Title |
FusionSeq: a modular framework for finding gene fusions by analyzing paired-end RNA-sequencing data
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Published in |
Genome Biology, October 2010
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DOI | 10.1186/gb-2010-11-10-r104 |
Pubmed ID | |
Authors |
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 |
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. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 6 | 3% |
United States | 4 | 2% |
France | 2 | 1% |
Norway | 2 | 1% |
Korea, Republic of | 2 | 1% |
Switzerland | 1 | <1% |
Netherlands | 1 | <1% |
Italy | 1 | <1% |
Austria | 1 | <1% |
Other | 6 | 3% |
Unknown | 165 | 86% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 65 | 34% |
Student > Ph. D. Student | 46 | 24% |
Professor > Associate Professor | 17 | 9% |
Student > Master | 17 | 9% |
Other | 8 | 4% |
Other | 21 | 11% |
Unknown | 17 | 9% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 100 | 52% |
Biochemistry, Genetics and Molecular Biology | 38 | 20% |
Computer Science | 15 | 8% |
Medicine and Dentistry | 13 | 7% |
Mathematics | 2 | 1% |
Other | 4 | 2% |
Unknown | 19 | 10% |