Get_zeta: Calculate Covariances of Z-scores between Traits from...
In MTAR: Multi-Trait Analysis of Rare-Variant Association Study

Description Usage Arguments Value Author(s) Examples

This function allows you to estimate the matrix ζ to adjust for the potential sample overlap in the data set. Here we applied LD pruning (r^2 < 0.1 in 500kb region) on 1000 Genome genotype dataset (hg19) as a list of reference independent SNPs. The SNP ID is chr:pos.

1	Get_zeta(Zscore, pval_cutoff = 0.05, Indp_common_snp)

`Zscore`	a numeric list, each sublist containing a vector of Z scores of SNPs with minor allele frequency (MAF) larger than 0.05. The chr:pos for each SNP is required.
`pval_cutoff`	a numeric value indicating the cutoff threshold of p-values. The default value is 0.05. Variants with p-value less than or equal to this threshold will be automatically removed.
`Indp_common_snp`	a numeric list of independent common SNPs

A K \times K matrix ζ, where K is the number of traits.

Lan Luo

data(zeta.example)
attach(zeta.example)
# Downloading independent common SNPs from 1000Genome data set.
githubURL <- "https://github.com/lan/MTAR/blob/master/indp_snps.1KG.rda?raw=true"
utils::download.file(githubURL,"1kgfile")
load("1kgfile")
zeta1 <- Get_zeta(Zscore = Zscore, Indp_common_snp = indp_snps.1KG)
zeta1
detach(zeta.example)