wlin.kernel: Weighted Linear Kernel

In xyz5074/DKAT: Dual Kernel-based Association Test

Description

Calculates the weighted linear kernel matrix for genotypes

Usage

 wlin.kernel(X, W.beta) 

Arguments

X	Genotype matrix, each row is a sample and each column is a genetic variant
W.beta	two-dimensional weights as in the beta density function

Details

Let W=diag(w_1,…,w_p) be the diagonal matrix containing the weights of the p genetic variants, where √{w_j}=beta(MAF_j,a_1,a_2), MAF_j is the minor allele frequency of variant j, and (a_1,a_2) are the weights. Then the weighted linear kernel matrix is calculated as K=XWWX^T.

Value

A n by n kernel matrix, where n is the number of subjects.

References

Wu, M. C. et al. (2011). Rare–variant association testing for sequencing data with the sequence kernel associaiton test. The American Journal of Human Genetics, 89, 82–93.

xyz5074/DKAT documentation built on May 4, 2019, 2:28 p.m.