to the intron ratio within each cluster. As covariate, we used the first 3 principal components of the genotype matrix to account for the effect of ancestry plus the first 15 principal components of the phenotype matrix (PSI) to regress out the effect of known and hidden factors. The principal components regress out the technical and biological covariates such as experimental batch, RNA integrity number (RIN), sex, age at death, and post-mortem interval (PMI). To estimate the number of sQTLs at any given false discovery rate (FDR), we ran an adaptive permutation scheme26, which maintains a reasonable computational load by tailoring the number of permutations to the significance of the association. We computed the empirical gene-level p-value for the most significant QTL for each gene. Finally, we applied Benjamini-Hochberg correction on the permutation p-values to extract all significant splicing QTL pairs with an FDR < 0.05.
