 |
 |
Journal articles
A convex formulation for joint RNA isoform detection and quantification from multiple RNA-seq samples
Abstract : Detecting and quantifying isoforms from RNA-seq data is an important but challenging task. The problem is often ill-posed, particularly at low coverage. One promising direction is to exploit several samples simultaneously.
We propose a new method for solving the isoform deconvolution problem jointly across several samples. We formulate a convex optimization problem that allows to share information between samples and that we solve efficiently. We demonstrate the benefits of combining several samples on simulated and real data, and show that our approach outperforms pooling strategies and methods based on integer programming.
Our convex formulation to jointly detect and quantify isoforms from RNA-seq data of multiple related samples is a computationally efficient approach to leverage the hypotheses that some isoforms are likely to be present in several samples. The software and source code are available at http://cbio.ensmp.fr/flipflop.
Cited literature [17 references]
https://hal-mines-paristech.archives-ouvertes.fr/hal-01123141
Contributor : Anne Jaigu <>
Submitted on : Thursday, October 15, 2015 - 2:06:54 PM
Last modification on : Tuesday, July 20, 2021 - 5:20:05 PM
Long-term archiving on: : Thursday, April 27, 2017 - 4:46:06 AM
Contributor : Anne Jaigu <>
Submitted on : Thursday, October 15, 2015 - 2:06:54 PM
Last modification on : Tuesday, July 20, 2021 - 5:20:05 PM
Long-term archiving on: : Thursday, April 27, 2017 - 4:46:06 AM
File
s12859-015-0695-9.pdf
Publication funded by an institution