Efficient RNA isoform identification and quantification from RNA-Seq data with network flows

Elsa Bernard, Laurent Jacob, Julien Mairal, Jean-Philippe Vert

Abstract: Several state-of-the-art methods for isoform identification and quantification are based on ℓ 1 -regularized regression, such as the Lasso. However, explicitly listing the—possibly exponentially—large set of candidate transcripts is intractable for genes with many exons. For this reason, existing approaches using the ℓ 1 -penalty are either restricted to genes with few exons or only run the regression algorithm on a small set of preselected isoforms.