Package: BioGA 1.7.0

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_1.7.0.tar.gz
BioGA_1.7.0.zip(r-4.7)BioGA_1.7.0.zip(r-4.6)BioGA_1.7.0.zip(r-4.5)
BioGA_1.7.0.tgz(r-4.6-x86_64)BioGA_1.7.0.tgz(r-4.6-arm64)BioGA_1.7.0.tgz(r-4.5-x86_64)BioGA_1.7.0.tgz(r-4.5-arm64)
BioGA_1.7.0.tar.gz(r-4.7-arm64)BioGA_1.7.0.tar.gz(r-4.7-x86_64)BioGA_1.7.0.tar.gz(r-4.6-arm64)BioGA_1.7.0.tar.gz(r-4.6-x86_64)
BioGA_1.7.0.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.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:4a2de1d1e3. Checks:1 NOTE, 13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksNOTE254
linux-devel-arm64OK302
linux-devel-x86_64OK343
source / vignettesOK334
linux-release-arm64OK321
linux-release-x86_64OK298
macos-release-arm64OK187
macos-release-x86_64OK498
macos-oldrel-arm64OK175
macos-oldrel-x86_64OK411
windows-develOK279
windows-releaseOK283
windows-oldrelOK252
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 20 2026.

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