getResiduals {pcgen}

Residuals from the GBLUP

Description

Residuals from the best linear unbiased predictor of the genetic effects (GBLUP), which is computed given REML-estimates of the variance components.

Usage

 getResiduals(suffStat, covariates = NULL, cov.method = "uni", K = NULL) 

Arguments

suffStat

A data.frame, of which the first column is the factor G (genotype), and subsequent columns contain the traits. The name of the first column should be G.

covariates

A data.frame containing covariates, that should always be used in each conditional independence test. Should be either NULL (default) or a data.frame with the same number of rows as suffStat. An intercept is already included for each trait in suffStat; covariates should not contain a column of ones.

cov.method

(A string, specifying which method should be used to compute the GBLUP. Options are "us" (unstructured multi-trait model fitted using sommer) and "uni" (based on univariate GBLUPs). Default is "uni").

K

A genetic relatedness matrix. If NULL (default), independent genetic effects are assumed.

Details

If cov.method = "uni", the GBLUP and the residuals are computed separately for each trait in suffStat. The covariance of each trait is then assumed to be

\sigma_G^2 Z K Z^t + \sigma_E^2 I_n

where Z is a binary incidence matrix, assigning plants or plots to genotypes. Z is based on the first column in suffStat. If there is a single observation per genotype (typically a genotypic mean), Z is the identity matrix, and the relatedness matrix K should be specified. If there are replicates for at least some of the genotypes, and no K is provided, independent genetic effects are assumed (K will be the identity matrix). It is also possible to have replicates and specify a non-diagonal K. Whenever K is specified, sommer (mmer2) will be used; otherwise lmer (lme4). The mmer2 is also used when cov.method = "us", in which case the multivariate GBLUP is computed, for all traits in suffStat simultaneously. This is only possible for a limited number of traits.

Value

A data-frame with the residuals.

Author(s)

Willem Kruijer and Pariya Behrouzi. Maintainers: Willem Kruijer [e-mail] and Pariya Behrouzi [e-mail]

References

Covarrubias-Pazaran, G., 2016. Genome-assisted prediction of quantitative traits using the R package sommer. PloS one, 11(6), p.e0156744.

Examples

data(simdata)
rs <- getResiduals(suffStat= simdata)