To assess the performance of our ranking algorithm and weighting score matrices, we explored whether the ranked genes showed non-random enrichment of significant signals in alcoholism GWAS results. Specifically, we examined enriched association signals of ranked genes in the COGA GWAS [23], one of the largest alcohol dependence GWAS datasets. To increase the effect of our analyses we filtered the data for minor allele frequency, Hardy-Weinberg equilibrium deviation, and failure rate (see section Materials and methods). This resulted in 958,380 SNPs in our follow up analysis, with an observed minimum p-value of 9.5 × 10-7. However, the minimum q-value was 0.605 after False Discovery Rate (FDR) analysis. Of those SNPs approximately 68.7% (658,008/958,380) mapped to the human non-pseudogenes in NCBI Entrez Gene database, and they were used in this study. FDR analysis was then performed on restricted subsets of markers based on gene rank score.
