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:	2.1
Depends:	R (≥ 4.0)
Imports:	Matrix, Rcpp, RcppEigen
LinkingTo:	Rcpp, RcppEigen
Published:	2022-07-16
Author:	Alencar Xavier, William Muir, David Habier, Kyle Kocak, Shizhong Xu, Katy Rainey.
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_2.1.tar.gz
Windows binaries:	r-devel: bWGR_2.1.zip, r-release: bWGR_2.1.zip, r-oldrel: bWGR_2.1.zip
macOS binaries:	r-release (arm64): bWGR_2.1.tgz, r-oldrel (arm64): bWGR_2.1.tgz, r-release (x86_64): bWGR_2.1.tgz, r-oldrel (x86_64): bWGR_2.1.tgz
Old sources:	bWGR archive

Reverse dependencies:

Reverse suggests:

NAM

Linking:

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