iReckon: Simultaneous isoform discovery and abundance estimation from RNA-seq data
- Aziz M Mezlini1,
- Eric JM Smith1,
- Marc Fiume1,
- Orion Buske1,
- Gleb Savich2,
- Sohrab Shah3,
- Sam Aparicion3,
- Derek Chiang2,
- Anna Goldenberg4 and
- Michael Brudno1,5
- 1 University of Toronto;
- 2 University of North Carolina;
- 3 BC Cancer Agency;
- 4 Hospital for Sick Children, Toronto
- ↵* Corresponding author; email: brudno{at}cs.toronto.edu
Abstract
High throughput RNA sequencing (RNA-seq) promises to revolutionize our understanding of genes and their role in human disease by characterizing the RNA content of tissues and cells. The realization of this promise, however, is conditional on the development of effective computational methods for the identification and quantification of transcripts from incomplete and noisy data. In this paper, we introduce iReckon, a method for simultaneous determination of the isoforms and estimation of their abundances. Our probabilistic approach incorporates multiple biological and technical phenom- ena, including novel isoforms, intron retention, unspliced pre-mRNA, PCR amplification biases, and multi-mapped reads. iReckon utilizes regularized Expectation-Maximization to accurately estimate the abundances of known and novel isoforms. Our results on simulated and real data demonstrate a supe- rior ability to discover novel isoforms with a significantly reduced number of false positive predictions, and our abundance accuracy prediction outmatches that of other state-of-the-art tools. Furthermore we have applied iReckon to two cancer transcriptome datasets, a triple negative breast cancer patient sample and the MCF7 breast cancer cell line, and show that iReckon is able to reconstruct the complex splicing changes that were not previously identified. QT-PCR validations of the isoforms detected in the MCF7 cell line confirmed all of iReckon's predictions and also showed strong agreement (r^2 = 0.94) with the predicted abundances.
- Received April 24, 2012.
- Accepted November 21, 2012.
- © 2012, Published by Cold Spring Harbor Laboratory Press
This article is distributed exclusively by Cold Spring Harbor Laboratory Press for the first six months after the full-issue publication date (see http://genome.cshlp.org/site/misc/terms.xhtml). After six months, it is available under a Creative Commons License (Attribution-NonCommercial 3.0 Unported License), as described at http://creativecommons.org/licenses/by-nc/3.0/.
