getK.rn: Environmental kernels for genomic prediction

In gcostaneto/envirotype: GIS platforms to support envirorytping in breeding programs

Description

Builds empirical environmental kernels for genomic prediction

Usage

getK.rn(.Kc = NULL, .Kg = NULL, .Y = NULL, .X = NULL,
  .type = NULL, .intrandom = NULL)

Arguments

.Kc	Kernel of environmental covariates (see envK function)
.Kg	Kernel of environmental covariates
.Y	data.frame Phenotypic data with three columns. The first column is a factor for environments, the second column is a factor identifying genotypes, and the third column contains the trait of interest
.X	Marker matrix with individuals in rows and markers in columns. Missing markers are not allowed.
.type	Kernel to be created internally. Methods currently implemented are the Reaction Norm (RN) and Random Covariate (RC).
.intrandom	if TRUE, kernel related to random intercept of genotype is included.

Author(s)

Germano Martins F Costa Neto <[e-mail]>

References

Jarquín, D. et al (2014). A reaction norm model for genomic selection using high-dimensional genomic and environmental data. Theoretical and Applied Genetics, 127(3), 595–607. https://doi.org/10.1007/s00122-013-2243-1

Bandeira e Souza, M et al. (2017). Genomic-Enabled Prediction in Maize Using Kernel Models with Genotype × Environment Interaction. G3, 7(June), g3.117.042341. https://doi.org/10.1534/g3.117.042341

Granato, I. et al. (2018). BGGE : A New Package for Genomic-Enabled Prediction Incorporating Genotype x Environment Interaction Models, 8(September), 3039–3047. https://doi.org/10.1534/g3.118.200435

See Also

envK

gcostaneto/envirotype documentation built on Feb. 19, 2020, 10:36 p.m.