GSgalgoR
An Evolutionary Framework for the Identification and Study of Prognostic Gene Expression Signatures in Cancer
Bioconductor version: 3.24 · Package version: 1.23.0
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.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("GSgalgoR")Details
| Maintainer | Carlos Catania <harpomaxx@gmail.com> |
| Author | Martin Guerrero [aut], Carlos Catania [cre] |
| License | MIT + file LICENSE |
| URL | https://github.com/harpomaxx/GSgalgoR |
| Bug Reports | https://github.com/harpomaxx/GSgalgoR/issues |
| Downloads rank | 397 |
| Source branch | devel |
| biocViews | Classification, Clustering, GeneExpression, Software, Survival, Transcription |
Documentation
Download
Follow the installation instructions to use this package in your R session.
| Source package | GSgalgoR_1.23.0.tar.gz |
| Windows binary (x86_64) | GSgalgoR_1.23.0.zip |
| macOS binary (arm64) | GSgalgoR_1.23.0.tgz |
| macOS binary (x86_64) | GSgalgoR_1.23.0.tgz |