학술논문
A platform for oncogenomic reporting and interpretation
Document Type
Original Paper
Author
Reisle, Caralyn; Williamson, Laura M.; Pleasance, Erin; Davies, Anna; Pellegrini, Brayden; Bleile, Dustin W.; Mungall, Karen L.; Chuah, Eric; Jones, Martin R.; Ma, Yussanne; Lewis, Eleanor; Beckie, Isaac; Pham, David; Matiello Pletz, Raphael; Muhammadzadeh, Amir; Pierce, Brandon M.; Li, Jacky; Stevenson, Ross; Wong, Hansen; Bailey, Lance; Reisle, Abbey; Douglas, Matthew; Bonakdar, Melika; Nelson, Jessica M. T.; Grisdale, Cameron J.; Krzywinski, Martin; Fisic, Ana; Mitchell, Teresa; Renouf, Daniel J.; Yip, Stephen; Laskin, Janessa; Marra, Marco A.; Jones, Steven J. M.
Source
Nature Communications. 13(1)
Subject
Language
English
ISSN
2041-1723
Abstract
Manual interpretation of variants remains rate limiting in precision oncology. The increasing scale and complexity of molecular data generated from comprehensive sequencing of cancer samples requires advanced interpretative platforms as precision oncology expands beyond individual patients to entire populations. To address this unmet need, we introduce a Platform for Oncogenomic Reporting and Interpretation (PORI), comprising an analytic framework that facilitates the interpretation and reporting of somatic variants in cancer. PORI integrates reporting and graph knowledge base tools combined with support for manual curation at the reporting stage. PORI represents an open-source platform alternative to commercial reporting solutions suitable for comprehensive genomic data sets in precision oncology. We demonstrate the utility of PORI by matching 9,961 pan-cancer genome atlas tumours to the graph knowledge base, calculating therapeutically informative alterations, and making available reports describing select individual samples.
The interpretation of somatic variants in cancer is challenging due to the scale and complexity of sequencing data. Here, the authors present PORI, an open-source framework for interpreting somatic variants in cancer using graph knowledge base tools, automated reporting, and manual curation.
The interpretation of somatic variants in cancer is challenging due to the scale and complexity of sequencing data. Here, the authors present PORI, an open-source framework for interpreting somatic variants in cancer using graph knowledge base tools, automated reporting, and manual curation.