cgrm.D: Dominance Genomic Relationship Matrix

In cpgen: Parallelized Genomic Prediction and GWAS

Description

Based on a marker matrix \mathbf{X} with {-1,0,1} - out of which a column-wise centered dominance coefficient matrix will be constructed and a shrinkage parameter λ, cgrm.D returns the following dominance genomic relationship matrix according to Su et al. (2012):

\mathbf{G} = (1-λ) \frac{\mathbf{X X}^{'}}{∑\limits_{i=1}^n 2 p_i q_i(1-2 p_i q_i) } + \mathbf{I}λ

The additive marker coefficients will be used to compute dominance coefficients as: 1-abs(X)

Usage

cgrm.D(X, lambda=0)

Arguments

X	marker matrix
lambda	numeric scalar, shrinkage parameter

Details

...

Value

Dominance relationship matrix with dimension nrow(X)

Author(s)

Claas Heuer

References

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

See Also

cgrm, cgrm.A.

Examples

## Not run: 
# generate random data
rand_data(500,5000)

D <- cgrm.D(M,lambda=0.01)

## End(Not run)

cpgen documentation built on May 2, 2019, 8:15 a.m.