To detect alternative mRNA associations with AUD we used Leafcutter version 0.2.923. Leafcutter is a powerful transcriptome-wide splicing method that uses a Dirichlet-multinomial generalized linear regression to identify differentially spliced genes. A differentially spliced gene generally is composed of multiple clusters, each of which includes various alternative splicing events, such as exon-skipping (see Fig. 1), intron retention, alternative acceptor or alternative donor splice sites, which we annotated with the Vertebrate Alternative Splicing and Transcription Database (https://vastdb.crg.eu/wiki/Main_Page). Each splicing event corresponds to a change in percent spliced in (ΔPSI or dPSI) metric. In our AUD analyses, a positive ΔPSI for an exon skipping event would suggest that an individual with AUD is more likely to skip a certain exon than someone without AUD. We utilized the default filtering parameters of Leafcutter that filtered out splicing clusters with < 5 samplers per intron, < 3 samples per group, and required at least 20 reads, which resulted in 18,685 unique genes across human brain regions. Human differential splicing analyses covaried for sex, age, brain pH, PMI, and smoking status. Note leafcutter performs analyses
