Package: BioGA 1.6.0

Dany Mukesha

BioGA: Bioinformatics Genetic Algorithm (BioGA)

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.

Authors:Dany Mukesha [aut, cre]

BioGA_1.6.0.tar.gz
BioGA_1.6.0.zip(r-4.7)BioGA_1.6.0.zip(r-4.6)BioGA_1.6.0.zip(r-4.5)
BioGA_1.6.0.tgz(r-4.6-x86_64)BioGA_1.6.0.tgz(r-4.6-arm64)BioGA_1.6.0.tgz(r-4.5-x86_64)BioGA_1.6.0.tgz(r-4.5-arm64)
BioGA_1.6.0.tar.gz(r-4.7-arm64)BioGA_1.6.0.tar.gz(r-4.7-x86_64)BioGA_1.6.0.tar.gz(r-4.6-arm64)BioGA_1.6.0.tar.gz(r-4.6-x86_64)
BioGA_1.6.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
BioGA/json (API)
NEWS

# Install 'BioGA' in R:
install.packages('BioGA', repos = c('https://bioc-release.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/danymukesha/bioga/issues

Pkgdown/docs site:https://danymukesha.github.io

Uses libs:
  • c++– GNU Standard C++ Library v3

On BioConductor:BioGA-1.7.0(bioc 3.24)BioGA-1.6.0(bioc 3.23)

experimentaldesigntechnologydata-analysisgene-expressiongenetic-algorithmsgenomicsoptimization-algorithmscpp

4.04 score 11 scripts 228 downloads 9 exports 72 dependencies

Last updated from:ad6ac0545d (on RELEASE_3_23). Checks:1 NOTE, 13 OK. Indexed: no.

TargetResultTimeFilesSyslog
bioc-checksNOTE243
linux-devel-arm64OK332
linux-devel-x86_64OK312
source / vignettesOK291
linux-release-arm64OK363
linux-release-x86_64OK358
macos-release-arm64OK246
macos-release-x86_64OK492
macos-oldrel-arm64OK176
macos-oldrel-x86_64OK633
windows-develOK248
windows-releaseOK303
windows-oldrelOK285
wasm-releaseOK193

Exports:crossover_cppevaluate_fitness_cppinitialize_population_cppmutation_cppplot_fitnessplot_fitness_historyplot_populationreplacement_cppselection_cpp

Dependencies:abindanimationbase64encBHBiobaseBiocGenericsBiocManagerBiocStylebiocViewsbitopsbookdownbslibcachemclicpp11curlDelayedArraydigestevaluatefarverfastmapfontawesomefsgenericsGenomicRangesggplot2gluegraphgtablehighrhtmltoolsIRangesisobandjquerylibjsonliteknitrlabelinglatticelifecyclemagickmagrittrMatrixMatrixGenericsmatrixStatsmemoisemimeR6rappdirsRBGLRColorBrewerRcppRCurlrlangrmarkdownRUnitS4ArraysS4VectorsS7sassscalesSeqinfosessioninfoSparseArraySummarizedExperimenttinytexvctrsviridisLitewithrxfunXMLXVectoryaml

Introduction

Dany Mukesha

Rendered fromIntroduction.Rmdusingknitr::rmarkdownon May 29 2026.

Last update: 2024-06-04
Started: 2024-02-26