predhy.GUI: Genomic Prediction of Hybrid Performance with Graphical User Interface

Performs genomic prediction of hybrid performance using eight GS methods including GBLUP, BayesB, RKHS, PLS, LASSO, Elastic net, Random forest and XGBoost. GBLUP: genomic best liner unbiased prediction, RKHS: reproducing kernel Hilbert space, PLS: partial least squares regression, LASSO: least absolute shrinkage and selection operator, XGBoost: extreme gradient boosting. 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: 1.0
Depends: R (≥ 4.1.0)
Imports: shiny, data.table, DT, predhy (≥ 1.2.1), BGLR, pls, glmnet, randomForest, xgboost, foreach, doParallel, parallel, htmltools
Published: 2023-02-21
Author: Yang Xu [aut], Guangning Yu [aut], Yuxiang Zhang [aut, cre], Yanru Cui [ctb], Shizhong Xu [ctb], Chenwu Xu [ctb]
Maintainer: Yuxiang Zhang <yuxiangzhang_99 at>
License: GPL-3
NeedsCompilation: no
CRAN checks: predhy.GUI results


Reference manual: predhy.GUI.pdf


Package source: predhy.GUI_1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): predhy.GUI_1.0.tgz, r-oldrel (arm64): predhy.GUI_1.0.tgz, r-release (x86_64): predhy.GUI_1.0.tgz, r-oldrel (x86_64): predhy.GUI_1.0.tgz


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