We used RVTESTS (Zhan, Hu, Li, Abecasis, & Liu, 2016) to perform admixture mapping within each dataset. For each phenotype, the association with the number of African alleles at each locus was tested after adjusting for study specific covariates and a kinship matrix estimated by RVTESTS. For COGA and SAGE, sex and birth cohort were significantly associated with alcohol dependence, and were therefore used as covariates (Lai, Wetherill, Bertelsen, et al., 2019; Lai, Wetherill, Kapoor, et al., 2019). For Yale-Penn and NIAAA, birth cohort was not available, therefore, sex and age were included, as in previous studies (Lai, Wetherill, Bertelsen, et al., 2019; Lai, Wetherill, Kapoor, et al., 2019). Global African ancestry was included as a covariate in all tests, as suggested (Molineros et al., 2013; Parra et al., 2017). Results from each dataset were meta-analyzed with the effect size weighted by the inverse of the estimated standard error using METAL (Willer, Li, & Abecasis, 2010). Since the block sizes were different for each cohort, only the overlapping part of the blocks from each cohort were included in meta-analysis.
