%0 Journal Article %1 Ahdesmaki084640 %A Ahdesmaki, Miika J %A Chapman, Brad %A Cingolani, Pablo E %A Hofmann, Oliver %A Sidoruk, Aleksandr %A Lai, Zhongwu %A Zakharov, Gennadii %A Rodichenko, Mikhail %A Alperovich, Mikhail %A Jenkins, David %A Carr, T. Hedley %A Stetson, Daniel %A Dougherty, Brian %A Barrett, J. Carl %A Johnson, Justin %D 2016 %I Cold Spring Harbor Laboratory %J bioRxiv %K MUSTREAD docker fulltext genomebrowser open-source %R 10.1101/084640 %T Prioritisation of Structural Variant Calls in Cancer Genomes %U https://www.biorxiv.org/content/early/2016/11/04/084640 %X 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. 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.

@article{Ahdesmaki084640, 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. 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.}, added-at = {2017-11-21T19:58:45.000+0100}, author = {Ahdesmaki, Miika J and Chapman, Brad and Cingolani, Pablo E and Hofmann, Oliver and Sidoruk, Aleksandr and Lai, Zhongwu and Zakharov, Gennadii and Rodichenko, Mikhail and Alperovich, Mikhail and Jenkins, David and Carr, T. Hedley and Stetson, Daniel and Dougherty, Brian and Barrett, J. Carl and Johnson, Justin}, biburl = {https://www.bibsonomy.org/bibtex/2797ee21b349ebbea2ce601573bb94f01/marcsaric}, description = {Prioritisation of Structural Variant Calls in Cancer Genomes | bioRxiv}, doi = {10.1101/084640}, eprint = {https://www.biorxiv.org/content/early/2016/11/04/084640.full.pdf}, interhash = {d23f2f90e1c7ddaaa93a04c42e97820e}, intrahash = {797ee21b349ebbea2ce601573bb94f01}, journal = {bioRxiv}, keywords = {MUSTREAD docker fulltext genomebrowser open-source}, publisher = {Cold Spring Harbor Laboratory}, timestamp = {2017-11-22T22:21:04.000+0100}, title = {Prioritisation of Structural Variant Calls in Cancer Genomes}, url = {https://www.biorxiv.org/content/early/2016/11/04/084640}, year = 2016 }