MTAFS: Multi-trait analysis of GWAS summary statistics using MTAFS

In Qiaolan/MTAFS: An Adaptive and Robust Method for Multi-trait Analysis of Genome-wide Association Studies Using Summary Statistics

Multi-trait analysis of GWAS summary statistics using MTAFS

Description

Analyze multi-trait GWAS summary statistics and get the p-values of MTAFS

Usage

MTAFS(Z, eigR, weights = NULL, snps = NULL, traits = NULL)

Arguments

Z	A matrix of z scores obtained from GWAS summary statistics, where its row and column correspond to SNP and trait, respectively.
eigR	A list returned by eigenDecomp.
weights	A vector of weights for the Cauchy combination. The defaul is NULL assuming a uniform weight.
snps	A vector of indices of SNPs that are going to be included in an analysis. By default, we include all SNPs in Z.
traits	A vector of indices of traits that are going to be included in an analysis. By default, we include all traits in Z.

Details

MTAFS applies the MTAFS method to GWAS summary statistics. It requires z scores from GWAS summary statistics and returns p-values of MTAFS.

Value

MTAFS returns a matrix of p-values, where its row correspond to SNP. The first few columns are p-values obtained by using a specific number of eigenvalues and the last column consists of the p-values of MTAFS which are the Cauchy combination of the first few columns.

Author(s)

Qiaolan Deng

References

Deng, Q., Song, C., & Lin, S. (2022). An Adaptive and Robust Method for Multi-trait Analysis of Genome-wide Association Studies Using Summary Statistics. arXiv preprint arXiv:2204.09751.

See Also

eigenDecomp

Examples

data("gwasArea")
Z <- gwasArea
Rhat <- cov(Z)
eigR <- eigenDecomp(estR = Rhat)
p_MTAFS <- MTAFS(Z,eigR)
head(p_MTAFS)

Qiaolan/MTAFS documentation built on Feb. 26, 2023, 7:02 p.m.