Database Commons
Database Commons

a catalog of worldwide biological databases

Database Profile

General information

URL: https://www.deciphergenomics.org/
Full name: DatabasE of genomiC varIation and Phenotype in Humans using Ensembl Resources
Description: The DECIPHER database is an accessible online repository of genetic variation with associated phenotypes that facilitates the identification and interpretation of pathogenic genetic variation in patients with rare disorders.
Year founded: 2012
Last update: 2022
Version: v11.12
Accessibility:
Manual:
Accessible
Real time : Checking...
Country/Region: United Kingdom

Classification & Tag

Data type:
DNA
Data object:
Database category:
Major species:
Keywords:

Contact information

University/Institution: Wellcome Sanger Institute
Address: Wellcome Trust Sanger Institute,Wellcome Trust Genome Campus,Hinxton,Cambridge CB10 1SD,UK
City: Cambridge
Province/State:
Country/Region: United Kingdom
Contact name (PI/Team): deciphergenomics
Contact email (PI/Helpdesk): contact@deciphergenomics.org

Publications

35143074
DECIPHER: Supporting the interpretation and sharing of rare disease phenotype-linked variant data to advance diagnosis and research. [PMID: 35143074]
Foreman J, Brent S, Perrett D, Bevan AP, Hunt SE, Cunningham F, Hurles ME, Firth HV.

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.

Hum Mutat. 2022:43(6) | 12 Citations (from Europe PMC, 2024-05-18)
26220709
Facilitating collaboration in rare genetic disorders through effective matchmaking in DECIPHER. [PMID: 26220709]
Chatzimichali EA, Brent S, Hutton B, Perrett D, Wright CF, Bevan AP, Hurles ME, Firth HV, Swaminathan GJ.

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.

Hum Mutat. 2015:36(10) | 29 Citations (from Europe PMC, 2024-05-18)
24150940
DECIPHER: database for the interpretation of phenotype-linked plausibly pathogenic sequence and copy-number variation. [PMID: 24150940]
Bragin E, Chatzimichali EA, Wright CF, Hurles ME, Firth HV, Bevan AP, Swaminathan GJ.

The DECIPHER database (https://decipher.sanger.ac.uk/) is an accessible online repository of genetic variation with associated phenotypes that facilitates the identification and interpretation of pathogenic genetic variation in patients with rare disorders. Contributing to DECIPHER is an international consortium of >200 academic clinical centres of genetic medicine and ?1600 clinical geneticists and diagnostic laboratory scientists. Information integrated from a variety of bioinformatics resources, coupled with visualization tools, provides a comprehensive set of tools to identify other patients with similar genotype-phenotype characteristics and highlights potentially pathogenic genes. In a significant development, we have extended DECIPHER from a database of just copy-number variants to allow upload, annotation and analysis of sequence variants such as single nucleotide variants (SNVs) and InDels. Other notable developments in DECIPHER include a purpose-built, customizable and interactive genome browser to aid combined visualization and interpretation of sequence and copy-number variation against informative datasets of pathogenic and population variation. We have also introduced several new features to our deposition and analysis interface. This article provides an update to the DECIPHER database, an earlier instance of which has been described elsewhere [Swaminathan et al. (2012) DECIPHER: web-based, community resource for clinical interpretation of rare variants in developmental disorders. Hum. Mol. Genet., 21, R37-R44].

Nucleic Acids Res. 2014:42(Database issue) | 137 Citations (from Europe PMC, 2024-05-18)
22962312
DECIPHER: web-based, community resource for clinical interpretation of rare variants in developmental disorders. [PMID: 22962312]
Swaminathan GJ, Bragin E, Chatzimichali EA, Corpas M, Bevan AP, Wright CF, Carter NP, Hurles ME, Firth HV.

Patients with developmental disorders often harbour sub-microscopic deletions or duplications that lead to a disruption of normal gene expression or perturbation in the copy number of dosage-sensitive genes. Clinical interpretation for such patients in isolation is hindered by the rarity and novelty of such disorders. The DECIPHER project (https://decipher.sanger.ac.uk) was established in 2004 as an accessible online repository of genomic and associated phenotypic data with the primary goal of aiding the clinical interpretation of rare copy-number variants (CNVs). DECIPHER integrates information from a variety of bioinformatics resources and uses visualization tools to identify potential disease genes within a CNV. A two-tier access system permits clinicians and clinical scientists to maintain confidential linked anonymous records of phenotypes and CNVs for their patients that, with informed consent, can subsequently be shared with the wider clinical genetics and research communities. Advances in next-generation sequencing technologies are making it practical and affordable to sequence the whole exome/genome of patients who display features suggestive of a genetic disorder. This approach enables the identification of smaller intragenic mutations including single-nucleotide variants that are not accessible even with high-resolution genomic array analysis. This article briefly summarizes the current status and achievements of the DECIPHER project and looks ahead to the opportunities and challenges of jointly analysing structural and sequence variation in the human genome.

Hum Mol Genet. 2012:21(R1) | 50 Citations (from Europe PMC, 2024-05-18)

Ranking

All databases:
577/6000 (90.4%)
Health and medicine:
137/1394 (90.244%)
Genotype phenotype and variation:
75/852 (91.315%)
577
Total Rank
221
Citations
18.417
z-index

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Record metadata

Created on: 2015-06-20
Curated by:
Lina Ma [2022-05-31]
Nashaiman Pervaiz [2018-12-28]
Hao Zhang [2018-01-28]
Jian Sang [2016-04-04]
Lin Liu [2016-02-28]
Mengwei Li [2016-02-19]
Zhang Zhang [2015-06-27]
Jian Sang [2015-06-26]