This is the released version of GSgalgoR; for the devel version, see GSgalgoR.
An Evolutionary Framework for the Identification and Study of Prognostic Gene Expression Signatures in CancerBioconductor version: Release (3.21)
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 gmail.com>
Citation (from within R, entercitation("GSgalgoR")
): Installation
To install this package, start R (version "4.5") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("GSgalgoR")
For older versions of R, please refer to the appropriate Bioconductor release.
DocumentationTo view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("GSgalgoR")
Details biocViews Classification, Clustering, GeneExpression, Software, Survival, Transcription Version 1.18.0 In Bioconductor since BioC 3.12 (R-4.0) (4.5 years) License MIT + file LICENSE Depends Imports cluster, doParallel, foreach, matchingR, nsga2R, survival, proxy, stats, methods System Requirements URL https://github.com/harpomaxx/GSgalgoR Bug Reports https://github.com/harpomaxx/GSgalgoR/issues See More Suggests knitr, rmarkdown, ggplot2, BiocStyle, genefu, survcomp, Biobase, survminer, breastCancerTRANSBIG, breastCancerUPP, iC10TrainingData, pamr, testthat Linking To Enhances Depends On Me Imports Me Suggests Me Links To Me Build Report Build Report Package Archives
Follow Installation instructions to use this package in your R session.
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