MGAS: a powerful tool for multivariate gene-based genome-wide association analysis.

ABSTRACT:

Motivation

Standard genome-wide association studies, testing the association between one phenotype and a large number of single nucleotide polymorphisms (SNPs), are limited in two ways: (i) traits are often multivariate, and analysis of composite scores entails loss in statistical power and (ii) gene-based analyses may be preferred, e.g. to decrease the multiple testing problem.

Results

Here we present a new method, multivariate gene-based association test by extended Simes procedure (MGAS), that allows gene-based testing of multivariate phenotypes in unrelated individuals. Through extensive simulation, we show that under most trait-generating genotype-phenotype models MGAS has superior statistical power to detect associated genes compared with gene-based analyses of univari

SUBMITTER: Van der Sluis S 

PROVIDER: S-EPMC4382905 | biostudies-literature | 2015 Apr

REPOSITORIES: biostudies-literature