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PhenoDB, GeneMatcher and VariantMatcher, tools for analysis and sharing of sequence data

BACKGROUND: With the advent of whole exome (ES) and genome sequencing (GS) as tools for disease gene discovery, rare variant filtering, prioritization and data sharing have become essential components of the search for disease genes and variants potentially contributing to disease phenotypes. The co...

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Autores principales: Wohler, Elizabeth, Martin, Renan, Griffith, Sean, Rodrigues, Eliete da S., Antonescu, Corina, Posey, Jennifer E., Coban-Akdemir, Zeynep, Jhangiani, Shalini N., Doheny, Kimberly F., Lupski, James R., Valle, David, Hamosh, Ada, Sobreira, Nara
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8371856/
https://www.ncbi.nlm.nih.gov/pubmed/34407837
http://dx.doi.org/10.1186/s13023-021-01916-z
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author Wohler, Elizabeth
Martin, Renan
Griffith, Sean
Rodrigues, Eliete da S.
Antonescu, Corina
Posey, Jennifer E.
Coban-Akdemir, Zeynep
Jhangiani, Shalini N.
Doheny, Kimberly F.
Lupski, James R.
Valle, David
Hamosh, Ada
Sobreira, Nara
author_facet Wohler, Elizabeth
Martin, Renan
Griffith, Sean
Rodrigues, Eliete da S.
Antonescu, Corina
Posey, Jennifer E.
Coban-Akdemir, Zeynep
Jhangiani, Shalini N.
Doheny, Kimberly F.
Lupski, James R.
Valle, David
Hamosh, Ada
Sobreira, Nara
author_sort Wohler, Elizabeth
collection PubMed
description BACKGROUND: With the advent of whole exome (ES) and genome sequencing (GS) as tools for disease gene discovery, rare variant filtering, prioritization and data sharing have become essential components of the search for disease genes and variants potentially contributing to disease phenotypes. The computational storage, data manipulation, and bioinformatic interpretation of thousands to millions of variants identified in ES and GS, respectively, is a challenging task. To aid in that endeavor, we constructed PhenoDB, GeneMatcher and VariantMatcher. RESULTS: PhenoDB is an accessible, freely available, web-based platform that allows users to store, share, analyze and interpret their patients’ phenotypes and variants from ES/GS data. GeneMatcher is accessible to all stakeholders as a web-based tool developed to connect individuals (researchers, clinicians, health care providers and patients) around the globe with interest in the same gene(s), variant(s) or phenotype(s). Finally, VariantMatcher was developed to enable public sharing of variant-level data and phenotypic information from individuals sequenced as part of multiple disease gene discovery projects. Here we provide updates on PhenoDB and GeneMatcher applications and implementation and introduce VariantMatcher. CONCLUSION: Each of these tools has facilitated worldwide data sharing and data analysis and improved our ability to connect genes to phenotypic traits. Further development of these platforms will expand variant analysis, interpretation, novel disease-gene discovery and facilitate functional annotation of the human genome for clinical genomics implementation and the precision medicine initiative. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13023-021-01916-z.
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spelling pubmed-83718562021-08-19 PhenoDB, GeneMatcher and VariantMatcher, tools for analysis and sharing of sequence data Wohler, Elizabeth Martin, Renan Griffith, Sean Rodrigues, Eliete da S. Antonescu, Corina Posey, Jennifer E. Coban-Akdemir, Zeynep Jhangiani, Shalini N. Doheny, Kimberly F. Lupski, James R. Valle, David Hamosh, Ada Sobreira, Nara Orphanet J Rare Dis Research BACKGROUND: With the advent of whole exome (ES) and genome sequencing (GS) as tools for disease gene discovery, rare variant filtering, prioritization and data sharing have become essential components of the search for disease genes and variants potentially contributing to disease phenotypes. The computational storage, data manipulation, and bioinformatic interpretation of thousands to millions of variants identified in ES and GS, respectively, is a challenging task. To aid in that endeavor, we constructed PhenoDB, GeneMatcher and VariantMatcher. RESULTS: PhenoDB is an accessible, freely available, web-based platform that allows users to store, share, analyze and interpret their patients’ phenotypes and variants from ES/GS data. GeneMatcher is accessible to all stakeholders as a web-based tool developed to connect individuals (researchers, clinicians, health care providers and patients) around the globe with interest in the same gene(s), variant(s) or phenotype(s). Finally, VariantMatcher was developed to enable public sharing of variant-level data and phenotypic information from individuals sequenced as part of multiple disease gene discovery projects. Here we provide updates on PhenoDB and GeneMatcher applications and implementation and introduce VariantMatcher. CONCLUSION: Each of these tools has facilitated worldwide data sharing and data analysis and improved our ability to connect genes to phenotypic traits. Further development of these platforms will expand variant analysis, interpretation, novel disease-gene discovery and facilitate functional annotation of the human genome for clinical genomics implementation and the precision medicine initiative. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13023-021-01916-z. BioMed Central 2021-08-18 /pmc/articles/PMC8371856/ /pubmed/34407837 http://dx.doi.org/10.1186/s13023-021-01916-z Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Wohler, Elizabeth
Martin, Renan
Griffith, Sean
Rodrigues, Eliete da S.
Antonescu, Corina
Posey, Jennifer E.
Coban-Akdemir, Zeynep
Jhangiani, Shalini N.
Doheny, Kimberly F.
Lupski, James R.
Valle, David
Hamosh, Ada
Sobreira, Nara
PhenoDB, GeneMatcher and VariantMatcher, tools for analysis and sharing of sequence data
title PhenoDB, GeneMatcher and VariantMatcher, tools for analysis and sharing of sequence data
title_full PhenoDB, GeneMatcher and VariantMatcher, tools for analysis and sharing of sequence data
title_fullStr PhenoDB, GeneMatcher and VariantMatcher, tools for analysis and sharing of sequence data
title_full_unstemmed PhenoDB, GeneMatcher and VariantMatcher, tools for analysis and sharing of sequence data
title_short PhenoDB, GeneMatcher and VariantMatcher, tools for analysis and sharing of sequence data
title_sort phenodb, genematcher and variantmatcher, tools for analysis and sharing of sequence data
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8371856/
https://www.ncbi.nlm.nih.gov/pubmed/34407837
http://dx.doi.org/10.1186/s13023-021-01916-z
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