build and deploy Shiny apps for interactively mining differential abundance data
Input
name:type
description
pattern
meta
:map
Groovy Map containing information on experiment, at a minimum an id.
e.g. [ id:‘test’ ]
sample
:file
CSV-format sample sheet with sample metadata
feature_meta
:file
TSV-format feature (e.g. gene) metadata
assay_files
:file
List of TSV-format matrix files representing different measures for the same samples (e.g. raw and normalised).
meta2
:map
Groovy Map containing information on experiment, at a minimum an id. To match meta.
e.g. [ id:‘test’ ]
contrasts
:file
CSV-format file with four columns identifying the sample sheet variable, reference level, treatment level, and optionally a comma-separated list of covariates used as blocking factors.
differential_results
:file
List of TSV-format differential analysis outputs, one per row of the contrasts file
contrast_stats_assay
:file
contrast statistics
gene_sets
:file
Optional: GMT-format gene set files used for enrichment, referenced in the
app via the shinyngs --enrichment_gene_sets argument.
*.{gmt}
enrichment_results
:file
Optional: per-contrast enrichment result tables (e.g. GSEA output), matched
to contrasts in the app via the shinyngs --enrichment_filename_template argument.
Output
name:type
description
pattern
app
meta
:map
Groovy Map containing information on experiment.
e.g. [ id:‘test’ ]
*/data.rds
:file
The mini R script required build an application from data.rds.
app/app.R
*/app.R
:file
The mini R script required build an application from data.rds.
