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ReactomeGSA

Bioc current

Client for the Reactome Analysis Service for comparative multi-omics gene set analysis

v1.26.0 · software · MIT + file LICENSE

Release Lineage

Entered 3.10 · Oct 30, 2019

Current · Requires R 4.6

1.0 In 14 of 49 releases 3.23

Description

The ReactomeGSA packages uses Reactome's online analysis service to perform a multi-omics gene set analysis. The main advantage of this package is, that the retrieved results can be visualized using REACTOME's powerful webapplication. Since Reactome's analysis service also uses R to perfrom the actual gene set analysis you will get similar results when using the same packages (such as limma and edgeR) locally. Therefore, if you only require a gene set analysis, different packages are more suited.

Test coverage

Line coverage

Expression

Tests / Examples

Functions

29 10 exported

Complexity

4 avg / 16 max

Call network

29 nodes / 16 edges

Test coverage is not measured for Bioconductor packages; nodes fall back to a neutral fill.

Loading call graph…

Lowest coverage

Per-function coverage is not measured for this package yet.

Code

Structure

Lines of code

7,125

Files

101

Compiled share

0%

Has compiled src

No

Language breakdown

R 3,173 (44.5%)Tests 110 (1.5%)Docs 3,107 (43.6%)Vignettes 735 (10.3%)

API

Exported functions

29

Internal functions

19

Recent export changes

v3.21+2 generate_metadata, generate_pseudo_bulk_data
v3.19+3 find_public_datasets, get_public_species, load_public_dataset

Testing & CI

Has tests

Yes

Test-to-code ratio

0.03

testthat edition

CI present

No

CI type

[]

PR gated

No

Docs

Roxygen coverage

100%

Health & Security signals

Informational signals; not verdicts.

on.exit coverage

0%

Unsafe pattern score

0

Dep constraint coverage

0%

Secret pattern count

0

Bundled 3rd-party code

2 items

Portability & License

Min R version

System requirements

C++ standard

License

MIT + file LICENSE

License flags

SPDX valid, OSI approved

History

Versions

14

First release

2019-10-29

Latest release

2026-04-28

Avg cadence

182 days

Cold removal rate

Dep drift

8

LOC over versions

v3.10: 3,802 LOCv3.11: 5,289 LOCv3.12: 5,298 LOCv3.13: 5,312 LOCv3.14: 5,636 LOCv3.15: 5,636 LOCv3.16: 5,636 LOCv3.17: 5,636 LOCv3.18: 5,636 LOCv3.19: 6,295 LOCv3.20: 6,295 LOCv3.21: 7,125 LOCv3.22: 7,125 LOCv3.23: 7,125 LOC

Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/bioc-code-metrics.

Documentation

Documentation
READMEYes · 210 wordsVignettesYes · dynamicpkgdown siteNoNEWSYes · 100% structuredCode of conductNoContributing guideNo
Examples that run
100%
Documented parameters
100%
Return-value docs
100%
References docs
0%

Topics

Depended on by (1)

Bioconductor (1)

People

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("ReactomeGSA")
Griss, J. (2026). ReactomeGSA: Client for the Reactome Analysis Service for comparative multi-omics gene set analysis (Version 1.26.0) [Computer software]. https://bioconductor.org/packages/ReactomeGSA

This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for ReactomeGSA version 1.26.0 [Data set]. HJJB, LLC. Data release v2026-08-22. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-22, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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