CancerVar: a web server for improved evidence-based clinical interpretation of cancer somatic mutations and copy number abnormalities
作者： Quan Li , Zilin Ren , Yunyun Zhou , Kai Wang
DOI: 10.1101/2020.10.06.323162
关键词: Web server 、 Evidence-based practice 、 Cancer 、 Computer science 、 Somatic cell 、 Computational biology
摘要: Several knowledgebases, such as CIViC, CGI and OncoKB, have been manually curated to support clinical interpretations of somatic mutations copy number abnormalities (CNAs) in cancer. However, these resources focus on known hotspot mutations, discrepancies or even conflicting observed between knowledgebases. To standardize interpretation, AMP/ASCO/CAP/ACMG/CGC jointly published consensus guidelines for the CNAs 2017 2019, respectively. Based guidelines, we developed a standardized, semi-automated interpretation tool called CancerVar (Cancer Variants interpretation), with user-friendly web interface assess impacts variants. Using semi-supervised method, interpret cancer variants four tiers: strong significance, potential unknown benign/likely benign. also allows users specify criteria adjust scoring weights customized strategy, phenotype-driven specific types Importantly, generates automated texts summarize evidence variants, which greatly reduces manual workload write that include relevant information from harmonized can be accessed at http://cancervar.wglab.org it is open all without login requirements. The command line available https://github.com/WGLab/CancerVar.
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