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This is the development version of GSgalgoR; for the stable release version, see GSgalgoR.

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

Bioconductor version: Development (3.20)

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.

Author: Martin Guerrero [aut], Carlos Catania [cre]

Maintainer: Carlos Catania <harpomaxx at>

Citation (from within R, enter citation("GSgalgoR")):


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))

# The following initializes usage of Bioc devel


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

GSgalgoR.html HTML R Script
GSgalgoR_callbacks.html HTML R Script
Reference Manual PDF


biocViews Classification, Clustering, GeneExpression, Software, Survival, Transcription
Version 1.15.0
In Bioconductor since BioC 3.12 (R-4.0) (3.5 years)
License MIT + file LICENSE
Imports cluster, doParallel, foreach, matchingR, nsga2R, survival, proxy, stats, methods
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Suggests knitr, rmarkdown, ggplot2, BiocStyle, genefu, survcomp, Biobase, survminer, breastCancerTRANSBIG, breastCancerUPP, iC10TrainingData, pamr, testthat
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Source Package GSgalgoR_1.15.0.tar.gz
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