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 that addresses these challenges, and enables streamlined analysis across multiple conditions taking into account biological variability. Using experimental and simulated data, we show that SUPPA2 achieves higher accuracy compared to other methods, especially at low sequencing depth and short read length. We use SUPPA2 to identify novel Transformer2-regulated exons, novel microexons induced during differentiation of bipolar neurons, and novel intron retention events during erythroblast differentiation.

This work was supported by the MINECO and FEDER with grants BIO2014-52566-R and BIO2017-85364-R, by AGAUR with grants SGR2014-1121 and SGR2017-1020, by BBSRC (BB/P006612/1), and by Breast Cancer Now (2014NovPR355). GH is a BBSRC-funded PhD student.