Meta-analysis for Discovering Rare-Variant Associations: Statistical Methods and Software Programs.

ABSTRACT: There is heightened interest in using next-generation sequencing technologies to identify rare variants that influence complex human diseases and traits. Meta-analysis is essential to this endeavor because large sample sizes are required for detecting associations with rare variants. In this article, we provide a comprehensive overview of statistical methods for meta-analysis of sequencing studies for discovering rare-variant associations. Specifically, we discuss the calculation of relevant summary statistics from participating studies, the construction of gene-level association tests, the choice of transformation for quantitative traits, the use of fixed-effects versus random-effects models, and the removal of shadow association signals through conditional analysis. We also show that met

SUBMITTER: Tang ZZ 

PROVIDER: S-EPMC4571037 | biostudies-literature | 2015 Jul

REPOSITORIES: biostudies-literature