Package: statgenGWAS 1.0.10

Bart-Jan van Rossum

statgenGWAS: Genome Wide Association Studies

Fast single trait Genome Wide Association Studies (GWAS) following the method described in Kang et al. (2010), <doi:10.1038/ng.548>. One of a series of statistical genetic packages for streamlining the analysis of typical plant breeding experiments developed by Biometris.

Authors:Bart-Jan van Rossum [aut, cre], Willem Kruijer [aut], Fred van Eeuwijk [ctb], Martin Boer [ctb], Marcos Malosetti [ctb], Daniela Bustos-Korts [ctb], Emilie Millet [ctb], Joao Paulo [ctb], Maikel Verouden [ctb], Ron Wehrens [ctb], Choazhi Zheng [ctb]

statgenGWAS_1.0.10.tar.gz
statgenGWAS_1.0.10.tar.gz(r-4.5-noble)statgenGWAS_1.0.10.tar.gz(r-4.4-noble)
statgenGWAS_1.0.10.tgz(r-4.4-emscripten)statgenGWAS_1.0.10.tgz(r-4.3-emscripten)
statgenGWAS.pdf |statgenGWAS.html✨
statgenGWAS/json (API)
NEWS

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

Bug tracker:https://github.com/biometris/statgengwas/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:

On CRAN:

Conda:

openblascppopenmp

3.94 score 1 stars 3 packages 14 scripts 1.4k downloads 1 mentions 5 exports 34 dependencies

Last updated 4 months agofrom:446981db0e. Checks:2 OK. Indexed: no.

TargetResultLatest binary
Doc / VignettesOKFeb 23 2025
R-4.5-linux-x86_64OKFeb 23 2025

Exports:codeMarkerscreateGDatakinshipreadPLINKrunSingleTraitGwas

Dependencies:clicolorspacecrayondata.tablefansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerRcppRcppArmadilloRcppProgressrlangscalessommertibbleutf8vctrsviridisLitewithr

Introduction to the statgenGWAS package

Bart-Jan van Rossum

Rendered fromGWAS.Rmdusingknitr::rmarkdownon Feb 23 2025.

Last update: 2024-11-15
Started: 2020-01-19