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
[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:
Downloads:
Reverse dependencies:
Linking:
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