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Functional annotation of non-coding sequence variants
Identifying functionally relevant variants against the background of ubiquitous genetic variation is a major challenge in human genetics. For variants that fall in protein-coding regions our understanding of the genetic code and splicing allow us to identify likely candidates, but interpreting varia...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5015703/ https://www.ncbi.nlm.nih.gov/pubmed/24487584 http://dx.doi.org/10.1038/nmeth.2832 |
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author | Ritchie, Graham R. S. Dunham, Ian Zeggini, Eleftheria Flicek, Paul |
author_facet | Ritchie, Graham R. S. Dunham, Ian Zeggini, Eleftheria Flicek, Paul |
author_sort | Ritchie, Graham R. S. |
collection | PubMed |
description | Identifying functionally relevant variants against the background of ubiquitous genetic variation is a major challenge in human genetics. For variants that fall in protein-coding regions our understanding of the genetic code and splicing allow us to identify likely candidates, but interpreting variants that fall outside of genic regions is more difficult. Here we present a new tool, GWAVA, which supports prioritisation of non-coding variants by integrating a range of annotations. |
format | Online Article Text |
id | pubmed-5015703 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
record_format | MEDLINE/PubMed |
spelling | pubmed-50157032016-09-08 Functional annotation of non-coding sequence variants Ritchie, Graham R. S. Dunham, Ian Zeggini, Eleftheria Flicek, Paul Nat Methods Article Identifying functionally relevant variants against the background of ubiquitous genetic variation is a major challenge in human genetics. For variants that fall in protein-coding regions our understanding of the genetic code and splicing allow us to identify likely candidates, but interpreting variants that fall outside of genic regions is more difficult. Here we present a new tool, GWAVA, which supports prioritisation of non-coding variants by integrating a range of annotations. 2014-02-02 2014-03 /pmc/articles/PMC5015703/ /pubmed/24487584 http://dx.doi.org/10.1038/nmeth.2832 Text en Users may view, print, copy, download and text and data- mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:http://www.nature.com/authors/editorial_policies/license.html#terms |
spellingShingle | Article Ritchie, Graham R. S. Dunham, Ian Zeggini, Eleftheria Flicek, Paul Functional annotation of non-coding sequence variants |
title | Functional annotation of non-coding sequence variants |
title_full | Functional annotation of non-coding sequence variants |
title_fullStr | Functional annotation of non-coding sequence variants |
title_full_unstemmed | Functional annotation of non-coding sequence variants |
title_short | Functional annotation of non-coding sequence variants |
title_sort | functional annotation of non-coding sequence variants |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5015703/ https://www.ncbi.nlm.nih.gov/pubmed/24487584 http://dx.doi.org/10.1038/nmeth.2832 |
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