Meta-analysis of genetic association studies under heterogeneity.

ABSTRACT: In multi-cohort genetic association studies or meta-analysis, associations of genetic variants with complex traits across cohorts may be heterogeneous because of genuine genetic diversity or differential biases or errors. To detect the associations of genes with heterogeneous associations across cohorts, new global fixed-effect (FE) and random-effects (RE) meta-analytic methods have been recently proposed. These global methods had improved power over both traditional FE and RE methods under heterogeneity in limited simulation scenarios and data application, but their usefulness in a wide range of practical situations is not clear. We assessed the performance of these methods for both binary and quantitative traits in extensive simulations and applied them to a multi-cohort association stud

SUBMITTER: Neupane B 

PROVIDER: S-EPMC3476718 | biostudies-literature | 2012 Nov

REPOSITORIES: biostudies-literature