The calculations described in the previous paragraph assume that each test of association is independent from the others. However, SNPs within a gene (or even in different genes) can be correlated with one another (i.e., in linkage disequilibrium [LD]). Consequently, in order to increase our confidence in the thresholds for determining enrichment, our primary test for significance was a stringent permutation test that determined an empirical threshold for the number of hits that could be expected from chance. Using RStudio (v0.98.994), individual phenotype data were randomly permuted and paired with preserved genomic data 1000 times for each phenotype among the target sample. We shuffled the phenotypes but preserved the SNPs under examination in order to preserve the LD structure of the genotypes in our target sample. Association analyses (using the SNP-level significance thresholds of 0.05, 0.01, and 0.001) were performed in PLINK (v1.90b3v) on all 1000 permuted data sets for each phenotype, and Z scores were calculated for the shuffled data in the same manner as the observed data. An empirical threshold was drawn at the 95th percentile highest-ranked Z
