CancerVar: a web server for improved evidence-based clinical interpretation of cancer somatic mutations and copy number abnormalities [article]

Quan Li, Zilin Ren, Yunyun Zhou, Kai Wang
2020 bioRxiv   pre-print
Several knowledgebases, such as CIViC, CGI and OncoKB, have been manually curated to support clinical interpretations of somatic mutations and copy number abnormalities (CNAs) in cancer. However, these resources focus on known hotspot mutations, and discrepancies or even conflicting interpretations have been observed between these knowledgebases. To standardize clinical interpretation, AMP/ASCO/CAP/ACMG/CGC jointly published consensus guidelines for the interpretations of somatic mutations and
more » ... atic mutations and CNAs in 2017 and 2019, respectively. Based on these guidelines, we developed a standardized, semi-automated interpretation tool called CancerVar (Cancer Variants interpretation), with a user-friendly web interface to assess the clinical impacts of somatic variants. Using a semi-supervised method, CancerVar interpret the clinical impacts of cancer variants as pathogenic, likely pathogenic, benign or uncertain significance. CancerVar also allows users to specify criteria or adjust scoring weights as a customized interpretation strategy. Importantly, CancerVar generates automated texts to summarize clinical evidence on somatic variants, which greatly reduces manual workload to write interpretations that include relevant information from the harmonized knowledgebase. CancerVar can be accessed at http://cancervar.wglab.org and it is open to all users without login requirements. The command line tool is also available at https://github.com/WGLab/CancerVar.
doi:10.1101/2020.10.06.323162 fatcat:ugyqwqmssbhmfb6k46uzbmzogu