rrBlupRotation: rrBlupRotation - linear transformation for the adjusted means...

In rrBlupMethod6: Re-parametrization of RR-BLUP to allow for a fixed residual variance

Description

This function implements the rotation described in Piepho et al. (2011) thus the assumption of R = I sigma2 in function rrBlupM6 is satisfied.

Usage

rrBlupRotation(y, X = matrix(1,nrow=n, ncol=1), Z, R)

Arguments

y	Numeric vector with adjusted means of the genotypes.
X	Design matrix of fixed effects, including the intercept. By default, this is an all 1 column vector for the intercept.
Z	Matrix assigning marker genotypes to phenotypes in y. The dimension of the matrix must be no. phenotypes (rows) times no. markers (columns). The coding must be 1 and -1 for the two homozygous genotypes.
R	Variance-covariance structure of the adjusted means

Details

Please see Piepho et al. (2011) and Schulz-Streeck et al. (2012) for details on the rotation approach. The variance-covariance structure R can, for example, be obtained with the function vcov from fitted (mer) model objects, or with the output option COV for the LSMEANS statement in PROC MIXED in SAS.

Value

A list with three components

y_tilda

Numeric vector with the rotated adjusted means,

X_tilda

Rotated design matrix of the fixed effects and

Z_tilda

Rotated design matrix with the marker information

Author(s)

Torben Schulz-Streeck, Boubacar Estaghvirou, Frank Technow

See Also

rrBlupMethod6,rrBlupM6

Examples

## simulate a small data set (250 observations, 300 markers)
set.seed(3421475)
N <- 250
M <- 300

Z <- matrix(sample(c(1,-1),N * M, replace = TRUE),
            nrow = N,
            ncol = M)

## marker effects
u <- rnorm(M, 0, sqrt(1/M))

sig2e <- 1
y <- Z %*% u + rnorm(N,0,sqrt(sig2e))

## simulate a random variance-covariance structure of the adjusted means
## (Note that this is just for demonstration purposes, the values are
## non-sensical!)
R <- matrix(rnorm(N*N),N,N) 
diag(R) <- abs(diag(R))
R <- R + t(R)


## rotate
out_r <- rrBlupRotation(y, Z = Z, R = R)

## use rotated y,X and Z for computing marker effects and set sig2e = 1
out_RRBLUP_m6_r <- rrBlupM6(y = out_r$y_tilda,
                            X = out_r$X_tilda,
                            Z = out_r$Z_tilda,
                            sig2e = 1,
                            chunks = 4)

rrBlupMethod6 documentation built on May 2, 2019, 7:38 a.m.