cgrm.A

lambda

boolean, diagonal elements of A according to Yang et al. (2010)

yang

Based on a marker matrix $\mathbf{X}$ with {-1,0,1} - coding that will be centered column-wise and a shrinkage parameter $\lambda$, <code>cgrm.A</code> returns
  the following additive genomic relationship matrix according to VanRaden (2008):
                             $$\mathbf{G} = (1-\lambda) \frac{\mathbf{X X}^{'}}{\sum\limits_{i=1}^n 2 p_i q_i}  + \mathbf{I}\lambda$$

Genomic Relationship

Frequently used methods in genomic applications with emphasis on parallel computing (OpenMP).
At its core, the package has a Gibbs Sampler that allows running univariate linear
mixed models that have both, sparse and dense design matrices. The parallel sampling method
in case of dense design matrices (e.g. Genotypes) allows running Ridge Regression or BayesA for
a very large number of individuals. The Gibbs Sampler is capable of running Single Step Genomic Prediction models.
In addition, the package offers parallelized functions for common tasks like genome-wide
association studies and cross validation in a memory efficient way.

cgrm.A: Additive Genomic Relationship Matrix

Description

Usage

Arguments

Value

Details

References

See Also

Examples