Prioritisation of structural variant calls in cancer genomes

被引：18

作者：

Ahdesmaki, Miika J. ^{[1
]}

Chapman, Brad A. ^{[2
]}

Cingolani, Pablo ^{[3
]}

Hofmann, Oliver ^{[4
]}

Sidoruk, Aleksandr ^{[5
,6
]}

Lai, Zhongwu ^{[7
]}

Zakharov, Gennadii ^{[5
,8
]}

Rodichenko, Mikhail ^{[5
]}

Alperovich, Mikhail ^{[5
]}

Jenkins, David ^{[9
]}

Carr, T. Hedley ^{[1
]}

Stetson, Daniel ^{[7
]}

Dougherty, Brian ^{[7
]}

Barrett, J. Carl ^{[7
]}

Johnson, Justin H. ^{[7
]}

机构：

[1] AstraZeneca, Oncol, Innovat Med & Early Dev, Cambridge, England

[2] Harvard Univ, Harvard TH Chan Sch Publ Hlth, Boston, MA 02115 USA

[3] Kew Inc, Cambridge, MA USA

[4] Univ Melbourne, Ctr Canc Res, Melbourne, Vic, Australia

[5] EPAM Syst Inc, Newtown, PA USA

[6] St Petersburg State Univ, Dept Software Engn, St Petersburg, Russia

[7] AstraZeneca, Oncol, Innovat Med & Early Dev, Waltham, MA USA

[8] Russian Acad Sci, Pavlov Inst Physiol, St Petersburg, Russia

[9] Boston Univ, Boston, MA 02215 USA

来源：

PEERJ | 2017年 / 5卷

关键词：

Structural variation; Gene fusion; Oncology; Prioritisation; Annotation; Visualisation; GENE;

D O I：

10.7717/peerj.3166

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

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.

引用

页数：15

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