads identified amongst the alignments to allow you to guage the overall level of duplication in your samples. However, for RNA-seq data it is not recommended to physically remove duplicate reads from the alignments (unless you are using UMIs) because you expect a significant level of true biological duplication that arises from the same fragments being sequenced from for example highly expressed genes. This step will be skipped automatically when using the `--with_umi` option or explicitly via the `--skip_markduplicates` parameter.
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![MultiQC - Picard MarkDuplicates metrics plot](images/mqc_picard_markduplicates.png)
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workflows/rnaseq.nf

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@@ -591,7 +591,7 @@ workflow RNASEQ {
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// SUBWORKFLOW: Mark duplicate reads
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//
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ch_markduplicates_multiqc = Channel.empty()
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if (!params.skip_alignment && !params.skip_markduplicates) {
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if (!params.skip_alignment && !params.skip_markduplicates && !params.with_umi) {
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BAM_MARKDUPLICATES_PICARD (
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ch_genome_bam,
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PREPARE_GENOME.out.fasta,

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