BioGA
Bioinformatics Genetic Algorithm (BioGA)
Bioconductor version: 3.23 · Package version: 1.6.0
Other Bioconductor versions
devel is the development version; release is the current stable one.
3.24 (devel), 3.23 (release)
Genetic algorithm are a class of optimization algorithms inspired by the process of natural selection and genetics. This package allows users to analyze and optimize high throughput genomic data using genetic algorithms. The functions provided are implemented in C++ for improved speed and efficiency, with an easy-to-use interface for use within R.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("BioGA")Details
| Maintainer | Dany Mukesha <danymukesha@gmail.com> |
| Author | Dany Mukesha [aut, cre] (ORCID: <https://orcid.org/0009-0001-9514-751X>) |
| License | MIT + file LICENSE |
| URL | https://danymukesha.github.io/BioGA/ |
| Bug Reports | https://github.com/danymukesha/BioGA/issues |
| Source branch | RELEASE_3_23 |
| Build report | Bioconductor build system, r-universe |
| biocViews | ExperimentalDesign, Software, Technology |
| Package Short Url | https://bioconductor.org/packages/BioGA/ |
Citation
From within R, enter citation("BioGA"):
Dany Mukesha. BioGA: Bioinformatics Genetic Algorithm (BioGA). doi:10.18129/B9.bioc.BioGA, R package version 1.6.0, https://bioconductor.org/packages/BioGA.
Generated from the package metadata; it may differ from the package's own citation.
Documentation
Download
Follow the installation instructions to use this package in your R session.
| Source package | BioGA_1.6.0.tar.gz |
| Windows binary (x86_64) | BioGA_1.6.0.zip |
| macOS binary (arm64) | BioGA_1.6.0.tgz |
| macOS binary (x86_64) | BioGA_1.6.0.tgz |
Dependencies
Depends: R (>= 4.4)
Imports: ggplot2, graphics, Rcpp, SummarizedExperiment, animation, rlang, biocViews, sessioninfo, BiocStyle
LinkingTo: Rcpp
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)