Package: BioGA 1.1.0

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_1.1.0.tar.gz
BioGA_1.1.0.zip(r-4.5)BioGA_1.1.0.zip(r-4.4)
BioGA_1.1.0.tgz(r-4.5-x86_64)BioGA_1.1.0.tgz(r-4.5-arm64)BioGA_1.1.0.tgz(r-4.4-x86_64)BioGA_1.1.0.tgz(r-4.4-arm64)
BioGA_1.1.0.tar.gz(r-4.5-noble)BioGA_1.1.0.tar.gz(r-4.4-noble)
BioGA_1.1.0.tgz(r-4.4-emscripten)
BioGA.pdf |BioGA.html✨
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 site:https://danymukesha.github.io

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

On BioConductor:BioGA-1.1.0(bioc 3.21)BioGA-1.0.0(bioc 3.20)

experimentaldesigntechnologygenetic-algorithmoptimizationcpp

4.74 score 5 scripts 122 downloads 9 exports 87 dependencies

Last updated 4 months agofrom:7656c41b59. Checks:6 OK, 2 WARNING. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKJan 28 2025
R-4.5-win-x86_64OKJan 28 2025
R-4.5-mac-x86_64WARNINGJan 28 2025
R-4.5-mac-aarch64WARNINGJan 28 2025
R-4.5-linux-x86_64OKJan 28 2025
R-4.4-win-x86_64OKJan 28 2025
R-4.4-mac-x86_64OKJan 28 2025
R-4.4-mac-aarch64OKJan 28 2025

Exports:crossover_cppevaluate_fitness_cppinitialize_population_cppmutation_cppplot_fitnessplot_fitness_historyplot_populationreplacement_cppselection_cpp

Dependencies:abindanimationaskpassbase64encBHBiobaseBiocGenericsBiocManagerBiocStylebiocViewsbitopsbookdownbslibcachemclicolorspacecrayoncurlDelayedArraydigestevaluatefansifarverfastmapfontawesomefsgenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2gluegraphgtablehighrhtmltoolshttrIRangesisobandjquerylibjsonliteknitrlabelinglatticelifecyclemagickmagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemgcvmimemunsellnlmeopensslpillarpkgconfigR6rappdirsRBGLRColorBrewerRcppRCurlrlangrmarkdownRUnitS4ArraysS4VectorssassscalessessioninfoSparseArraySummarizedExperimentsystibbletinytexUCSC.utilsutf8vctrsviridisLitewithrxfunXMLXVectoryaml

Introduction

Dany Mukesha

Rendered fromIntroduction.Rmdusingknitr::rmarkdownon Jan 28 2025.

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