cgrm.D | R Documentation |
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 \lambda
, cgrm.D
returns
the following dominance genomic relationship matrix according to Su et al. (2012):
\mathbf{G} = (1-\lambda) \frac{\mathbf{X X}^{'}}{\sum\limits_{i=1}^n 2 p_i q_i(1-2 p_i q_i) } + \mathbf{I}\lambda
The additive marker coefficients will be used to compute dominance coefficients as: 1-abs(X)
cgrm.D(X, lambda=0)
X |
marker matrix |
lambda |
numeric scalar, shrinkage parameter |
...
Dominance relationship matrix with dimension nrow(X)
Claas Heuer
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
cgrm
, cgrm.A
.
# generate random data
rand_data(100,500)
D <- cgrm.D(M,lambda=0.01)
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