We used Leafcutter20 to obtain the proportion of intron defining reads to the total number of reads from the intron cluster it belongs to. This intron ratio describes how often an intron is used relative to other introns in the same cluster. We used WASP60 to remove read-mapping biases caused by allele-specific reads. This is particularly significant when a variant is covered by reads that also span intron junctions as it can lead to a spurious association between the variant and intron excision level estimates. We standardized the intron ratio values across individuals for each intron and quantile normalize across introns61 and used this as our phenotype matrix. We used linear regression (as implemented in fastQTL)26 to test for associations between SNP dosages (MAF ≥ 0.01) within 100kb of intron clusters and the rows of our phenotype matrix that correspond 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
