MTGS (version 0.1.0)

MTGS.mrce: Genomic Selection using Multivariate Regression with Covariance Estimation (MRCE)

Description

Calculates the Genomic Estimated Breeding Value based on MRCE method.

Usage

MTGS.mrce(X, Y, r)

Arguments

X

X is a design matrix of marker genotype of size n<U+00D7>p, where n are no of Individuals under study (i.e. genotype, lines) and p are no of markers.

Y

Y is matrix of individuals (n) with their phenotypic traits (q) of size n<U+00D7>q.

r

r is fraction of testing data (ranges from (0-1)) used during model fitting(suppose if one want to use 75% of data for model training and remaining 25% for model testing so one has to define r=0.25).

Value

$Bhat Estimate of marker effects for different phenotypic traits(q).

$muhat Estimate of intercept for different phenotypic traits(q).

$Pred GEBVs for genotype under study.

References

Rothman, A.J., Levina, E., and Zhu, J. 2010. Sparse multivariate regression with covariance estimation. J. Comput. Graph. Stat. 19, 947-962.

Adam J. Rothman (2017). MRCE: Multivariate Regression with Covariance Estimation. R package version 2.1. https://CRAN.R-project.org/package=MRCE.

Examples

# NOT RUN {
library(MTGS)
data(brassica_data)
X<-brassica_data[,1:100]
Y<-brassica_data[,101:103]
r<-0.25
MTGS.mrce(X,Y,r)

# }