An alternative strategy is to employ more flexible parametric models. For GWAS with case-control designs, we have explored modeling disease associations with gene sets using a class of statistical models called mixed effects models [55,56]. In addition to the fixed effects that model the mean structure (e.g., overall association for a group of genes), these models also include random effects that account for variance and covariance structures in the dataset. Future studies include assessing the feasibility of these models for GWAS with more complex designs.
