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Sherloc: a comprehensive refinement of the ACMG–AMP variant classification criteria

PURPOSE: The 2015 American College of Medical Genetics and Genomics–Association for Molecular Pathology (ACMG–AMP) guidelines were a major step toward establishing a common framework for variant classification. In practice, however, several aspects of the guidelines lack specificity, are subject to...

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Autores principales: Nykamp, Keith, Anderson, Michael, Powers, Martin, Garcia, John, Herrera, Blanca, Ho, Yuan-Yuan, Kobayashi, Yuya, Patil, Nila, Thusberg, Janita, Westbrook, Marjorie, Topper, Scott
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5632818/
https://www.ncbi.nlm.nih.gov/pubmed/28492532
http://dx.doi.org/10.1038/gim.2017.37
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author Nykamp, Keith
Anderson, Michael
Powers, Martin
Garcia, John
Herrera, Blanca
Ho, Yuan-Yuan
Kobayashi, Yuya
Patil, Nila
Thusberg, Janita
Westbrook, Marjorie
Topper, Scott
author_facet Nykamp, Keith
Anderson, Michael
Powers, Martin
Garcia, John
Herrera, Blanca
Ho, Yuan-Yuan
Kobayashi, Yuya
Patil, Nila
Thusberg, Janita
Westbrook, Marjorie
Topper, Scott
author_sort Nykamp, Keith
collection PubMed
description PURPOSE: The 2015 American College of Medical Genetics and Genomics–Association for Molecular Pathology (ACMG–AMP) guidelines were a major step toward establishing a common framework for variant classification. In practice, however, several aspects of the guidelines lack specificity, are subject to varied interpretations, or fail to capture relevant aspects of clinical molecular genetics. A simple implementation of the guidelines in their current form is insufficient for consistent and comprehensive variant classification. METHODS: We undertook an iterative process of refining the ACMG–AMP guidelines. We used the guidelines to classify more than 40,000 clinically observed variants, assessed the outcome, and refined the classification criteria to capture exceptions and edge cases. During this process, the criteria evolved through eight major and minor revisions. RESULTS: Our implementation: (i) separated ambiguous ACMG–AMP criteria into a set of discrete but related rules with refined weights; (ii) grouped certain criteria to protect against the overcounting of conceptually related evidence; and (iii) replaced the “clinical criteria” style of the guidelines with additive, semiquantitative criteria. CONCLUSION: Sherloc builds on the strong framework of 33 rules established by the ACMG–AMP guidelines and introduces 108 detailed refinements, which support a more consistent and transparent approach to variant classification.
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spelling pubmed-56328182017-10-11 Sherloc: a comprehensive refinement of the ACMG–AMP variant classification criteria Nykamp, Keith Anderson, Michael Powers, Martin Garcia, John Herrera, Blanca Ho, Yuan-Yuan Kobayashi, Yuya Patil, Nila Thusberg, Janita Westbrook, Marjorie Topper, Scott Genet Med Original Research Article PURPOSE: The 2015 American College of Medical Genetics and Genomics–Association for Molecular Pathology (ACMG–AMP) guidelines were a major step toward establishing a common framework for variant classification. In practice, however, several aspects of the guidelines lack specificity, are subject to varied interpretations, or fail to capture relevant aspects of clinical molecular genetics. A simple implementation of the guidelines in their current form is insufficient for consistent and comprehensive variant classification. METHODS: We undertook an iterative process of refining the ACMG–AMP guidelines. We used the guidelines to classify more than 40,000 clinically observed variants, assessed the outcome, and refined the classification criteria to capture exceptions and edge cases. During this process, the criteria evolved through eight major and minor revisions. RESULTS: Our implementation: (i) separated ambiguous ACMG–AMP criteria into a set of discrete but related rules with refined weights; (ii) grouped certain criteria to protect against the overcounting of conceptually related evidence; and (iii) replaced the “clinical criteria” style of the guidelines with additive, semiquantitative criteria. CONCLUSION: Sherloc builds on the strong framework of 33 rules established by the ACMG–AMP guidelines and introduces 108 detailed refinements, which support a more consistent and transparent approach to variant classification. Nature Publishing Group 2017-10 2017-05-11 /pmc/articles/PMC5632818/ /pubmed/28492532 http://dx.doi.org/10.1038/gim.2017.37 Text en Copyright © 2017 The Author(s) http://creativecommons.org/licenses/by-nc-nd/4.0/ This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/4.0/
spellingShingle Original Research Article
Nykamp, Keith
Anderson, Michael
Powers, Martin
Garcia, John
Herrera, Blanca
Ho, Yuan-Yuan
Kobayashi, Yuya
Patil, Nila
Thusberg, Janita
Westbrook, Marjorie
Topper, Scott
Sherloc: a comprehensive refinement of the ACMG–AMP variant classification criteria
title Sherloc: a comprehensive refinement of the ACMG–AMP variant classification criteria
title_full Sherloc: a comprehensive refinement of the ACMG–AMP variant classification criteria
title_fullStr Sherloc: a comprehensive refinement of the ACMG–AMP variant classification criteria
title_full_unstemmed Sherloc: a comprehensive refinement of the ACMG–AMP variant classification criteria
title_short Sherloc: a comprehensive refinement of the ACMG–AMP variant classification criteria
title_sort sherloc: a comprehensive refinement of the acmg–amp variant classification criteria
topic Original Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5632818/
https://www.ncbi.nlm.nih.gov/pubmed/28492532
http://dx.doi.org/10.1038/gim.2017.37
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