rrBLUP

This package has been developed primarily for genomic prediction with mixed models (but it can also do genome-wide association mapping with <code><a href="/link/GWAS?package=rrBLUP&version=4.2" rd-options="" data-mini-rdoc="rrBLUP::GWAS">GWAS</a></code>). The heart of the package is the function <code><a href="/link/mixed.solve?package=rrBLUP&version=4.2" rd-options="" data-mini-rdoc="rrBLUP::mixed.solve">mixed.solve</a></code>, which is a general-purpose solver for mixed models with a single variance component other than the error.  Genomic predictions can be made by estimating marker effects (RR-BLUP) or by estimating line effects (G-BLUP). In Endelman (2011) I made the poor choice of using the letter G to denotype the genotype or marker data.  To be consistent with Endelman (2011) I have retained this notation in <code><a href="/link/kinship.BLUP?package=rrBLUP&version=4.2" rd-options="" data-mini-rdoc="rrBLUP::kinship.BLUP">kinship.BLUP</a></code>.  However, that function has now been superseded by <code><a href="/link/kin.blup?package=rrBLUP&version=4.2" rd-options="" data-mini-rdoc="rrBLUP::kin.blup">kin.blup</a></code> and <code><a href="/link/A.mat?package=rrBLUP&version=4.2" rd-options="" data-mini-rdoc="rrBLUP::A.mat">A.mat</a></code>, the latter being a utility for estimating the additive relationship matrix (A) from markers.  In these newer functions I adopt the usual convention that G is the genetic covariance (not the marker data), which is also consistent with the notation in Endelman and Jannink (2012).

rrBLUP-package

Software for genomic prediction with the RR-BLUP mixed
        model. One application is to estimate marker effects by ridge
        regression; alternatively, BLUPs can be calculated based on an
        additive relationship matrix or a Gaussian kernel.

rrBLUP-package: Ridge regression and other kernels for genomic selection

Description

Arguments

References