FlipFlop: Fast Lasso-based Isoform Prediction as a Flow Problem

FlipFlop implements a fast method for de novo transcript discovery and abundance estimation from RNA-Seq data. It differs from Cufflinks by simultaneously performing the transcript and quantitation tasks using a penalized maximum likelihood approach, which leads to improved precision/recall. Other softwares taking this approach have an exponential complexity in the number of exons in the gene. We use a novel algorithm based on network flow formalism, which gives us a polynomial runtime. In practice, FlipFlop was shown to outperform penalized maximum likelihood based softwares in terms of speed and to perform transcript discovery in less than 1/2 second even for large genes.