Generalized estimating equations for genome-wide association studies using longitudinal phenotype data.

ABSTRACT: Many longitudinal cohort studies have both genome-wide measures of genetic variation and repeated measures of phenotypes and environmental exposures. Genome-wide association study analyses have typically used only cross-sectional data to evaluate quantitative phenotypes and binary traits. Incorporation of repeated measures may increase power to detect associations, but also requires specialized analysis methods. Here, we discuss one such method-generalized estimating equations (GEE)-in the contexts of analysis of main effects of rare genetic variants and analysis of gene-environment interactions. We illustrate the potential for increased power using GEE analyses instead of cross-sectional analyses. We also address challenges that arise, such as the need for small-sample corrections when th

SUBMITTER: Sitlani CM 

PROVIDER: S-EPMC4321952 | biostudies-literature | 2015 Jan

REPOSITORIES: biostudies-literature