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GSgalgoR

Bioc current

An Evolutionary Framework for the Identification and Study of Prognostic Gene Expression Signatures in Cancer

v1.22.0 · software · MIT + file LICENSE

Release Lineage

Entered 3.12 · Oct 28, 2020

Current · Requires R 4.6

1.0 In 12 of 49 releases 3.23

Description

A multi-objective optimization algorithm for disease sub-type discovery based on a non-dominated sorting genetic algorithm. The 'Galgo' framework combines the advantages of clustering algorithms for grouping heterogeneous 'omics' data and the searching properties of genetic algorithms for feature selection. The algorithm search for the optimal number of clusters determination considering the features that maximize the survival difference between sub-types while keeping cluster consistency high.

Test coverage

Line coverage

Expression

Tests / Examples

Functions

39 21 exported

Complexity

2.2 avg / 12 max

Call network

39 nodes / 26 edges

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

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Lowest coverage

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

Code

Structure

Lines of code

4,585

Files

132

Compiled share

0%

Has compiled src

No

Language breakdown

R 2,036 (44.4%)Tests 331 (7.2%)Docs 1,042 (22.7%)Vignettes 1,176 (25.6%)

API

Exported functions

21

Internal functions

13

Testing & CI

Has tests

Yes

Test-to-code ratio

0.16

testthat edition

CI present

No

CI type

[]

PR gated

No

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

12

First release

2020-10-27

Latest release

2026-04-28

Avg cadence

182 days

Cold removal rate

Dep drift

0

LOC over versions

v3.12: 4,585 LOCv3.13: 4,585 LOCv3.14: 4,585 LOCv3.15: 4,585 LOCv3.16: 4,585 LOCv3.17: 4,585 LOCv3.18: 4,585 LOCv3.19: 4,585 LOCv3.20: 4,585 LOCv3.21: 4,585 LOCv3.22: 4,585 LOCv3.23: 4,585 LOC

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

Documentation

Documentation
READMEYes · 615 wordsVignettesYes · dynamicpkgdown siteYesNEWSYes · 67% structuredCode of conductNoContributing guideNo
Examples that run
100%
Documented parameters
94%
Return-value docs
100%
References docs
11%

Topics

People

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("GSgalgoR")
Catania, C., & Guerrero, M. (2026). GSgalgoR: An Evolutionary Framework for the Identification and Study of Prognostic Gene Expression Signatures in Cancer (Version 1.22.0) [Computer software]. https://bioconductor.org/packages/GSgalgoR

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 GSgalgoR version 1.22.0 [Data set]. HJJB, LLC. Data release v2026-08-24. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-24, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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