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SVA: software for annotating and visualizing sequenced human genomes
Summary: Here we present Sequence Variant Analyzer (SVA), a software tool that assigns a predicted biological function to variants identified in next-generation sequencing studies and provides a browser to visualize the variants in their genomic contexts. SVA also provides for flexible interaction w...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3129530/ https://www.ncbi.nlm.nih.gov/pubmed/21624899 http://dx.doi.org/10.1093/bioinformatics/btr317 |
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author | Ge, Dongliang Ruzzo, Elizabeth K. Shianna, Kevin V. He, Min Pelak, Kimberly Heinzen, Erin L. Need, Anna C. Cirulli, Elizabeth T. Maia, Jessica M. Dickson, Samuel P. Zhu, Mingfu Singh, Abanish Allen, Andrew S. Goldstein, David B. |
author_facet | Ge, Dongliang Ruzzo, Elizabeth K. Shianna, Kevin V. He, Min Pelak, Kimberly Heinzen, Erin L. Need, Anna C. Cirulli, Elizabeth T. Maia, Jessica M. Dickson, Samuel P. Zhu, Mingfu Singh, Abanish Allen, Andrew S. Goldstein, David B. |
author_sort | Ge, Dongliang |
collection | PubMed |
description | Summary: Here we present Sequence Variant Analyzer (SVA), a software tool that assigns a predicted biological function to variants identified in next-generation sequencing studies and provides a browser to visualize the variants in their genomic contexts. SVA also provides for flexible interaction with software implementing variant association tests allowing users to consider both the bioinformatic annotation of identified variants and the strength of their associations with studied traits. We illustrate the annotation features of SVA using two simple examples of sequenced genomes that harbor Mendelian mutations. Availability and implementation: Freely available on the web at http://www.svaproject.org. Contact: d.ge@duke.edu Supplementary information: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-3129530 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-31295302011-07-06 SVA: software for annotating and visualizing sequenced human genomes Ge, Dongliang Ruzzo, Elizabeth K. Shianna, Kevin V. He, Min Pelak, Kimberly Heinzen, Erin L. Need, Anna C. Cirulli, Elizabeth T. Maia, Jessica M. Dickson, Samuel P. Zhu, Mingfu Singh, Abanish Allen, Andrew S. Goldstein, David B. Bioinformatics Applications Note Summary: Here we present Sequence Variant Analyzer (SVA), a software tool that assigns a predicted biological function to variants identified in next-generation sequencing studies and provides a browser to visualize the variants in their genomic contexts. SVA also provides for flexible interaction with software implementing variant association tests allowing users to consider both the bioinformatic annotation of identified variants and the strength of their associations with studied traits. We illustrate the annotation features of SVA using two simple examples of sequenced genomes that harbor Mendelian mutations. Availability and implementation: Freely available on the web at http://www.svaproject.org. Contact: d.ge@duke.edu Supplementary information: Supplementary data are available at Bioinformatics online. Oxford University Press 2011-07-15 2011-05-29 /pmc/articles/PMC3129530/ /pubmed/21624899 http://dx.doi.org/10.1093/bioinformatics/btr317 Text en © The Author(s) 2011. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/2.5 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Applications Note Ge, Dongliang Ruzzo, Elizabeth K. Shianna, Kevin V. He, Min Pelak, Kimberly Heinzen, Erin L. Need, Anna C. Cirulli, Elizabeth T. Maia, Jessica M. Dickson, Samuel P. Zhu, Mingfu Singh, Abanish Allen, Andrew S. Goldstein, David B. SVA: software for annotating and visualizing sequenced human genomes |
title | SVA: software for annotating and visualizing sequenced human genomes |
title_full | SVA: software for annotating and visualizing sequenced human genomes |
title_fullStr | SVA: software for annotating and visualizing sequenced human genomes |
title_full_unstemmed | SVA: software for annotating and visualizing sequenced human genomes |
title_short | SVA: software for annotating and visualizing sequenced human genomes |
title_sort | sva: software for annotating and visualizing sequenced human genomes |
topic | Applications Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3129530/ https://www.ncbi.nlm.nih.gov/pubmed/21624899 http://dx.doi.org/10.1093/bioinformatics/btr317 |
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