We tested the genetic associations between five SNPs and three smoking-related behaviors in three groups (the combined sample, AAs and EAs), requiring adjustment of the α level to avoid inflation of the type 1 error rate. Because traditional Bonferroni correction is too conservative when different tests are correlated, we used a permutation-based correction procedure. Briefly, we randomly reshuffled the phenotypes and genotypes while keeping the phenotype and genotype correlation structure unchanged. In each randomly permuted sample, we ran the association test in exactly the same way as in the real dataset and a minimum P-value was recorded. This process was repeated 10,000 times and 10,000 minimum P-values were obtained to get the empirical distribution of the minimum P-values. For each point-wise association test P-value, the empirical P-value corrected for multiple testing was estimated by counting the proportion of the minimum P-values less than or equal to the observed one across the 10,000 randomly permuted samples.
