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Calculates the realized epistatic relationship matrix of second order (additive x additive, additive x dominance, or dominance x dominance).
E.mat(X,min.MAF=NULL,max.missing=NULL,impute.method="mean",tol=0.02,
n.core=1,shrink=FALSE,return.imputed=FALSE, type="A#A", ploidy=2)
Matrix (
Minimum minor allele frequency. The A matrix is not sensitive to rare alleles, so by default only monomorphic markers are removed.
Maximum proportion of missing data; default removes completely missing markers.
There are two options. The default is "mean", which imputes with the mean for each marker. The "EM" option imputes with an EM algorithm (see details).
Specifies the convergence criterion for the EM algorithm (see details).
Specifies the number of cores to use for parallel execution of the EM algorithm (use only at UNIX command line).
Set shrink=TRUE to use the shrinkage estimation procedure (see Details).
When TRUE, the imputed marker matrix is returned.
An argument specifying the type of epistatic relationship matrix desired. The default is the second order epistasis (additive x additive) type="A#A". Other options are additive x dominant (type="A#D"), or dominant by dominant (type="D#D").
The ploidy of the organism. The default is 2 which means diploid but higher ploidy levels are supported.
If return.imputed = FALSE, the
If return.imputed = TRUE, the function returns a list containing
the E matrix
the imputed marker matrix
it is computed as the Hadamard product of the epistatic relationship matrix (A); E=A#A.
Covarrubias-Pazaran G (2016) Genome assisted prediction of quantitative traits using the R package sommer. PLoS ONE 11(6): doi:10.1371/journal.pone.0156744
Su G, Christensen OF, Ostersen T, Henryon M, Lund MS. 2012. Estimating Additive and Non-Additive Genetic Variances and Predicting Genetic Merits Using Genome-Wide Dense Single Nucleotide Polymorphism Markers. PLoS ONE 7(9): e45293. doi:10.1371/journal.pone.0045293
Endelman, J.B., and J.-L. Jannink. 2012. Shrinkage estimation of the realized relationship matrix. G3:Genes, Genomes, Genetics. 2:1405-1413. doi: 10.1534/g3.112.004259
Poland, J., J. Endelman et al. 2012. Genomic selection in wheat breeding using genotyping-by-sequencing. Plant Genome 5:103-113. doi: 10.3835/plantgenome2012.06.0006
The core functions of the package mmer
# NOT RUN {
####=========================================####
####random population of 200 lines with 1000 markers
####=========================================####
X <- matrix(rep(0,200*1000),200,1000)
for (i in 1:200) {
X[i,] <- sample(c(-1,0,0,1), size=1000, replace=TRUE)
}
E <- E.mat(X, type="A#A")
# if heterozygote markers are present can be used "A#D" or "D#D"
# }
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