Description

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

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.

app/app.R

versions_shinyngs

${task.process}

:string

The name of the process

shinyngs

:string

The name of the tool

Rscript -e "library(shinyngs); cat(as.character(packageVersion('shinyngs')))"

:eval

The expression to obtain the version of the tool

Topics

name:type
description
pattern

versions

${task.process}

:string

The name of the process

shinyngs

:string

The name of the tool

Rscript -e "library(shinyngs); cat(as.character(packageVersion('shinyngs')))"

:eval

The expression to obtain the version of the tool

Tools

shinyngs
AGPL v3

Provides Shiny applications for various array and NGS applications. Currently very RNA-seq centric, with plans for expansion.