Prior information can be harnessed in multiple ways to increase the power of genetic association testing. While there are robust developments in methodology that allow for the inclusion of functional information, we highlight an existing approach that incorporates functional information while correcting for multiple testing. The weighted FDR (False Discovery Rate) allows for the inclusion of a prior value in the FDR (Roeder, Bacanu, Wasserman, & Devlin, 2006). This prior allows additional information (previous GWAS findings, biological plausibility, etc) to be included as a weight in the calculation of the FDR potentially influencing the relative ranks of p-values of a new set of analyses. For instance, investigators can up-weight SNPs with evidence a significant impact on expression or methylation variation in the brain. The approach was recently used, with success, in an ‘informed GWAS’, or iGWAS, to include prior information from previous genome-wide scans in a novel analysis (Fortney et al., 2015).
