A GIN prioritization score represents an order of magnitude change in P-value from a test for association. For example, a SNP with an overall score of 1 and a P-value of 0.01 has the same priority in the GIN model as a SNP with a score of 0 and P-value of 0.001. This allows the user to specify their priority for testing certain biological hypotheses by weighing that priority against evidence for genotype–phenotype correlation. Typically there are few P-values from a GWAS <10−8, so a score of ≥8 essentially guarantees a SNP will have extremely high priority after GIN prioritization. The effect of a score on rank, however, depends on the overall distribution of scores the user has specified for their set of SNPs. For example, there is no effect on rank if all SNPs receive a score of 8; the rankings are the same as by P-value alone [for more information see the discussion of normalized weights in (4)]. When deciding on a score, it is helpful to use a frame of reference. By default, we prioritize SNPs in
