Event-level prediction and quantification of transcript isoforms from RNA-seq data

RNA-seq data are informative for the analysis of known and novel transcript isoforms. While the short length of RNA-seq reads limits the ability to predict and quantify full-length transcripts, short read data are well suited for the analysis of individual alternative transcript events (e.g. inclusion or skipping of a cassette exon). Available event-centric methods typically rely on annotated transcripts and only consider a subset of all possible events. We developed a novel approach for the identification and quantification of alternative transcript events from RNA-seq data, implemented in the SGSeq package.