A Platform for Oncogenomic Reporting and Interpretation
| Autor: | B. M. Pierce, I. Beckie, R. Stevenson, B. Pellegrini, Melika Bonakdar, L. Bailey, Laura Williamson, A. Muhammadzadeh, E. Chuah, M. Douglas, Stephen Yip, Martin Jones, Martin Krzywinski, D. W. Bleile, A. Fisic, Yussanne Ma, R. Matiello Pletz, T. Mitchell, Erin Pleasance, Janessa Laskin, Cameron J. Grisdale, D. Pham, Jessica Nelson, A. Davies, H. Wong, Karen Mungall, Marco A. Marra, C. Reisle, Daniel J. Renouf, A. Reisle, Sjm Jones, Jun Li |
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| Rok vydání: | 2021 |
| Předmět: |
Manual interpretation
Matching (statistics) Carcinogenesis Computer science Science Knowledge Bases Genomic data General Physics and Astronomy General Biochemistry Genetics and Molecular Biology Unmet needs Neoplasms Databases Genetic Biomarkers Tumor Humans Precision Medicine Multidisciplinary Interpretation (logic) business.industry Genetic Variation General Chemistry Genomics Data science Knowledge base Precision oncology Graph (abstract data type) InformationSystems_MISCELLANEOUS business |
| Zdroj: | Nature Communications, Vol 13, Iss 1, Pp 1-11 (2022) |
| Popis: | 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 created the Platform for Oncogenomic Reporting and Interpretation (PORI), comprising an analytic framework created to facilitate the interpretation and reporting of somatic variants in cancer. PORI is unique in its integration of reporting and graph knowledge base tools combined with support for manual curation at the reporting stage. PORI represents one of the first open-source platform alternatives to commercial reporting solutions suitable for comprehensive genomic data sets in precision oncology. We demonstrate the utility of PORI by matching 9,961 TCGA tumours to the graph knowledge base, revealing that 88.2% have at least one potentially targetable alteration, and making available reports describing select individual samples. |
| Databáze: | OpenAIRE |
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