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Facilitating Collaboration in Rare Genetic Disorders Through Effective Matchmaking in DECIPHER

DECIPHER (https://decipher.sanger.ac.uk) is a web‐based platform for secure deposition, analysis, and sharing of plausibly pathogenic genomic variants from well‐phenotyped patients suffering from genetic disorders. DECIPHER aids clinical interpretation of these rare sequence and copy‐number variants...

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Autores principales: Chatzimichali, Eleni A., Brent, Simon, Hutton, Benjamin, Perrett, Daniel, Wright, Caroline F., Bevan, Andrew P., Hurles, Matthew E., Firth, Helen V., Swaminathan, Ganesh J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4832335/
https://www.ncbi.nlm.nih.gov/pubmed/26220709
http://dx.doi.org/10.1002/humu.22842
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author Chatzimichali, Eleni A.
Brent, Simon
Hutton, Benjamin
Perrett, Daniel
Wright, Caroline F.
Bevan, Andrew P.
Hurles, Matthew E.
Firth, Helen V.
Swaminathan, Ganesh J.
author_facet Chatzimichali, Eleni A.
Brent, Simon
Hutton, Benjamin
Perrett, Daniel
Wright, Caroline F.
Bevan, Andrew P.
Hurles, Matthew E.
Firth, Helen V.
Swaminathan, Ganesh J.
author_sort Chatzimichali, Eleni A.
collection PubMed
description DECIPHER (https://decipher.sanger.ac.uk) is a web‐based platform for secure deposition, analysis, and sharing of plausibly pathogenic genomic variants from well‐phenotyped patients suffering from genetic disorders. DECIPHER aids clinical interpretation of these rare sequence and copy‐number variants by providing tools for variant analysis and identification of other patients exhibiting similar genotype–phenotype characteristics. DECIPHER also provides mechanisms to encourage collaboration among a global community of clinical centers and researchers, as well as exchange of information between clinicians and researchers within a consortium, to accelerate discovery and diagnosis. DECIPHER has contributed to matchmaking efforts by enabling the global clinical genetics community to identify many previously undiagnosed syndromes and new disease genes, and has facilitated the publication of over 700 peer‐reviewed scientific publications since 2004. At the time of writing, DECIPHER contains anonymized data from ∼250 registered centers on more than 51,500 patients (∼18000 patients with consent for data sharing and ∼25000 anonymized records shared privately). In this paper, we describe salient features of the platform, with special emphasis on the tools and processes that aid interpretation, sharing, and effective matchmaking with other data held in the database and that make DECIPHER an invaluable clinical and research resource.
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spelling pubmed-48323352016-04-20 Facilitating Collaboration in Rare Genetic Disorders Through Effective Matchmaking in DECIPHER Chatzimichali, Eleni A. Brent, Simon Hutton, Benjamin Perrett, Daniel Wright, Caroline F. Bevan, Andrew P. Hurles, Matthew E. Firth, Helen V. Swaminathan, Ganesh J. Hum Mutat Special Issue Articles DECIPHER (https://decipher.sanger.ac.uk) is a web‐based platform for secure deposition, analysis, and sharing of plausibly pathogenic genomic variants from well‐phenotyped patients suffering from genetic disorders. DECIPHER aids clinical interpretation of these rare sequence and copy‐number variants by providing tools for variant analysis and identification of other patients exhibiting similar genotype–phenotype characteristics. DECIPHER also provides mechanisms to encourage collaboration among a global community of clinical centers and researchers, as well as exchange of information between clinicians and researchers within a consortium, to accelerate discovery and diagnosis. DECIPHER has contributed to matchmaking efforts by enabling the global clinical genetics community to identify many previously undiagnosed syndromes and new disease genes, and has facilitated the publication of over 700 peer‐reviewed scientific publications since 2004. At the time of writing, DECIPHER contains anonymized data from ∼250 registered centers on more than 51,500 patients (∼18000 patients with consent for data sharing and ∼25000 anonymized records shared privately). In this paper, we describe salient features of the platform, with special emphasis on the tools and processes that aid interpretation, sharing, and effective matchmaking with other data held in the database and that make DECIPHER an invaluable clinical and research resource. John Wiley and Sons Inc. 2015-08-20 2015-10 /pmc/articles/PMC4832335/ /pubmed/26220709 http://dx.doi.org/10.1002/humu.22842 Text en © 2015 The Authors. **Human Mutation published by Wiley Periodicals, Inc. This is an open access article under the terms of the Creative Commons Attribution (http://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Special Issue Articles
Chatzimichali, Eleni A.
Brent, Simon
Hutton, Benjamin
Perrett, Daniel
Wright, Caroline F.
Bevan, Andrew P.
Hurles, Matthew E.
Firth, Helen V.
Swaminathan, Ganesh J.
Facilitating Collaboration in Rare Genetic Disorders Through Effective Matchmaking in DECIPHER
title Facilitating Collaboration in Rare Genetic Disorders Through Effective Matchmaking in DECIPHER
title_full Facilitating Collaboration in Rare Genetic Disorders Through Effective Matchmaking in DECIPHER
title_fullStr Facilitating Collaboration in Rare Genetic Disorders Through Effective Matchmaking in DECIPHER
title_full_unstemmed Facilitating Collaboration in Rare Genetic Disorders Through Effective Matchmaking in DECIPHER
title_short Facilitating Collaboration in Rare Genetic Disorders Through Effective Matchmaking in DECIPHER
title_sort facilitating collaboration in rare genetic disorders through effective matchmaking in decipher
topic Special Issue Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4832335/
https://www.ncbi.nlm.nih.gov/pubmed/26220709
http://dx.doi.org/10.1002/humu.22842
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