Details

Autor(en) / Beteiligte

• 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.

Titel

A platform for oncogenomic reporting and interpretation

Ist Teil von

• Nature communications, 2022-02, Vol.13 (1), p.756-756, Article 756

Ort / Verlag

London: Nature Publishing Group UK

Erscheinungsjahr

2022

Quelle

MEDLINE

Beschreibungen/Notizen

• 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.