SUPPA2 provides fast, accurate, and uncertainty-aware differential splicing analysis across multiple conditions

Despite the many approaches to study differential splicing from RNA-seq, many challenges remain unsolved, including computing capacity and sequencing depth requirements. Here we present SUPPA2, a new method for differential splicing analysis that addresses these challenges and enables streamlined analysis across multiple conditions taking into account biological variability. Using experimental and simulated data SUPPA2 achieves higher accuracy compared to other methods; especially at low sequencing depth and short read length, with important implications for cost-effective use of RNA-seq for splicing; and was able to identify novel Transformer2-regulated exons. We further analyzed two differentiation series to support the applicability of SUPPA2 beyond binary comparisons. This identified clusters of alternative splicing events enriched in microexons induced during differentiation of bipolar neurons, and a cluster enriched in intron retention events that are present at late stages during erythroblast differentiation. Our data suggest that SUPPA2 is a valuable tool for the robust investigation of the biological complexity of alternative splicing.