MTAFS-package: MTAFS

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

MTAFS

Description

This package provides functions for multi-trait analysis of GWAS summary statistics.

Details

Package:	MTAFS
Type:	Package
Version:	1.0.0
Date:	2022-05-11
License:	GPL (>= 2)
LazyLoad:	yes

This package contains two main functions, eigenDecomp and MTAFS. eigenDecomp conducts eigendecompositions and its output is used by MTAFS. MTAFS analyzes multiple GWAS summary statistics and return p-values.

Author(s)

Qiaolan Deng, Chi Song, Shili Lin

Maintainer: Qiaolan Deng <[e-mail]>

References

Deng, Qiaolan, Chi Song, and Shili Lin. "An Adaptive and Robust Method for Multi-trait Analysis of Genome-wide Association Studies Using Summary Statistics." arXiv preprint arXiv:2204.09751 (2022).

See Also

MTAFS, eigenDecomp.

Examples

# load a simulated dataset
data("gwasArea")
Z <- gwasArea

# estimate the variance-covariance matrix
Rhat <- cov(Z)


## the default setting

# conduct eigendecomposition
eigRhat <- eigenDecomp(Rhat)

# use MTAFS to analyze the summary statistics
pMTAFS <- MTAFS(Z, eigRhat)
head(pMTAFS)


## user-defined setting

# conduct eigendecomposition
eigRhat2 <- eigenDecomp(Rhat, varExp = c(0.4,0.6,0.8))

# use MTAFS to analyze the summary statistics
pMTAFS2 <- MTAFS(Z, eigRhat2)
head(pMTAFS2)

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