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miRVaS: a tool to predict the impact of genetic variants on miRNAs
Genetic variants in or near miRNA genes can have profound effects on miRNA expression and targeting. As user-friendly software for the impact prediction of miRNA variants on a large scale is still lacking, we created a tool called miRVaS. miRVaS automates this prediction by annotating the location o...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4756848/ https://www.ncbi.nlm.nih.gov/pubmed/26384425 http://dx.doi.org/10.1093/nar/gkv921 |
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author | Cammaerts, Sophia Strazisar, Mojca Dierckx, Jenne Del Favero, Jurgen De Rijk, Peter |
author_facet | Cammaerts, Sophia Strazisar, Mojca Dierckx, Jenne Del Favero, Jurgen De Rijk, Peter |
author_sort | Cammaerts, Sophia |
collection | PubMed |
description | Genetic variants in or near miRNA genes can have profound effects on miRNA expression and targeting. As user-friendly software for the impact prediction of miRNA variants on a large scale is still lacking, we created a tool called miRVaS. miRVaS automates this prediction by annotating the location of the variant relative to functional regions within the miRNA hairpin (seed, mature, loop, hairpin arm, flanks) and by annotating all predicted structural changes within the miRNA due to the variant. In addition, the tool defines the most important region that is predicted to have structural changes and calculates a conservation score that is indicative of the reliability of the structure prediction. The output is presented in a tab-separated file, which enables fast screening, and in an html file, which allows visual comparison between wild-type and variant structures. All separate images are provided for downstream use. Finally, we tested two different approaches on a small test set of published functionally validated genetic variants for their capacity to predict the impact of variants on miRNA expression. |
format | Online Article Text |
id | pubmed-4756848 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-47568482016-02-18 miRVaS: a tool to predict the impact of genetic variants on miRNAs Cammaerts, Sophia Strazisar, Mojca Dierckx, Jenne Del Favero, Jurgen De Rijk, Peter Nucleic Acids Res Methods Online Genetic variants in or near miRNA genes can have profound effects on miRNA expression and targeting. As user-friendly software for the impact prediction of miRNA variants on a large scale is still lacking, we created a tool called miRVaS. miRVaS automates this prediction by annotating the location of the variant relative to functional regions within the miRNA hairpin (seed, mature, loop, hairpin arm, flanks) and by annotating all predicted structural changes within the miRNA due to the variant. In addition, the tool defines the most important region that is predicted to have structural changes and calculates a conservation score that is indicative of the reliability of the structure prediction. The output is presented in a tab-separated file, which enables fast screening, and in an html file, which allows visual comparison between wild-type and variant structures. All separate images are provided for downstream use. Finally, we tested two different approaches on a small test set of published functionally validated genetic variants for their capacity to predict the impact of variants on miRNA expression. Oxford University Press 2016-02-18 2015-09-17 /pmc/articles/PMC4756848/ /pubmed/26384425 http://dx.doi.org/10.1093/nar/gkv921 Text en © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Methods Online Cammaerts, Sophia Strazisar, Mojca Dierckx, Jenne Del Favero, Jurgen De Rijk, Peter miRVaS: a tool to predict the impact of genetic variants on miRNAs |
title | miRVaS: a tool to predict the impact of genetic variants on miRNAs |
title_full | miRVaS: a tool to predict the impact of genetic variants on miRNAs |
title_fullStr | miRVaS: a tool to predict the impact of genetic variants on miRNAs |
title_full_unstemmed | miRVaS: a tool to predict the impact of genetic variants on miRNAs |
title_short | miRVaS: a tool to predict the impact of genetic variants on miRNAs |
title_sort | mirvas: a tool to predict the impact of genetic variants on mirnas |
topic | Methods Online |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4756848/ https://www.ncbi.nlm.nih.gov/pubmed/26384425 http://dx.doi.org/10.1093/nar/gkv921 |
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