GCvr: A robust and efficient LD score regression approach to...

In baolinwu/MTAR: Various Multi-Trait Association tests in R

Description

We follow the Bulik-Sullivan et al. (2015) approach but use a robust LS estimation. The input r2 is the averaged reference LD scores (scaled by the total number of SNPs used to compute the LD scores). The weight W is typically based on the LD scores computed using HapMap3 common SNPs to correct over-counting.

Usage

GCvr(Zs, r2, N1, N2, Nc = 0, W = NULL)

Arguments

Zs	Mx2 matrix of summary Z-statistics for M variants from two GWAS
r2	average reference LD scores for M variants
N1	sample size for the 1st GWAS
N2	sample size for the 2nd GWAS
Nc	overlapped sample size between the two GWAS
W	variant weight

Value

gv

genetic covariance

gc

genetic correlation

r0

estimated intercept, quantifying the marginal trait correlation

h2s

SNP heritabilities

References

Bulik-Sullivan,B.K. et al. (2015) An atlas of genetic correlations across human diseases and traits. Nat. Genet. 47, 1236–1241.

Guo,B. and Wu,B. (2018) Principal component based adaptive association test of multiple traits using GWAS summary statistics. bioRxiv 269597; doi: 10.1101/269597

baolinwu/MTAR documentation built on May 14, 2019, 6:03 a.m.