The effectiveness of such ranking can be verified by conducting further testing on genes ranked highly in the analyses. Alternatively, because the design of genome-wide association studies (GWAS) is hypothesis free, this approach offers opportunities to empirically test a ranking method and provide insight into further refinement, and all or most potential candidate genes can be tested in one experiment. If higher ranked genes contain more significant SNPs than a random set of genes, then the utility of a cross-species and platform integration and ranking approach would be demonstrated [12]. In this report, we attempt to implement and evaluate the utility of the approach outlined above by collecting data across species and approaches, summarizing at the gene level, ranking the genes, and testing the rankings in complex traits related to alcoholism and ethanol response. We included data generated from ethanol response experiments because this trait is one of the contributing factors for alcoholism [13].
