A Novel Combinatorial Method for Estimating Transcript Expression with RNA-Seq: Bounding the Number of Paths

TL;DR

This paper introduces Traph, a new combinatorial algorithm for estimating transcript expression from RNA-Seq data, which efficiently handles the NP-hard problem of bounding the number of paths explaining the splicing graph.

Contribution

It presents a fast dynamic programming algorithm for a bounded-paths transcript estimation problem and implements heuristics that outperform existing tools on real and simulated data.

Findings

Traph achieves better performance than Cufflinks, IsoLasso, and SLIDE.

The algorithm effectively handles the NP-hard problem with practical heuristics.

Traph is available as an open-source tool for transcript quantification.

Abstract

RNA-Seq technology offers new high-throughput ways for transcript identification and quantification based on short reads, and has recently attracted great interest. The problem is usually modeled by a weighted splicing graph whose nodes stand for exons and whose edges stand for split alignments to the exons. The task consists of finding a number of paths, together with their expression levels, which optimally explain the coverages of the graph under various fitness functions, such least sum of squares. In (Tomescu et al. RECOMB-seq 2013) we showed that under general fitness functions, if we allow a polynomially bounded number of paths in an optimal solution, this problem can be solved in polynomial time by a reduction to a min-cost flow program. In this paper we further refine this problem by asking for a bounded number k of paths that optimally explain the splicing graph. This problem becomes NP-hard in the strong sense, but we give a fast combinatorial algorithm based on dynamic programming for it. In order to obtain a practical tool, we implement three optimizations and heuristics, which achieve better performance on real data, and similar or better performance on simulated data, than state-of-the-art tools Cufflinks, IsoLasso and SLIDE. Our tool, called Traph, is available at http://www.cs.helsinki.fi/gsa/traph/