Prioritisation of structural variant calls in cancer genomes
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Date
2017
Author(s)
Ahdesmäki, Miika J.
Cingolani, Pablo
Hofmann, Oliver
Sidoruk, Aleksandr
Lai, Zhongwu
Zakharov, Gennadii
Rodichenko, Mikhail
Alperovich, Mikhail
Jenkins, David
Carr, T. Hedley
Stetson, Daniel
Dougherty, Brian
Barrett, J. Carl
Johnson, Justin H.
Publisher
PeerJ Inc.
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Citation
Ahdesmäki, M. J., B. A. Chapman, P. Cingolani, O. Hofmann, A. Sidoruk, Z. Lai, G. Zakharov, et al. 2017. “Prioritisation of structural variant calls in cancer genomes.” PeerJ 5 (1): e3166. doi:10.7717/peerj.3166. http://dx.doi.org/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.
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