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.

Version: 1.0.5
Depends: R (≥ 3.5)
Imports: data.table, ggplot2 (≥ 3.0.0), sommer (≥ 3.7.3), Rcpp
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, rmarkdown, officer, tinytest
Published: 2020-09-29
Author: Bart-Jan van Rossum [aut, cre], Willem Kruijer ORCID iD [aut], Fred van Eeuwijk ORCID iD [ctb], Martin Boer [ctb], Marcos Malosetti ORCID iD [ctb], Daniela Bustos-Korts ORCID iD [ctb], Emilie Millet ORCID iD [ctb], Joao Paulo ORCID iD [ctb], Maikel Verouden ORCID iD [ctb], Ron Wehrens ORCID iD [ctb], Choazhi Zheng ORCID iD [ctb]
Maintainer: Bart-Jan van Rossum <bart-jan.vanrossum at wur.nl>
BugReports: https://github.com/Biometris/statgenGWAS/issues
License: GPL-3
URL: https://biometris.github.io/statgenGWAS/index.html, https://github.com/Biometris/statgenGWAS/
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: statgenGWAS results

Downloads:

Reference manual: statgenGWAS.pdf
Vignettes: Introduction to the statgenGWAS package
Package source: statgenGWAS_1.0.5.tar.gz
Windows binaries: r-devel: statgenGWAS_1.0.5.zip, r-release: statgenGWAS_1.0.5.zip, r-oldrel: statgenGWAS_1.0.5.zip
macOS binaries: r-release: statgenGWAS_1.0.5.tgz, r-oldrel: statgenGWAS_1.0.5.tgz
Old sources: statgenGWAS archive

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