Genomic Prediction of Hybrid Performance with Graphical User Interface R package predhy.GUI version 2.1.1 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) <doi:10.1111/tpj.13242>; Xu S (2017) <doi:10.1534/g3.116.038059>). 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"). Software Depends: R (>= 4.1.0) Imports: shiny, data.table, DT, predhy(>= 2.1.2), BGLR, pls, glmnet, xgboost, lightgbm, foreach, doParallel, parallel, htmltools Yuxiang Zhang <yuxiangzhang_99@foxmail.com> Comprehensive R Archive Network (CRAN) Yang Xu [aut], Guangning Yu [aut], Yuxiang Zhang [aut, cre], Yanru Cui [ctb], Shizhong Xu [ctb], Chenwu Xu [ctb] GPL-3 2025-11-03 application/tgz https://CRAN.R-project.org/package=predhy.GUI doi:10.32614/CRAN.package.predhy.GUI