input_geno

<p>Genotypic data of 348 maize inbred lines in Hapmap format with double bit.</p>

datasets

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").

Yuxiang Zhang

predhy.GUI

Genomic Prediction of Hybrid Performance with Graphical User
Interface

Yang Xu

Guangning Yu

Yanru Cui

Shizhong Xu

Chenwu Xu

input_geno function

<p>A data frame with 4979 rows and 359 columns.</p>

Format

Genotype in Hapmap Format — input_geno

Genotype in Hapmap Format

input_geno: Genotype in Hapmap Format

Description

Usage

Arguments

Format