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Apply suggestions from code review
Co-authored-by: Moritz E. Beber <midnighter@posteo.net>
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2 changed files with 2 additions and 2 deletions
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@ -55,7 +55,7 @@ process {
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params.shortread_clipmerge_adapter1 ? "--adapter_sequence ${params.shortread_clipmerge_adapter1}" : "",
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// filtering options
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"--length_required ${params.shortread_clipmerge_minlength}",
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params.perform_shortread_complexityfilter && params.shortread_complexityfilter_tool == 'fastp' ? "--low_complexity_filter --complexity_threshold ${params.shortread_complexityfilter_fastp_threshold}" : ''
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(params.perform_shortread_complexityfilter && params.shortread_complexityfilter_tool == 'fastp') ? "--low_complexity_filter --complexity_threshold ${params.shortread_complexityfilter_fastp_threshold}" : ''
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].join(' ').trim()
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ext.prefix = { "${meta.id}_${meta.run_accession}" }
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publishDir = [
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@ -185,7 +185,7 @@ Complexity filtering is primarily a run-time optimisation step. It is not necess
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There are currently three options for short-read complexity filtering: [`bbduk`](https://jgi.doe.gov/data-and-tools/software-tools/bbtools/bb-tools-user-guide/bbduk-guide/), [`prinseq++`](https://github.com/Adrian-Cantu/PRINSEQ-plus-plus), and [`fastp`](https://github.com/OpenGene/fastp#low-complexity-filter).
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The tools offer different algorithms and parameters for removing low complexity reads. We therefore recommend reviewing the pipeline's [parameter documentation](https://nf-co.re/taxprofiler/parameters) and the documentation of both tools (see links above) to decide on optimal methods and parameters for your dataset.
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The tools offer different algorithms and parameters for removing low complexity reads. We therefore recommend reviewing the pipeline's [parameter documentation](https://nf-co.re/taxprofiler/parameters) and the documentation of the tools (see links above) to decide on optimal methods and parameters for your dataset.
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You can optionally save the FASTQ output of the run merging with the `--save_complexityfiltered_reads`. If running with `fastp`, complexity filtering happens inclusively within the earlier shortread preprocessing step. Therefore there will not be an independent pipeline step for complexity filtering, and no independent FASTQ file (i.e. `--save_complexityfiltered_reads` will be ignored) - your complexity filtered reads will also be in the `fastp/` folder in the same file(s) as the preprocessed read.
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