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, XGBoost and LightGBM. 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, LightGBM: light gradient boosting machine. It also provides fast cross-validation and mating design scheme for training population (Xu S et al (2016) ; Xu S (2017) ). A complete manual for this package is provided in the manual folder of the package installation directory. You can locate the manual by running the following command in R: system.file("manual", package = "predhy.GUI").