Due to corrections for multiple testing and limited sample sizes, genome-wide association studies (GWAS) often lack the statistical power to discover statistically significant associations between phenotype and genotype (1). Therefore when a single nucleotide polymorphism (SNP) shows relatively strong evidence of genetic association, that is, is among the top signals from the study, the next step is to genotype the SNP in additional independent samples in order to prove the association is not simply due to chance. The strategy for selecting SNPs for additional genotyping could be simple, such as ranking the SNPs by their P-values from statistical tests for association, or somewhat complex if certain biological considerations are taken into account (2). Once a set of SNPs has been confirmed to be associated with the phenotype, the next logical steps include functional experiments that attempt to isolate the precise molecular genetic mechanism, such as the effect of the genetic variant on transcription, which may act by a direct modification to the amino acid sequence or structure of the protein product, or by an effect on a regulatory mechanism. Functional experiments can be very costly, raising the question of how to prioritize SNPs to maximize returns.
