G: Genomic additive relationship matrix for the Jersey dataset.
Description
A matrix, similar to this was used in Gianola et al. (2011) for predicting
milk, fat and protein production in Jersey cows. In this software version we do not center the incidence
matrix for the additive effects.
$G=\frac{X_a X_a'}{2\sum_{j=1}^p p_j (1-p_j)},$
where
- $X_a$is the design matrix for allele substitution effects for additivity.
- $p_j$ is the frecuency of the second allele at locus $j$ and $q_j=1-p_j$.
source
University of Wisconsin at Madison, USA.References
Gianola, D. Okut, H., Weigel, K. and Rosa, G. 2011.
"Predicting complet quantitative traits with Bayesian neural networks:
a case study with Jersey cows and wheat". BMC Genetics.