A powerful statistical framework for generalization testing in GWAS, with application to the HCHS/SOL.

ABSTRACT: In genome-wide association studies (GWAS), "generalization" is the replication of genotype-phenotype association in a population with different ancestry than the population in which it was first identified. Current practices for declaring generalizations rely on testing associations while controlling the family-wise error rate (FWER) in the discovery study, then separately controlling error measures in the follow-up study. This approach does not guarantee control over the FWER or false discovery rate (FDR) of the generalization null hypotheses. It also fails to leverage the two-stage design to increase power for detecting generalized associations. We provide a formal statistical framework for quantifying the evidence of generalization that accounts for the (in)consistency between the direc

SUBMITTER: Sofer T 

PROVIDER: S-EPMC5340573 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature