Open Access Highly Accessed Method

SOAPfuse: an algorithm for identifying fusion transcripts from paired-end RNA-Seq data

Wenlong Jia12, Kunlong Qiu12, Minghui He12, Pengfei Song2, Quan Zhou123, Feng Zhou24, Yuan Yu2, Dandan Zhu2, Michael L Nickerson5, Shengqing Wan12, Xiangke Liao6, Xiaoqian Zhu67, Shaoliang Peng67, Yingrui Li12, Jun Wang1289 and Guangwu Guo12*

Author affiliations

1 BGI Tech Solutions Co., Ltd, Beishan Industrial Zone, Yantian District, Shenzhen 518083, China

2 BGI-Shenzhen, Beishan Industrial Zone, Yantian District, Shenzhen 518083, China

3 School of Life Science and Technology, University of Electronic Science and Technology of China, No.4, Section 2, North Jianshe Road, Chengdu 610054, China

4 School of Bioscience and Bioengineering, South China University of Technology, Guangzhou Higher Education Mega Centre, Panyu District, Guangzhou 510006, China

5 Cancer and Inflammation Program, National Cancer Institute, National Institutes of Health, 1050 Boyles Street, Frederick, MD 21702, USA

6 School of Computer Science, National University of Defense Technology, No.47, Yanwachi street, Kaifu District, Changsha, Hunan 410073, China

7 State Key Laboratory of High Performance Computing, National University of Defense Technology, No.47, Yanwachi street, Kaifu District, Changsha, Hunan 410073, China

8 The Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, DK-1165 Copenhagen, Denmark

9 Department of Biology, University of Copenhagen, DK-1165 Copenhagen, Denmark

For all author emails, please log on.

Citation and License

Genome Biology 2013, 14:R12  doi:10.1186/gb-2013-14-2-r12

Published: 14 February 2013

Abstract

We have developed a new method, SOAPfuse, to identify fusion transcripts from paired-end RNA-Seq data. SOAPfuse applies an improved partial exhaustion algorithm to construct a library of fusion junction sequences, which can be used to efficiently identify fusion events, and employs a series of filters to nominate high-confidence fusion transcripts. Compared with other released tools, SOAPfuse achieves higher detection efficiency and consumed less computing resources. We applied SOAPfuse to RNA-Seq data from two bladder cancer cell lines, and confirmed 15 fusion transcripts, including several novel events common to both cell lines. SOAPfuse is available at http://soap.genomics.org.cn/soapfuse.html webcite.