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’ ]

meta2 (map)

Groovy Map containing information on experiment, at a minimum an id. To match meta.
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).

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

Output

Name (Type)
Description
Pattern

meta (map)

Groovy Map containing information on experiment.
e.g. [ id:‘test’ ]

data (file)

A shinyngs ExploratorySummarizedExperiment
object serialized with saveRDS().

app/data.rds

app (file)

The mini R script required build an application from data.rds.

app/app.R

versions (file)

File containing software versions

versions.yml
included in
differentialabundance
author
Github user pinin4fjords
get in touch
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Tools

shinyngs
AGPL v3

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

github.com/pinin4fjords/shinyngs rawgit.com/pinin4fjords/shinyngs/master/vignettes/shinyngs https://github.com/pinin4fjords/shinyngs