Improving the coverage of credible sets in Bayesian genetic fine-mapping.

ABSTRACT: Genome Wide Association Studies (GWAS) have successfully identified thousands of loci associated with human diseases. Bayesian genetic fine-mapping studies aim to identify the specific causal variants within GWAS loci responsible for each association, reporting credible sets of plausible causal variants, which are interpreted as containing the causal variant with some "coverage probability". Here, we use simulations to demonstrate that the coverage probabilities are over-conservative in most fine-mapping situations. We show that this is because fine-mapping data sets are not randomly selected from amongst all causal variants, but from amongst causal variants with larger effect sizes. We present a method to re-estimate the coverage of credible sets using rapid simulations based on the obser

SUBMITTER: Hutchinson A 

PROVIDER: S-EPMC7179948 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature