Description

Perform differential analysis and filtering on abundance data

Input

name:type
description
pattern

ch_abundance :file

Channel with abundance data and metadata
Structure: [ val(meta_exp), path(counts) ]
meta keys: method, args_diff

ch_transcript_lengths :file

Channel with transcript length information
Structure: [ val(meta_exp), path(transcript_lengths) ]

ch_control_features :file

Channel with control features information
Structure: [ val(meta_exp), path(control_features) ]

ch_samplesheet :file

Channel with sample information
Structure: [ val(meta_exp), path(samplesheet) ]

ch_contrasts :value

Channel with contrast information
Structure: [ val(meta_contrast), val(contrast_variable), val(reference), val(target) ]

differential_method :string

Method to use for differential analysis. Options: ‘limma’, ‘deseq2’

FC_threshold :float

Fold change threshold for filtering differential results

padj_threshold :float

Adjusted p-value threshold for filtering differential results

Output

name:type
description
pattern

results_genewise :file

Unfiltered differential analysis results

*.{csv,tsv}

results_genewise_filtered :file

Filtered differential analysis results

*.{csv,tsv}

normalised_matrix :file

Normalised count matrix

*.{csv,tsv}

variance_stabilised_matrix :file

Variance stabilised count matrix (optional, DESeq2 only)

*.{csv,tsv}

model :file

Statistical model object from differential analysis

*.rds

versions :file

File containing software versions

versions.yml