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

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.

Package details

AuthorMartin Guerrero [aut], Carlos Catania [cre]
Bioconductor views Classification Clustering GeneExpression Survival Transcription
MaintainerCarlos Catania <>
LicenseMIT + file LICENSE
Package repositoryView on Bioconductor
Installation Install the latest version of this package by entering the following in R:
if (!requireNamespace("BiocManager", quietly = TRUE))


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GSgalgoR documentation built on Nov. 8, 2020, 6:57 p.m.