Nextflow Registry | nf-core/limma/differential@0.0.0-c4ed7fd

nf-core/limma/differential @ 0.0.0-c4ed7fd

runs a differential expression analysis with Limma

differential expression microarray limma

Latest version: 0.0.0-c4ed7fd

Total downloads: 16

Source: nf-core/modules

Authors: @pinin4fjords

Maintainers: @pinin4fjords

runs a differential expression analysis with Limma

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

include { LIMMA_DIFFERENTIAL } from 'nf-core/limma/differential'

MIT License

Process

`Name`	`LIMMA_DIFFERENTIAL`

Input 2 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	(Optional, required if reference and target are used) The column in the sample sheet that should be used to define groups for comparison
`reference` string	(Optional, required if contrast_variable and target are used) The value within the contrast_variable column of the sample sheet that should be used to derive the reference samples
`target` string	(Optional, required if contrast_variable and reference are used) The value within the contrast_variable column of the sample sheet that should be used to derive the target samples
`formula` string	(Optional, requires comparison if used) R formula string used for modeling, e.g. '~ treatment'.
`comparison` string	(Optional, mandatory if formula is used) Literal string passed to `limma::makeContrasts`, e.g. 'treatmentmCherry'.

#2 tuple

`meta2` map	Groovy map containing study-wide metadata related to the sample sheet and matrix
`samplesheet` file	Sample sheet file
`intensities` file	Raw TSV or CSV format expression matrix with probes by row and samples by column

Output 7 channels

#1 model 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'.
`*.limma.model.txt` file	TXT-format limma model `*.limma.model.tsv`

#2 rdata 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'.
`*.MArrayLM.limma.rds` file	Serialised MArrayLM object `*.MArrayLM.limma.rds`

#3 md_plot 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'.
`*.limma.mean_difference.png` file	Limma mean difference plot `*.mean_difference.png`

#4 results 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'.
`*.limma.results.tsv` file	TSV-format table of differential expression information as output by Limma `*.limma.results.tsv`

#5 versions

`versions.yml` file	File containing software versions `versions.yml`

#6 session_info 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'.
`*.R_sessionInfo.log` file	dump of R SessionInfo `*.log`

#7 normalised_counts 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'.
`*.normalised_counts.tsv` file	normalised TSV format expression matrix with probes by row and samples by column `*.normalised_counts.tsv`

Tool	Description	Homepage
limma	Linear Models for Microarray Data	https://bioconductor.org/packages/release/bioc/html/limma.html

Version	0.0.0-c4ed7fd