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RevUP: an online scoring system for regulatory variants implicated in rare diseases

SUMMARY: To address the difficulty in assessing the implication of regulatory variants in diseases, a scoring scheme previously published allows the calculation of the Regulatory Variant Evidence score (RVE-score). The score represents the accumulated evidence for a causative role of a regulatory va...

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Autores principales: Correard, Solenne, Hewitson, Brittany, van der Lee, Robin, Wasserman, Wyeth W
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9048665/
https://www.ncbi.nlm.nih.gov/pubmed/35289834
http://dx.doi.org/10.1093/bioinformatics/btac157
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author Correard, Solenne
Hewitson, Brittany
van der Lee, Robin
Wasserman, Wyeth W
author_facet Correard, Solenne
Hewitson, Brittany
van der Lee, Robin
Wasserman, Wyeth W
author_sort Correard, Solenne
collection PubMed
description SUMMARY: To address the difficulty in assessing the implication of regulatory variants in diseases, a scoring scheme previously published allows the calculation of the Regulatory Variant Evidence score (RVE-score). The score represents the accumulated evidence for a causative role of a regulatory variant in a disease. Regulatory Evidence for Variants Underlying Phenotypes was built to calculate the RVE-score of regulatory variants, based on the 24 criteria, with a hybrid approach combining information retrieved from public databases and user input. AVAILABILITY AND IMPLEMENTATION: RevUP is freely available at http://www.revup-classifier.ca. The source code is available at https://github.com/wassermanlab/revup. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-90486652022-04-29 RevUP: an online scoring system for regulatory variants implicated in rare diseases Correard, Solenne Hewitson, Brittany van der Lee, Robin Wasserman, Wyeth W Bioinformatics Applications Notes SUMMARY: To address the difficulty in assessing the implication of regulatory variants in diseases, a scoring scheme previously published allows the calculation of the Regulatory Variant Evidence score (RVE-score). The score represents the accumulated evidence for a causative role of a regulatory variant in a disease. Regulatory Evidence for Variants Underlying Phenotypes was built to calculate the RVE-score of regulatory variants, based on the 24 criteria, with a hybrid approach combining information retrieved from public databases and user input. AVAILABILITY AND IMPLEMENTATION: RevUP is freely available at http://www.revup-classifier.ca. The source code is available at https://github.com/wassermanlab/revup. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2022-03-15 /pmc/articles/PMC9048665/ /pubmed/35289834 http://dx.doi.org/10.1093/bioinformatics/btac157 Text en © The Author(s) 2022. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Notes
Correard, Solenne
Hewitson, Brittany
van der Lee, Robin
Wasserman, Wyeth W
RevUP: an online scoring system for regulatory variants implicated in rare diseases
title RevUP: an online scoring system for regulatory variants implicated in rare diseases
title_full RevUP: an online scoring system for regulatory variants implicated in rare diseases
title_fullStr RevUP: an online scoring system for regulatory variants implicated in rare diseases
title_full_unstemmed RevUP: an online scoring system for regulatory variants implicated in rare diseases
title_short RevUP: an online scoring system for regulatory variants implicated in rare diseases
title_sort revup: an online scoring system for regulatory variants implicated in rare diseases
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9048665/
https://www.ncbi.nlm.nih.gov/pubmed/35289834
http://dx.doi.org/10.1093/bioinformatics/btac157
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