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vaRHC: an R package for semi-automation of variant classification in hereditary cancer genes according to ACMG/AMP and gene-specific ClinGen guidelines

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....

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Autores principales: Munté, Elisabet, Feliubadaló, Lidia, Pineda, Marta, Tornero, Eva, Gonzalez, Maribel, Moreno-Cabrera, José Marcos, Roca, Carla, Bales Rubio, Joan, Arnaldo, Laura, Capellá, Gabriel, Mosquera, Jose Luis, Lázaro, Conxi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10032633/
https://www.ncbi.nlm.nih.gov/pubmed/36916756
http://dx.doi.org/10.1093/bioinformatics/btad128
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author Munté, Elisabet
Feliubadaló, Lidia
Pineda, Marta
Tornero, Eva
Gonzalez, Maribel
Moreno-Cabrera, José Marcos
Roca, Carla
Bales Rubio, Joan
Arnaldo, Laura
Capellá, Gabriel
Mosquera, Jose Luis
Lázaro, Conxi
author_facet Munté, Elisabet
Feliubadaló, Lidia
Pineda, Marta
Tornero, Eva
Gonzalez, Maribel
Moreno-Cabrera, José Marcos
Roca, Carla
Bales Rubio, Joan
Arnaldo, Laura
Capellá, Gabriel
Mosquera, Jose Luis
Lázaro, Conxi
author_sort Munté, Elisabet
collection PubMed
description 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.
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spelling pubmed-100326332023-03-23 vaRHC: an R package for semi-automation of variant classification in hereditary cancer genes according to ACMG/AMP and gene-specific ClinGen guidelines Munté, Elisabet Feliubadaló, Lidia Pineda, Marta Tornero, Eva Gonzalez, Maribel Moreno-Cabrera, José Marcos Roca, Carla Bales Rubio, Joan Arnaldo, Laura Capellá, Gabriel Mosquera, Jose Luis Lázaro, Conxi Bioinformatics Original Paper 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. Oxford University Press 2023-03-14 /pmc/articles/PMC10032633/ /pubmed/36916756 http://dx.doi.org/10.1093/bioinformatics/btad128 Text en © The Author(s) 2023. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Paper
Munté, Elisabet
Feliubadaló, Lidia
Pineda, Marta
Tornero, Eva
Gonzalez, Maribel
Moreno-Cabrera, José Marcos
Roca, Carla
Bales Rubio, Joan
Arnaldo, Laura
Capellá, Gabriel
Mosquera, Jose Luis
Lázaro, Conxi
vaRHC: an R package for semi-automation of variant classification in hereditary cancer genes according to ACMG/AMP and gene-specific ClinGen guidelines
title vaRHC: an R package for semi-automation of variant classification in hereditary cancer genes according to ACMG/AMP and gene-specific ClinGen guidelines
title_full vaRHC: an R package for semi-automation of variant classification in hereditary cancer genes according to ACMG/AMP and gene-specific ClinGen guidelines
title_fullStr vaRHC: an R package for semi-automation of variant classification in hereditary cancer genes according to ACMG/AMP and gene-specific ClinGen guidelines
title_full_unstemmed vaRHC: an R package for semi-automation of variant classification in hereditary cancer genes according to ACMG/AMP and gene-specific ClinGen guidelines
title_short vaRHC: an R package for semi-automation of variant classification in hereditary cancer genes according to ACMG/AMP and gene-specific ClinGen guidelines
title_sort varhc: an r package for semi-automation of variant classification in hereditary cancer genes according to acmg/amp and gene-specific clingen guidelines
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10032633/
https://www.ncbi.nlm.nih.gov/pubmed/36916756
http://dx.doi.org/10.1093/bioinformatics/btad128
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