학술논문
CIViC is a community knowledgebase for expert crowdsourcing the clinical interpretation of variants in cancer
Clinical Interpretation of Variants in Cancer
Clinical Interpretation of Variants in Cancer
Document Type
Report
Author
Griffith, Malachi; Spies, Nicholas C; Krysiak, Kilannin; McMichael, Joshua F; Coffman, Adam C; Danos, Arpad M; Ainscough, Benjamin J; Ramirez, Cody A; Rieke, Damian T; Kujan, Lynzey; Barnell, Erica K; Wagner, Alex H; Skidmore, Zachary L; Wollam, Amber; Liu, Connor J; Jones, Martin R; Bilski, Rachel L; Lesurf, Robert; Feng, Yan-Yang; Shah, Nakul M; Bonakdar, Melika; Trani, Lee; Matlock, Matthew; Ramu, Avinash; Campbell, Katie M; Spies, Gregory C; Graubert, Aaron P; Gangavarapu, Karthik; Eldred, James M; Larson, David E; Walker, Jason R; Good, Benjamin M; Wu, Chunlei; Su, Andrew I; Dienstmann, Rodrigo; Margolin, Adam A; Tamborero, David; Lopez-Bigas, Nuria; Jones, Steven J M; Bose, Ron; Spencer, David H; Wartman, Lukas D; Wilson, Richard K; Mardis, Elaine R; Griffith, Obi L
Source
Nature Genetics. February 2017, Vol. 49 Issue 2, p170, 5 p.
Subject
Language
English
ISSN
1061-4036
Abstract
Author(s): Malachi Griffith (corresponding author) [1, 2, 3, 4]; Nicholas C Spies [1]; Kilannin Krysiak [1, 4]; Joshua F McMichael [1]; Adam C Coffman [1]; Arpad M Danos [1]; Benjamin [...]
CIViC is an expert-crowdsourced knowledgebase for Clinical Interpretation of Variants in Cancer describing the therapeutic, prognostic, diagnostic and predisposing relevance of inherited and somatic variants of all types. CIViC is committed to open-source code, open-access content, public application programming interfaces (APIs) and provenance of supporting evidence to allow for the transparent creation of current and accurate variant interpretations for use in cancer precision medicine.
CIViC is an expert-crowdsourced knowledgebase for Clinical Interpretation of Variants in Cancer describing the therapeutic, prognostic, diagnostic and predisposing relevance of inherited and somatic variants of all types. CIViC is committed to open-source code, open-access content, public application programming interfaces (APIs) and provenance of supporting evidence to allow for the transparent creation of current and accurate variant interpretations for use in cancer precision medicine.