PeerJ (Apr 2017)

Prioritisation of structural variant calls in cancer genomes

  • Miika J. Ahdesmäki,
  • Brad A. Chapman,
  • Pablo Cingolani,
  • Oliver Hofmann,
  • Aleksandr Sidoruk,
  • Zhongwu Lai,
  • Gennadii Zakharov,
  • Mikhail Rodichenko,
  • Mikhail Alperovich,
  • David Jenkins,
  • T. Hedley Carr,
  • Daniel Stetson,
  • Brian Dougherty,
  • J. Carl Barrett,
  • Justin H. Johnson

DOI
https://doi.org/10.7717/peerj.3166
Journal volume & issue
Vol. 5
p. e3166

Abstract

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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.

Keywords