GSgalgoR

DOI: 10.18129/B9.bioc.GSgalgoR  

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

Bioconductor version: Release (3.16)

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>

Installation

To install this package, start R (version "4.2") 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.

Documentation

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

browseVignettes("GSgalgoR")

 

HTML	R Script	GSgalgoR.html
HTML	R Script	GSgalgoR_callbacks.html
PDF		Reference Manual
Text		NEWS
Text		LICENSE

Details

biocViews	Classification, Clustering, GeneExpression, Software, Survival, Transcription
Version	1.8.0
In Bioconductor since	BioC 3.12 (R-4.0) (2.5 years)
License	MIT + file LICENSE
Depends
Imports	cluster, doParallel, foreach, matchingR, nsga2R, survival, proxy, stats, methods
LinkingTo
Suggests	knitr, rmarkdown, ggplot2, BiocStyle, genefu, survcomp, Biobase, survminer, breastCancerTRANSBIG, breastCancerUPP, iC10TrainingData, pamr, testthat
SystemRequirements
Enhances
URL	https://github.com/harpomaxx/GSgalgoR
BugReports	https://github.com/harpomaxx/GSgalgoR/issues
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package	GSgalgoR_1.8.0.tar.gz
Windows Binary	GSgalgoR_1.8.0.zip (64-bit only)
macOS Binary (x86_64)	GSgalgoR_1.8.0.tgz
macOS Binary (arm64)	GSgalgoR_1.8.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/GSgalgoR
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/GSgalgoR
Bioc Package Browser	https://code.bioconductor.org/browse/GSgalgoR/
Package Short Url	https://bioconductor.org/packages/GSgalgoR/
Package Downloads Report	Download Stats