4.4 Article

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

Journal

GENOME BIOLOGY
Volume 11, Issue 10, Pages -

Publisher

BMC
DOI: 10.1186/gb-2010-11-10-r104

Keywords

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Funding

  1. Yale University Biomedical High Performance Computing Center
  2. NIH [RR19895]
  3. National Cancer Institute [R01CA125612]
  4. National Human Genome Research Institute [5R44HG004237]
  5. Prostate Cancer Foundation
  6. Breslin Foundation
  7. NATIONAL CANCER INSTITUTE [R01CA125612] Funding Source: NIH RePORTER
  8. NATIONAL CENTER FOR RESEARCH RESOURCES [S10RR019895] Funding Source: NIH RePORTER
  9. NATIONAL HUMAN GENOME RESEARCH INSTITUTE [R44HG004237] Funding Source: NIH RePORTER

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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.

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