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VarAFT: a variant annotation and filtration system for human next generation sequencing data
With the rapidly developing high-throughput sequencing technologies known as next generation sequencing or NGS, our approach to gene hunting and diagnosis has drastically changed. In <10 years, these technologies have moved from gene panel to whole genome sequencing and from an exclusively resear...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6030844/ https://www.ncbi.nlm.nih.gov/pubmed/29860484 http://dx.doi.org/10.1093/nar/gky471 |
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author | Desvignes, Jean-Pierre Bartoli, Marc Delague, Valérie Krahn, Martin Miltgen, Morgane Béroud, Christophe Salgado, David |
author_facet | Desvignes, Jean-Pierre Bartoli, Marc Delague, Valérie Krahn, Martin Miltgen, Morgane Béroud, Christophe Salgado, David |
author_sort | Desvignes, Jean-Pierre |
collection | PubMed |
description | With the rapidly developing high-throughput sequencing technologies known as next generation sequencing or NGS, our approach to gene hunting and diagnosis has drastically changed. In <10 years, these technologies have moved from gene panel to whole genome sequencing and from an exclusively research context to clinical practice. Today, the limit is not the sequencing of one, many or all genes but rather the data analysis. Consequently, the challenge is to rapidly and efficiently identify disease-causing mutations within millions of variants. To do so, we developed the VarAFT software to annotate and pinpoint human disease-causing mutations through access to multiple layers of information. VarAFT was designed both for research and clinical contexts and is accessible to all scientists, regardless of bioinformatics training. Data from multiple samples may be combined to address all Mendelian inheritance modes, cancers or population genetics. Optimized filtration parameters can be stored and re-applied to large datasets. In addition to classical annotations from dbNSFP, VarAFT contains unique features at the disease (OMIM), phenotypic (HPO), gene (Gene Ontology, pathways) and variation levels (predictions from UMD-Predictor and Human Splicing Finder) that can be combined to optimally select candidate pathogenic mutations. VarAFT is freely available at: http://varaft.eu. |
format | Online Article Text |
id | pubmed-6030844 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-60308442018-07-10 VarAFT: a variant annotation and filtration system for human next generation sequencing data Desvignes, Jean-Pierre Bartoli, Marc Delague, Valérie Krahn, Martin Miltgen, Morgane Béroud, Christophe Salgado, David Nucleic Acids Res Web Server Issue With the rapidly developing high-throughput sequencing technologies known as next generation sequencing or NGS, our approach to gene hunting and diagnosis has drastically changed. In <10 years, these technologies have moved from gene panel to whole genome sequencing and from an exclusively research context to clinical practice. Today, the limit is not the sequencing of one, many or all genes but rather the data analysis. Consequently, the challenge is to rapidly and efficiently identify disease-causing mutations within millions of variants. To do so, we developed the VarAFT software to annotate and pinpoint human disease-causing mutations through access to multiple layers of information. VarAFT was designed both for research and clinical contexts and is accessible to all scientists, regardless of bioinformatics training. Data from multiple samples may be combined to address all Mendelian inheritance modes, cancers or population genetics. Optimized filtration parameters can be stored and re-applied to large datasets. In addition to classical annotations from dbNSFP, VarAFT contains unique features at the disease (OMIM), phenotypic (HPO), gene (Gene Ontology, pathways) and variation levels (predictions from UMD-Predictor and Human Splicing Finder) that can be combined to optimally select candidate pathogenic mutations. VarAFT is freely available at: http://varaft.eu. Oxford University Press 2018-07-02 2018-05-31 /pmc/articles/PMC6030844/ /pubmed/29860484 http://dx.doi.org/10.1093/nar/gky471 Text en © The Author(s) 2018. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Web Server Issue Desvignes, Jean-Pierre Bartoli, Marc Delague, Valérie Krahn, Martin Miltgen, Morgane Béroud, Christophe Salgado, David VarAFT: a variant annotation and filtration system for human next generation sequencing data |
title | VarAFT: a variant annotation and filtration system for human next generation sequencing data |
title_full | VarAFT: a variant annotation and filtration system for human next generation sequencing data |
title_fullStr | VarAFT: a variant annotation and filtration system for human next generation sequencing data |
title_full_unstemmed | VarAFT: a variant annotation and filtration system for human next generation sequencing data |
title_short | VarAFT: a variant annotation and filtration system for human next generation sequencing data |
title_sort | varaft: a variant annotation and filtration system for human next generation sequencing data |
topic | Web Server Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6030844/ https://www.ncbi.nlm.nih.gov/pubmed/29860484 http://dx.doi.org/10.1093/nar/gky471 |
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