RVS.params: Compute parameters for (weighted linear) kernel association...

In baolinwu/KATSP: Sample size and power calculation for variant-set association test with SKAT

Description

Assume a linear model for continous traits, Y=α+Gβ+ε. Input population genotype covariance matrix (VLD), variant weights (Wv), variant effect sizes (Ves, i.e., β), and sample size (n). This function computes the asymptotic mixture of 1-DF chi-square distributions, ∑_iλ_iχ_1^2(δ_i).

Usage

RVS.params(n = 2000, VLD, Ves, MAF, Wv = NULL, W.beta = c(1, 25))

Arguments

n	sample size of a planned study
VLD	population genotype covariance matrix for the variant set
Ves	variant effect sizes
MAF	minor allele freqs of variant set
Wv	variant weights
W.beta	beta dist parameters to compute variant weights based on MAF when Wv is not specified.

Value

lambda

mixing cofficients of 1-DF chi-square mixtures

delta

non-centrality parameters of 1-DF chi-square mixtures

References

Wu,B. and Pankow,J.S. (2016) On sample size and power calculation for variant set-based association tests. /AHG/, 80(2), 136-143.

baolinwu/KATSP documentation built on May 29, 2019, 12:04 p.m.