Genome MedicineBioinformaticsPeer-reviewed journal article
The CIViC knowledge model and standard operating procedures for curation and clinical interpretation of variants in cancer
Arpad M. DanosiD, Kilannin KrysiakiD, Erica Kay BarnelliD, Adam C. CoffmaniD, Joshua F. McMichaeliD, Susanna KiwalaiD, Nicholas C. SpiesiD, Lana M. ShetaiD, Shahil P. PemaiD, Lynzey KujaniD, Kaitlin A. Clark, Amber Z. WollamiD, Shruti RaoiD, Deborah RitteriD, Dmitriy SonkiniD, Gordana RacaiD, Wan‐Hsin LiniD, Cameron J. GrisdaleiD, Raymond H. KimiD, Alex Handler WagneriD, Subha MadhavaniD, Malachi GriffithiD, Obi L. GriffithiD
Abstract
Manually curated variant knowledgebases and their associated knowledge models are serving an increasingly important role in distributing and interpreting variants in cancer. These knowledgebases vary in their level of public accessibility, and the complexity of the models used to capture clinical knowledge. CIViC (Clinical Interpretations of Variants in Cancer - www.civicdb.org) is a fully open, free-to-use cancer variant interpretation knowledgebase that incorporates highly detailed curation of evidence obtained from peer-reviewed publications. Currently, the CIViC knowledge model consists of four main components: Genes, Variants, Evidence Items, and Assertions. Each component has an associated knowledge model and methods for curation. Gene and Variant data contextualize the genomic region(s) involved in the clinical statement. Evidence Items provide structured associations between variants and their clinically predictive/therapeutic, prognostic, diagnostic, predisposing, and functional implications. Finally, CIViC Assertions summarize collections of CIViC Evidence Items for a specific Disease, Variant, and Clinical Significance with incorporation of clinical and technical guidelines. Here we present the CIViC knowledge model, curation standard operating procedures, and detailed examples to support community-driven curation of cancer variants.
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- 27
- FWCI
- 0.47
- Field percentile
- 45th percentile
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