Bayesian test for colocalisation between pairs of genetic association studies using summary statistics.

ABSTRACT: Genetic association studies, in particular the genome-wide association study (GWAS) design, have provided a wealth of novel insights into the aetiology of a wide range of human diseases and traits, in particular cardiovascular diseases and lipid biomarkers. The next challenge consists of understanding the molecular basis of these associations. The integration of multiple association datasets, including gene expression datasets, can contribute to this goal. We have developed a novel statistical methodology to assess whether two association signals are consistent with a shared causal variant. An application is the integration of disease scans with expression quantitative trait locus (eQTL) studies, but any pair of GWAS datasets can be integrated in this framework. We demonstrate the value of

SUBMITTER: Giambartolomei C 

PROVIDER: S-EPMC4022491 | biostudies-literature | 2014 May

REPOSITORIES: biostudies-literature