FusionSeq: A modular framework for finding gene fusions by analyzing paired-end RNA-sequencing data

Andrea Sboner, Lukas Habegger, Dorothee Pflueger, Stephane Terry, David Z. Chen, Joel S. Rozowsky, Ashutosh K. Tewari, Naoki Kitabayashi, Benjamin J. Moss, Mark S. Chee, Francesca Demichelis, Mark A. Rubin, Mark B. Gerstein

Research output: Contribution to journalArticlepeer-review

136 Scopus citations

Abstract

We have developed FusionSeq to identify fusion transcripts from paired-end RNA-sequencing. FusionSeq includes filters to remove spurious candidate fusions with artifacts, such as misalignment or random pairing of transcript fragments, and it ranks candidates according to several statistics. It also has a module to identify exact sequences at breakpoint junctions. FusionSeq detected known and novel fusions in a specially sequenced calibration data set, including eight cancers with and without known rearrangements.

Original languageEnglish
Article numberR104
JournalGenome Biology
Volume11
Issue number10
DOIs
StatePublished - 21 Oct 2010
Externally publishedYes

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