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Consensus: a framework for evaluation of uncertain gene variants in laboratory test reporting
Accurate interpretation of gene testing is a key component in customizing patient therapy. Where confirming evidence for a gene variant is lacking, computational prediction may be employed. A standardized framework, however, does not yet exist for quantitative evaluation of disease association for u...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3506914/ https://www.ncbi.nlm.nih.gov/pubmed/22640420 http://dx.doi.org/10.1186/gm347 |
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author | Crockett, David K Ridge, Perry G Wilson, Andrew R Lyon, Elaine Williams, Marc S Narus, Scott P Facelli, Julio C Mitchell, Joyce A |
author_facet | Crockett, David K Ridge, Perry G Wilson, Andrew R Lyon, Elaine Williams, Marc S Narus, Scott P Facelli, Julio C Mitchell, Joyce A |
author_sort | Crockett, David K |
collection | PubMed |
description | Accurate interpretation of gene testing is a key component in customizing patient therapy. Where confirming evidence for a gene variant is lacking, computational prediction may be employed. A standardized framework, however, does not yet exist for quantitative evaluation of disease association for uncertain or novel gene variants in an objective manner. Here, complementary predictors for missense gene variants were incorporated into a weighted Consensus framework that includes calculated reference intervals from known disease outcomes. Data visualization for clinical reporting is also discussed. |
format | Online Article Text |
id | pubmed-3506914 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-35069142012-11-28 Consensus: a framework for evaluation of uncertain gene variants in laboratory test reporting Crockett, David K Ridge, Perry G Wilson, Andrew R Lyon, Elaine Williams, Marc S Narus, Scott P Facelli, Julio C Mitchell, Joyce A Genome Med Method Accurate interpretation of gene testing is a key component in customizing patient therapy. Where confirming evidence for a gene variant is lacking, computational prediction may be employed. A standardized framework, however, does not yet exist for quantitative evaluation of disease association for uncertain or novel gene variants in an objective manner. Here, complementary predictors for missense gene variants were incorporated into a weighted Consensus framework that includes calculated reference intervals from known disease outcomes. Data visualization for clinical reporting is also discussed. BioMed Central 2012-05-28 /pmc/articles/PMC3506914/ /pubmed/22640420 http://dx.doi.org/10.1186/gm347 Text en Copyright ©2012 Crockett et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Method Crockett, David K Ridge, Perry G Wilson, Andrew R Lyon, Elaine Williams, Marc S Narus, Scott P Facelli, Julio C Mitchell, Joyce A Consensus: a framework for evaluation of uncertain gene variants in laboratory test reporting |
title | Consensus: a framework for evaluation of uncertain gene variants in laboratory test reporting |
title_full | Consensus: a framework for evaluation of uncertain gene variants in laboratory test reporting |
title_fullStr | Consensus: a framework for evaluation of uncertain gene variants in laboratory test reporting |
title_full_unstemmed | Consensus: a framework for evaluation of uncertain gene variants in laboratory test reporting |
title_short | Consensus: a framework for evaluation of uncertain gene variants in laboratory test reporting |
title_sort | consensus: a framework for evaluation of uncertain gene variants in laboratory test reporting |
topic | Method |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3506914/ https://www.ncbi.nlm.nih.gov/pubmed/22640420 http://dx.doi.org/10.1186/gm347 |
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