Random-effects model aimed at discovering associations in meta-analysis of genome-wide association studies.

ABSTRACT: Meta-analysis is an increasingly popular tool for combining multiple different genome-wide association studies (GWASs) in a single aggregate analysis in order to identify associations with very small effect sizes. Because the data of a meta-analysis can be heterogeneous, referring to the differences in effect sizes between the collected studies, what is often done in the literature is to apply both the fixed-effects model (FE) under an assumption of the same effect size between studies and the random-effects model (RE) under an assumption of varying effect size between studies. However, surprisingly, RE gives less significant p values than FE at variants that actually show varying effect sizes between studies. This is ironic because RE is designed specifically for the case in which there i

SUBMITTER: Han B 

PROVIDER: S-EPMC3146723 | biostudies-literature | 2011 May

REPOSITORIES: biostudies-literature