University Library
  • Login
A gateway to Melbourne's research publications
Minerva Access is the University's Institutional Repository. It aims to collect, preserve, and showcase the intellectual output of staff and students of the University of Melbourne for a global audience.
View Item 
  • Minerva Access
  • Medicine, Dentistry & Health Sciences
  • Melbourne Medical School
  • Clinical Pathology
  • Clinical Pathology - Research Publications
  • View Item
  • Minerva Access
  • Medicine, Dentistry & Health Sciences
  • Melbourne Medical School
  • Clinical Pathology
  • Clinical Pathology - Research Publications
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

    Prioritisation of structural variant calls in cancer genomes

    Thumbnail
    Download
    Published version (842.8Kb)

    Citations
    Scopus
    Web of Science
    Altmetric
    3
    3
    Author
    Ahdesmaki, MJ; Chapman, BA; Cingolani, P; Hofmann, O; Sidoruk, A; Lai, Z; Zakharov, G; Rodichenko, M; Alperovich, M; Jenkins, D; ...
    Date
    2017-04-04
    Source Title
    PeerJ
    Publisher
    PEERJ INC
    University of Melbourne Author/s
    Hofmann, Oliver
    Affiliation
    Clinical Pathology
    Metadata
    Show full item record
    Document Type
    Journal Article
    Citations
    Ahdesmaki, M. J., Chapman, B. A., Cingolani, P., Hofmann, O., Sidoruk, A., Lai, Z., Zakharov, G., Rodichenko, M., Alperovich, M., Jenkins, D., Carr, T. H., Stetson, D., Dougherty, B., Barrett, J. C. & Johnson, J. H. (2017). Prioritisation of structural variant calls in cancer genomes. PEERJ, 5 (4), https://doi.org/10.7717/peerj.3166.
    Access Status
    Open Access
    URI
    http://hdl.handle.net/11343/255706
    DOI
    10.7717/peerj.3166
    Abstract
    Sensitivity of short read DNA-sequencing for gene fusion detection is improving, but is hampered by the significant amount of noise composed of uninteresting or false positive hits in the data. In this paper we describe a tiered prioritisation approach to extract high impact gene fusion events from existing structural variant calls. Using cell line and patient DNA sequence data we improve the annotation and interpretation of structural variant calls to best highlight likely cancer driving fusions. We also considerably improve on the automated visualisation of the high impact structural variants to highlight the effects of the variants on the resulting transcripts. The resulting framework greatly improves on readily detecting clinically actionable structural variants.

    Export Reference in RIS Format     

    Endnote

    • Click on "Export Reference in RIS Format" and choose "open with... Endnote".

    Refworks

    • Click on "Export Reference in RIS Format". Login to Refworks, go to References => Import References


    Collections
    • Minerva Elements Records [45770]
    • Clinical Pathology - Research Publications [385]
    Minerva AccessDepositing Your Work (for University of Melbourne Staff and Students)NewsFAQs

    BrowseCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects
    My AccountLoginRegister
    StatisticsMost Popular ItemsStatistics by CountryMost Popular Authors