R Observatory: Metrics for GSABenchmark version 1.0.0

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

GSABenchmark

Bioc current

Tools for benchmarking single-cell gene set analysis methods

v1.0.0 · Package record · software · MIT + file LICENSE

View on Bioconductor ↗ Source ↗

Release Lineage

Entered 3.23 · Apr 29, 2026

Current · Requires R 4.6

1.0 In 1 of 49 releases 3.23

Description

GSABenchmark is a package designed for benchmarking scRNA-seq gene set analysis (scGSA) methods. It provides both traditional and novel benchmark metrics, as well as visualization tools. Currently, GSABenchmark supports 17 scGSA methods.

Advisories

None published for Bioconductor

Test coverage

Line coverage

–

Expression

–

Tests / Examples

–

Functions

96 36 exported

Complexity

1.6 avg / 7 max

Call network

96 nodes / 92 edges

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

Call graph

Open call graph →

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Lowest coverage

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

How coverage is measured·How the call graph is built

Code

Structure

Lines of code

5,964

Files

116

Compiled share

0%

Has compiled src

No

Language breakdown

R 3,025 (50.7%)Tests 112 (1.9%)Docs 2,566 (43%)Vignettes 261 (4.4%)

API

Exported functions

36

Internal functions

60

Recent export changes

v3.23+36 aggregateRankPlot, allBenchmarkPlots, allBenchmarkResults +33 more

Testing

Has tests

Yes

Test-to-code ratio

0.04

testthat edition

3

Docs

Roxygen coverage

100%

Health & Security signals

Informational signals; not verdicts.

on.exit coverage

–

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

1

First release

2026-04-28

Latest release

2026-04-28

Avg cadence

–

Cold removal rate

–

Dep drift

0

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

Documentation

In the Bioconductor 3.23 release

READMEYes · 530 wordsVignettesYes · 1 · dynamicNEWSYes · 67% structuredCitation fileNoWebsitenot declared in DESCRIPTION

Help pages: 75 (39 internal)includes a package overview page
Examples that run: 100%36 run in a plain check (4 of them under a condition)
Exported functions with examples: 100%
Documented parameters: 99%
Return-value docs: 100%
Help pages citing references: 0%

Vignettes (1)

GSABenchmark HTML

How these are measured

Repository practices

Upstream repositoryBeta

Checks run against github.com/andrei-stoica26/gsabenchmark on 2026-10-22.

No development-tooling practices detected in the upstream repository.

How this is detected·Detection ruleset v4 (2026-10-20)

Topics

Software

Software › Technology › SingleCell

Software › BiologicalQuestion › GeneSetEnrichment

Software › AssayDomain › GeneExpression

Software › WorkflowStep › Visualization

Maintainer: Andrei-Florian Stoica

Available on

CRANr2uBioconductorautoCRANCOPR

People

Andrei-Florian Stoica author maintainer

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("GSABenchmark")

Format

Stoica, A. (2026). GSABenchmark: Tools for benchmarking single-cell gene set analysis methods (Version 1.0.0) [Computer software]. https://bioconductor.org/packages/GSABenchmark

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

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

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for GSABenchmark version 1.0.0 [Data set]. HJJB, LLC. Data release v2026-10-25. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-25, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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