runs a differential expression analysis with Limma
Input
name:type
description
pattern
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
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
name:type
description
pattern
results
meta:file
TSV-format table of differential expression information as output by Limma
*.limma.results.tsv
*.limma.results.tsv:file
TSV-format table of differential expression information as output by Limma
*.limma.results.tsv
md_plot
meta:file
Limma mean difference plot
*.mean_difference.png
*.limma.mean_difference.png:file
Limma mean difference plot
*.mean_difference.png
rdata
meta:file
Serialised MArrayLM object
*.MArrayLM.limma.rds
*.MArrayLM.limma.rds:file
Serialised MArrayLM object
*.MArrayLM.limma.rds
model
meta:file
TXT-format limma model
*.limma.model.tsv
*.limma.model.txt:file
TXT-format limma model
*.limma.model.tsv
session_info
meta:file
dump of R SessionInfo
*.log
*.R_sessionInfo.log:file
dump of R SessionInfo
*.log
normalised_counts
meta:file
normalised TSV format expression matrix with probes by row and samples by column
*.normalised_counts.tsv
*.normalised_counts.tsv:file
normalised TSV format expression matrix with probes by row and samples by column
