1. vaRHC: an R package for semi-automation of variant classification in hereditary cancer genes according to ACMG/AMP and gene-specific ClinGen guidelines
- Author
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Elisabet Munté, Lidia Feliubadaló, Marta Pineda, Eva Tornero, Maribel Gonzalez, José Marcos Moreno-Cabrera, Carla Roca, Joan Bales Rubio, Laura Arnaldo, Gabriel Capellá, Jose Luis Mosquera, and Conxi Lázaro
- Subjects
Statistics and Probability ,Computational Mathematics ,Computational Theory and Mathematics ,Molecular Biology ,Biochemistry ,Computer Science Applications - Abstract
Motivation Germline variant classification allows accurate genetic diagnosis and risk assessment. However, it is a tedious iterative process integrating information from several sources and types of evidence. It should follow gene-specific (if available) or general updated international guidelines. Thus, it is the main burden of the incorporation of next-generation sequencing into the clinical setting. Results We created the vaRiants in HC (vaRHC) R package to assist the process of variant classification in hereditary cancer by: (i) collecting information from diverse databases; (ii) assigning or denying different types of evidence according to updated American College of Molecular Genetics and Genomics/Association of Molecular Pathologist gene-specific criteria for ATM, CDH1, CHEK2, MLH1, MSH2, MSH6, PMS2, PTEN, and TP53 and general criteria for other genes; (iii) providing an automated classification of variants using a Bayesian metastructure and considering CanVIG-UK recommendations; and (iv) optionally printing the output to an .xlsx file. A validation using 659 classified variants demonstrated the robustness of vaRHC, presenting a better criteria assignment than Cancer SIGVAR, an available similar tool. Availability and implementation The source code can be consulted in the GitHub repository (https://github.com/emunte/vaRHC) Additionally, it will be submitted to CRAN soon.
- Published
- 2023