Introduction

Gene fusions created by somatic genomic rearrangements are known to play an important role in the onset and development of some cancers, such as lymphomas and sarcomas. RNA-Seq (whole transcriptome shotgun sequencing) is proving to be a useful tool for the discovery of novel gene fusions in cancer transcriptomes. However, algorithmic methods for the discovery of gene fusions using RNA-Seq data remain underdeveloped. We have developed deFuse, a novel computational method for fusion discovery in tumor RNA-Seq data. Unlike existing methods that use only unique best-hit alignments and consider only fusion boundaries at the ends of known exons, deFuse considers all alignments and all possible locations for fusion boundaries. As a result, deFuse is able to identify fusion sequences with demonstrably better sensitivity than previous approaches. To increase the specificity of our approach, we curated a list of 60 true positive and 61 true negative fusion sequences (as confirmed by RT-PCR), and have trained an adaboost classifier on 11 novel features of the sequence data. The resulting classifier has an estimated value of 0.91 for the area under the ROC curve. We have used deFuse to discover gene fusions in 40 ovarian tumor samples, one ovarian cancer cell line, and three sarcoma samples. We report herein the first gene fusions discovered in ovarian cancer. We conclude that gene fusions are not infrequent events in ovarian cancer and that these events have the potential to substantially alter the expression patterns of the genes involved; gene fusions should therefore be considered in efforts to comprehensively characterize the mutational profiles of ovarian cancer transcriptomes.

Publications

  1. deFuse: an algorithm for gene fusion discovery in tumor RNA-Seq data.
    Cite this
    McPherson A, Hormozdiari F, Zayed A, Giuliany R, Ha G, Sun MG, Griffith M, Heravi Moussavi A, Senz J, Melnyk N, Pacheco M, Marra MA, Hirst M, Nielsen TO, Sahinalp SC, Huntsman D, Shah SP, 2011-05-01 - PLoS computational biology

Credits

  1. Andrew McPherson
    Developer

  2. Fereydoun Hormozdiari
    Developer

  3. Abdalnasser Zayed
    Developer

  4. Ryan Giuliany
    Developer

  5. Gavin Ha
    Developer

  6. Mark G F Sun
    Developer

  7. Malachi Griffith
    Developer

  8. Alireza Heravi Moussavi
    Developer

  9. Janine Senz
    Developer

  10. Nataliya Melnyk
    Developer

  11. Marina Pacheco
    Developer

  12. Marco A Marra
    Developer

  13. Martin Hirst
    Developer

  14. Torsten O Nielsen
    Developer

  15. S Cenk Sahinalp
    Developer

  16. David Huntsman
    Developer

  17. Sohrab P Shah
    Investigator

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Summary
AccessionBT001239
Tool TypeApplication
Category
PlatformsLinux/Unix
TechnologiesC++
User InterfaceTerminal Command Line
Download Count0
Submitted BySohrab P Shah