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bioRxiv · 10.1101/477828

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

Trochet, H.·Pirinen, M.·Band, G.·Jostins, L.·Wellcome Trust Case-Control Consortium 2,·McVean, G.·Spencer, C. C. A.
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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.

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Trochet, H., Pirinen, M., Band, G., Jostins, L., Wellcome Trust Case-Control Consortium 2,, McVean, G., Spencer, C. C. A.. 2018-11-24. Bayesian meta-analysis across genome-wide association studies of diverse phenotypes. https://doi.org/10.1101/477828

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