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Annual Review of Genomics and Human Genetics: DECIPHER: Improving Genetic Diagnosis Through Dynamic Integration of Genomic and Clinical Data
DECIPHER (Database of Genomic Variation and Phenotype in Humans Using Ensembl Resources) shares candidate diagnostic variants and phenotypic data from patients with genetic disorders to facilitate research and improve the diagnosis, management, and therapy of rare diseases. The platform sits at the...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7615097/ https://www.ncbi.nlm.nih.gov/pubmed/37285546 http://dx.doi.org/10.1146/annurev-genom-102822-100509 |
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author | Foreman, Julia Perrett, Daniel Mazaika, Erica Hunt, Sarah E. Ware, James S. Firth, Helen V. |
author_facet | Foreman, Julia Perrett, Daniel Mazaika, Erica Hunt, Sarah E. Ware, James S. Firth, Helen V. |
author_sort | Foreman, Julia |
collection | PubMed |
description | DECIPHER (Database of Genomic Variation and Phenotype in Humans Using Ensembl Resources) shares candidate diagnostic variants and phenotypic data from patients with genetic disorders to facilitate research and improve the diagnosis, management, and therapy of rare diseases. The platform sits at the boundary between genomic research and the clinical community. DECIPHER aims to ensure that the most up-to-date data are made rapidly available within its interpretation interfaces to improve clinical care. Newly integrated cardiac case–control data that provide evidence of gene–disease associations and inform variant interpretation exemplify this mission. New research resources are presented in a format optimized for use by a broad range of professionals supporting the delivery of genomic medicine. The interfaces within DECIPHER integrate and contextualize variant and phenotypic data, helping to determine a robust clinico-molecular diagnosis for rare-disease patients, which combines both variant classification and clinical fit. DECIPHER supports discovery research, connecting individuals within the rare-disease community to pursue hypothesis-driven research. |
format | Online Article Text |
id | pubmed-7615097 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
record_format | MEDLINE/PubMed |
spelling | pubmed-76150972023-09-15 Annual Review of Genomics and Human Genetics: DECIPHER: Improving Genetic Diagnosis Through Dynamic Integration of Genomic and Clinical Data Foreman, Julia Perrett, Daniel Mazaika, Erica Hunt, Sarah E. Ware, James S. Firth, Helen V. Annu Rev Genomics Hum Genet Article DECIPHER (Database of Genomic Variation and Phenotype in Humans Using Ensembl Resources) shares candidate diagnostic variants and phenotypic data from patients with genetic disorders to facilitate research and improve the diagnosis, management, and therapy of rare diseases. The platform sits at the boundary between genomic research and the clinical community. DECIPHER aims to ensure that the most up-to-date data are made rapidly available within its interpretation interfaces to improve clinical care. Newly integrated cardiac case–control data that provide evidence of gene–disease associations and inform variant interpretation exemplify this mission. New research resources are presented in a format optimized for use by a broad range of professionals supporting the delivery of genomic medicine. The interfaces within DECIPHER integrate and contextualize variant and phenotypic data, helping to determine a robust clinico-molecular diagnosis for rare-disease patients, which combines both variant classification and clinical fit. DECIPHER supports discovery research, connecting individuals within the rare-disease community to pursue hypothesis-driven research. 2023-06-07 2023-06-07 /pmc/articles/PMC7615097/ /pubmed/37285546 http://dx.doi.org/10.1146/annurev-genom-102822-100509 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See credit lines of images or other third-party material in this article for license information https://creativecommons.org/licenses/by/4.0/. https://creativecommons.org/licenses/by/4.0/This work is licensed under a BY 4.0 (https://creativecommons.org/licenses/by/4.0/) International license. |
spellingShingle | Article Foreman, Julia Perrett, Daniel Mazaika, Erica Hunt, Sarah E. Ware, James S. Firth, Helen V. Annual Review of Genomics and Human Genetics: DECIPHER: Improving Genetic Diagnosis Through Dynamic Integration of Genomic and Clinical Data |
title | Annual Review of Genomics and Human Genetics: DECIPHER: Improving Genetic Diagnosis Through Dynamic Integration of Genomic and Clinical Data |
title_full | Annual Review of Genomics and Human Genetics: DECIPHER: Improving Genetic Diagnosis Through Dynamic Integration of Genomic and Clinical Data |
title_fullStr | Annual Review of Genomics and Human Genetics: DECIPHER: Improving Genetic Diagnosis Through Dynamic Integration of Genomic and Clinical Data |
title_full_unstemmed | Annual Review of Genomics and Human Genetics: DECIPHER: Improving Genetic Diagnosis Through Dynamic Integration of Genomic and Clinical Data |
title_short | Annual Review of Genomics and Human Genetics: DECIPHER: Improving Genetic Diagnosis Through Dynamic Integration of Genomic and Clinical Data |
title_sort | annual review of genomics and human genetics: decipher: improving genetic diagnosis through dynamic integration of genomic and clinical data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7615097/ https://www.ncbi.nlm.nih.gov/pubmed/37285546 http://dx.doi.org/10.1146/annurev-genom-102822-100509 |
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