cpgen : Parallelized Genomic Prediction and GWAS

Package: cpgen
Type: Package
Title: Parallelized Genomic Prediction and GWAS
Version: 0.1
Date: 2015-09-14
Author: Claas Heuer
Maintainer: Claas Heuer <cheuer@tierzucht.uni-kiel.de>
Description: Frequently used methods in genomic applications with emphasis on parallel computing (OpenMP).
At its core, the package has a Gibbs Sampler that allows running univariate linear
mixed models that have both, sparse and dense design matrices. The parallel sampling method
in case of dense design matrices (e.g. Genotypes) allows running Ridge Regression or BayesA for
a very large number of individuals. The Gibbs Sampler is capable of running Single Step Genomic Prediction models.
In addition, the package offers parallelized functions for common tasks like genome-wide
association studies and cross validation in a memory efficient way.
License: GPL (>= 2)
SystemRequirements: C++11
Imports: methods, stats
URL: https://github.com/cheuerde/cpgen
Depends: R (>= 3.1.0), Matrix (>= 1.0-5), pedigreemm (>= 0.3-3)
LinkingTo: Rcpp, RcppEigen, RcppProgress
NeedsCompilation: yes
Packaged: 2015-09-14 21:44:43 UTC; cheuer
Repository: CRAN
Date/Publication: 2015-09-15 08:35:30