MTAR (version 0.1.1)

Get_zeta: Calculate Covariances of Z-scores between Traits from Overlapping Samples

Description

This function allows you to estimate the matrix \(\zeta\) 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.

Usage

Get_zeta(Zscore, pval_cutoff = 0.05, Indp_common_snp)

Arguments

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

Value

A \(K \times K\) matrix \(\zeta\), where \(K\) is the number of traits.

Examples

# NOT RUN {
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)
# }