SCIENCE@home

Bayesian meta-analysis across genome-wide association studies of diverse phenotypes

H. Trochet,M. Pirinen,G. Band,L. Jostins,G. McVean,C. Spencer

Published 2018 in bioRxiv

ABSTRACT

Genome-wide association studies (GWAS) are a powerful tool for understanding the genetic basis of diseases and traits, but most studies have been conducted in isolation, with a focus on either a single or a set of closely related phenotypes. We describe MetABF, a simple Bayesian framework for performing integrative meta-analysis across multiple GWAS using summary statistics. The approach is applicable across a wide range of study designs and can increase the power by 50% compared to standard frequentist tests when only a subset of studies have a true effect. We demonstrate its utility in a meta-analysis of 20 diverse GWAS which were part of the Wellcome Trust Case-Control Consortium 2. The novelty of the approach is its ability to explore, and assess the evidence for, a range of possible true patterns of association across studies in a computationally efficient framework.

PUBLICATION RECORD

CITATION MAP

EXTRACTION MAP

CLAIMS

  • No claims are published for this paper.

CONCEPTS

  • No concepts are published for this paper.

REFERENCES

Showing 1-42 of 42 references · Page 1 of 1

CITED BY

Showing 1-26 of 26 citing papers · Page 1 of 1