Nextflow Registry | nf-core/deseq2/differential@0.0.0-6c4ed3a

nf-core/deseq2/differential @ 0.0.0-6c4ed3a

runs a differential expression analysis with DESeq2

differential expression rna-seq deseq2

Latest version: 0.0.0-6c4ed3a

Total downloads: 7

Source: nf-core/modules

Authors: @pinin4fjords

Maintainers: @pinin4fjords

runs a differential expression analysis with DESeq2

Add the following snippet to your workflow script to include this module.

include { DESEQ2_DIFFERENTIAL } from 'nf-core/deseq2/differential'

MIT License

Process

`Name`	`DESEQ2_DIFFERENTIAL`

Input 4 channels

#1 tuple

`meta` map	Groovy Map containing contrast information. This can be used at the workflow level to pass optional parameters to the module, e.g. [ id:'contrast1', blocking:'patient' ] passed in as ext.args like: '--blocking_variable $meta.blocking'.
`contrast_variable` string	The column in the sample sheet that should be used to define groups for comparison
`reference` string	The value within the contrast_variable column of the sample sheet that should be used to derive the reference samples
`target` string	The value within the contrast_variable column of the sample sheet that should be used to derive the target samples
`formula` string	(Optional) R formula string used for modeling, e.g. '~ treatment'.
`comparison` string	(Optional, mandatory if formula is provided) Literal string for contrasts, e.g. 'treatmenthND6'.

#2 tuple

`meta2` map	Groovy map containing study-wide metadata related to the sample sheet and matrix
`samplesheet` file	CSV or TSV format sample sheet with sample metadata
`counts` file	Raw TSV or CSV format expression matrix as output from the nf-core RNA-seq workflow

#3 tuple

`meta3` map	Meta map describing control genes, e.g. [ id: 'ERCC' ]
`control_genes_file` file	Text file listing control genes, one per line

#4 tuple

`meta4` map	Groovy map containing study-wide metadata related to the transcript lengths file
`transcript_lengths_file` file	Optional file of transcript lengths, with the same sample columns as counts. If supplied, lengths will be supplied to DESeq2 to correct for differences in average transcript lengths across samples.

Output 11 channels

#1 model tuple

`meta` map	Groovy Map containing contrast information, same as input meta
`*.deseq2.model.txt` file	TXT-format DESeq2 model `*.deseq2.model.txt`

#2 rdata tuple

`meta` map	Groovy Map containing contrast information, same as input meta
`*.dds.rld.rds` file	Serialised DESeq2 object `*.dds.rld.rds`

#3 results tuple

`meta` map	Groovy Map containing contrast information, same as input meta
`*.deseq2.results.tsv` file	TSV-format table of differential expression information as output by DESeq2 `*.deseq2.results.tsv`

#4 versions

`versions.yml` file	YAML file containing versions of tools used in the module

#5 vst_counts tuple

`meta` map	Groovy Map containing contrast information, same as input meta
`*.vst.tsv` file	Optional, TSV-format counts matrix, normalised to size factors, with variance stabilisation applied via `vst()`. `*.vst.tsv`

#6 rlog_counts tuple

`meta` map	Groovy Map containing contrast information, same as input meta
`*.rlog.tsv` file	Optional, TSV-format counts matrix, normalised to size factors, with variance stabilisation applied via `rlog()`. `*.rlog.tsv`

#7 session_info tuple

`*.R`
`meta` map	Groovy Map containing contrast information, same as input meta