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_0.99.6.zip(r-4.3)
BioGA_1.1.0.tgz(r-4.4-x86_64)BioGA_1.1.0.tgz(r-4.4-arm64)BioGA_0.99.6.tgz(r-4.3-x86_64)BioGA_0.99.6.tgz(r-4.3-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_0.99.6.tgz(r-4.3-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'))

Peer review:

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

Pkgdown: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)

experimentaldesigntechnologycpp

4.74 score 5 scripts 120 downloads 9 exports 88 dependencies

Last updated 2 months agofrom:7656c41b59. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 29 2024
R-4.5-win-x86_64OKNov 29 2024
R-4.5-linux-x86_64OKNov 29 2024
R-4.4-win-x86_64OKNov 29 2024
R-4.4-mac-x86_64OKNov 29 2024
R-4.4-mac-aarch64OKNov 29 2024
R-4.3-win-x86_64OKSep 14 2024
R-4.3-mac-x86_64OKSep 14 2024
R-4.3-mac-aarch64OKSep 14 2024

Exports:crossover_cppevaluate_fitness_cppinitialize_population_cppmutation_cppplot_fitnessplot_fitness_historyplot_populationreplacement_cppselection_cpp

Dependencies:abindanimationaskpassbase64encBHBiobaseBiocGenericsBiocManagerBiocStylebiocViewsbitopsbookdownbslibcachemclicolorspacecrayoncurlDelayedArraydigestevaluatefansifarverfastmapfontawesomefsgenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2gluegraphgtablehighrhtmltoolshttrIRangesisobandjquerylibjsonliteknitrlabelinglatticelifecyclemagickmagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemgcvmimemunsellnlmeopensslpillarpkgconfigR6rappdirsRBGLRColorBrewerRcppRCurlrlangrmarkdownRUnitS4ArraysS4VectorssassscalessessioninfoSparseArraySummarizedExperimentsystibbletinytexUCSC.utilsutf8vctrsviridisLitewithrxfunXMLXVectoryamlzlibbioc

Introduction

Dany Mukesha

Rendered fromIntroduction.Rmdusingknitr::rmarkdownon Nov 29 2024.

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