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DECIPHER: Supporting the interpretation and sharing of rare disease phenotype‐linked variant data to advance diagnosis and research
DECIPHER (https://www.deciphergenomics.org) is a free web platform for sharing anonymized phenotype‐linked variant data from rare disease patients. Its dynamic interpretation interfaces contextualize genomic and phenotypic data to enable more informed variant interpretation, incorporating internatio...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9303633/ https://www.ncbi.nlm.nih.gov/pubmed/35143074 http://dx.doi.org/10.1002/humu.24340 |
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author | Foreman, Julia Brent, Simon Perrett, Daniel Bevan, Andrew P. Hunt, Sarah E. Cunningham, Fiona Hurles, Matthew E. Firth, Helen V. |
author_facet | Foreman, Julia Brent, Simon Perrett, Daniel Bevan, Andrew P. Hunt, Sarah E. Cunningham, Fiona Hurles, Matthew E. Firth, Helen V. |
author_sort | Foreman, Julia |
collection | PubMed |
description | DECIPHER (https://www.deciphergenomics.org) is a free web platform for sharing anonymized phenotype‐linked variant data from rare disease patients. Its dynamic interpretation interfaces contextualize genomic and phenotypic data to enable more informed variant interpretation, incorporating international standards for variant classification. DECIPHER supports almost all types of germline and mosaic variation in the nuclear and mitochondrial genome: sequence variants, short tandem repeats, copy‐number variants, and large structural variants. Patient phenotypes are deposited using Human Phenotype Ontology (HPO) terms, supplemented by quantitative data, which is aggregated to derive gene‐specific phenotypic summaries. It hosts data from >250 projects from ~40 countries, openly sharing >40,000 patient records containing >51,000 variants and >172,000 phenotype terms. The rich phenotype‐linked variant data in DECIPHER drives rare disease research and diagnosis by enabling patient matching within DECIPHER and with other resources, and has been cited in >2,600 publications. In this study, we describe the types of data deposited to DECIPHER, the variant interpretation tools, and patient matching interfaces which make DECIPHER an invaluable rare disease resource. |
format | Online Article Text |
id | pubmed-9303633 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-93036332022-07-28 DECIPHER: Supporting the interpretation and sharing of rare disease phenotype‐linked variant data to advance diagnosis and research Foreman, Julia Brent, Simon Perrett, Daniel Bevan, Andrew P. Hunt, Sarah E. Cunningham, Fiona Hurles, Matthew E. Firth, Helen V. Hum Mutat Review DECIPHER (https://www.deciphergenomics.org) is a free web platform for sharing anonymized phenotype‐linked variant data from rare disease patients. Its dynamic interpretation interfaces contextualize genomic and phenotypic data to enable more informed variant interpretation, incorporating international standards for variant classification. DECIPHER supports almost all types of germline and mosaic variation in the nuclear and mitochondrial genome: sequence variants, short tandem repeats, copy‐number variants, and large structural variants. Patient phenotypes are deposited using Human Phenotype Ontology (HPO) terms, supplemented by quantitative data, which is aggregated to derive gene‐specific phenotypic summaries. It hosts data from >250 projects from ~40 countries, openly sharing >40,000 patient records containing >51,000 variants and >172,000 phenotype terms. The rich phenotype‐linked variant data in DECIPHER drives rare disease research and diagnosis by enabling patient matching within DECIPHER and with other resources, and has been cited in >2,600 publications. In this study, we describe the types of data deposited to DECIPHER, the variant interpretation tools, and patient matching interfaces which make DECIPHER an invaluable rare disease resource. John Wiley and Sons Inc. 2022-02-21 2022-06 /pmc/articles/PMC9303633/ /pubmed/35143074 http://dx.doi.org/10.1002/humu.24340 Text en © 2022 The Authors. Human Mutation published by Wiley Periodicals LLC https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Foreman, Julia Brent, Simon Perrett, Daniel Bevan, Andrew P. Hunt, Sarah E. Cunningham, Fiona Hurles, Matthew E. Firth, Helen V. DECIPHER: Supporting the interpretation and sharing of rare disease phenotype‐linked variant data to advance diagnosis and research |
title | DECIPHER: Supporting the interpretation and sharing of rare disease phenotype‐linked variant data to advance diagnosis and research |
title_full | DECIPHER: Supporting the interpretation and sharing of rare disease phenotype‐linked variant data to advance diagnosis and research |
title_fullStr | DECIPHER: Supporting the interpretation and sharing of rare disease phenotype‐linked variant data to advance diagnosis and research |
title_full_unstemmed | DECIPHER: Supporting the interpretation and sharing of rare disease phenotype‐linked variant data to advance diagnosis and research |
title_short | DECIPHER: Supporting the interpretation and sharing of rare disease phenotype‐linked variant data to advance diagnosis and research |
title_sort | decipher: supporting the interpretation and sharing of rare disease phenotype‐linked variant data to advance diagnosis and research |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9303633/ https://www.ncbi.nlm.nih.gov/pubmed/35143074 http://dx.doi.org/10.1002/humu.24340 |
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