predhy: Genomic Prediction of Hybrid Performance

Performs genomic prediction of hybrid performance using eight GS methods including GBLUP, BayesB, RKHS, PLS, LASSO, Elastic net, Random forest and XGBoost. It also provides fast cross-validation and mating design scheme for training population (Xu S et al (2016) <doi:10.1111/tpj.13242>; Xu S (2017) <doi:10.1534/g3.116.038059>).

Version: 1.2.0
Depends: R (≥ 3.6.0)
Imports: BGLR, pls, glmnet, randomForest, xgboost, foreach, doParallel, parallel
Published: 2021-08-16
Author: Yang Xu, Guangning Yu, Yanru Cui, Shizhong Xu, Chenwu Xu
Maintainer: Yang Xu <xuyang_89 at 126.com>
License: GPL-3
NeedsCompilation: no
CRAN checks: predhy results

Documentation:

Reference manual: predhy.pdf

Downloads:

Package source: predhy_1.2.0.tar.gz
Windows binaries: r-devel: predhy_1.2.0.zip, r-release: predhy_1.2.0.zip, r-oldrel: predhy_1.2.0.zip
macOS binaries: r-release (arm64): predhy_1.2.0.tgz, r-release (x86_64): predhy_1.2.0.tgz, r-oldrel: predhy_1.2.0.tgz
Old sources: predhy archive

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