RNA-seq data were corrected for up to 20 technical covariates, dataset indicator variables and four multidimensional scaling components derived from the genotype data using OLS. In addition, we evaluated the impact of regressing out increasing numbers of PCs and defined the optimal numbers of PCs to remove for each eQTL discovery dataset (Supplementary Note and Supplementary Fig. 7). To identify secondary, tertiary, quaternary and other non-primary cis-eQTLs, we repeated the procedure in an iterative conditional approach, where in each subsequent iteration, we regressed out the cis-eQTL effect of the previous iterations using OLS and identified cis-eQTLs using the residuals, followed by an LD pruning step to circumvent SNP missingness between included cohorts (Supplementary Note).
