lme4breeding (version 1.0.50)

A.mat: Additive relationship matrix

Description

Calculates the realized additive relationship matrix.

Usage

A.mat(X,min.MAF=NULL)

Value

If return.imputed = FALSE, the \(n \times n\) additive relationship matrix is returned.

If return.imputed = TRUE, the function returns a list containing

$A

the A matrix

Arguments

X

Matrix (\(n \times m\)) of unphased genotypes for \(n\) lines and \(m\) biallelic markers, coded as {-1,0,1}. Fractional (imputed) and missing values (NA) are allowed.

min.MAF

Minimum minor allele frequency. The A matrix is not sensitive to rare alleles, so by default only monomorphic markers are removed.

Details

For vanraden method: the marker matrix is centered by subtracting column means \(M= X - ms\) where ms is the coumn means. Then \(A=M M'/c\), where \(c = \sum_k{d_k}/k\), the mean value of the diagonal values of the \(M M'\) portion.

References

Giovanny Covarrubias-Pazaran (2024). lme4breeding: enabling genetic evaluation in the age of genomic data. To be submitted to Bioinformatics.

Douglas Bates, Martin Maechler, Ben Bolker, Steve Walker (2015). Fitting Linear Mixed-Effects Models Using lme4. Journal of Statistical Software, 67(1), 1-48.

See Also

lmebreed -- the core function of the package

Examples

## random population of 200 lines with 1000 markers
X <- matrix(rep(0,200*1000),200,1000)
for (i in 1:200) {
  X[i,] <- ifelse(runif(1000)<0.5,-1,1)
}

A <- A.mat(X)

 # \donttest{
## take a look at the Genomic relationship matrix 
 colfunc <- colorRampPalette(c("steelblue4","springgreen","yellow"))
 hv <- heatmap(A[1:15,1:15], col = colfunc(100),Colv = "Rowv")
 str(hv)
 # }