bWGR: Bayesian Whole-Genome Regression

Whole-genome regression methods on Bayesian framework fitted via EM or Gibbs sampling, single step (<doi:10.1534/g3.119.400728>), univariate and multivariate (<doi:10.1186/s12711-022-00730-w>), with optional kernel term and sampling techniques (<doi:10.1186/s12859-017-1582-3>).

Version: 2.2.5
Depends: R (≥ 4.0)
Imports: Matrix, Rcpp
LinkingTo: Rcpp, RcppEigen
Published: 2023-11-21
Author: Alencar Xavier ORCID iD [aut, cre], William Muir [aut], David Habier [aut], Kyle Kocak [aut], Shizhong Xu [aut], Katy Rainey [aut]
Maintainer: Alencar Xavier <alenxav at gmail.com>
License: GPL-3
NeedsCompilation: yes
Citation: bWGR citation info
CRAN checks: bWGR results

Documentation:

Reference manual: bWGR.pdf

Downloads:

Package source: bWGR_2.2.5.tar.gz
Windows binaries: r-devel: bWGR_2.2.5.zip, r-release: bWGR_2.2.5.zip, r-oldrel: bWGR_2.2.5.zip
macOS binaries: r-release (arm64): bWGR_2.2.5.tgz, r-oldrel (arm64): bWGR_2.2.5.tgz, r-release (x86_64): bWGR_2.2.5.tgz, r-oldrel (x86_64): bWGR_2.2.3.tgz
Old sources: bWGR archive

Reverse dependencies:

Reverse suggests: NAM

Linking:

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