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geneAttribution: trait agnostic identification of candidate genes associated with noncoding variation

MOTIVATION: We have developed geneAttribution, an R package that assigns candidate causal gene(s) to a risk variant identified by a genetic association study such as a GWAS. The method combines user-supplied functional annotation such as expression quantitative trait loci (eQTL) or Hi-C genome confo...

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Detalles Bibliográficos
Autores principales: Wuster, Arthur, Chang, Diana, Behrens, Timothy W, Bhangale, Tushar R
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5408921/
https://www.ncbi.nlm.nih.gov/pubmed/28035029
http://dx.doi.org/10.1093/bioinformatics/btw698
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author Wuster, Arthur
Chang, Diana
Behrens, Timothy W
Bhangale, Tushar R
author_facet Wuster, Arthur
Chang, Diana
Behrens, Timothy W
Bhangale, Tushar R
author_sort Wuster, Arthur
collection PubMed
description MOTIVATION: We have developed geneAttribution, an R package that assigns candidate causal gene(s) to a risk variant identified by a genetic association study such as a GWAS. The method combines user-supplied functional annotation such as expression quantitative trait loci (eQTL) or Hi-C genome conformation data and reports the most likely candidate genes. In the absence of annotation data, geneAttribution relies on the distances between the genes and the input variant. AVAILABILITY AND IMPLEMENTATION: The package is freely available from http://www.bioconductor.org/. A quick-start vignette is included with the package.
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spelling pubmed-54089212017-05-03 geneAttribution: trait agnostic identification of candidate genes associated with noncoding variation Wuster, Arthur Chang, Diana Behrens, Timothy W Bhangale, Tushar R Bioinformatics Applications Notes MOTIVATION: We have developed geneAttribution, an R package that assigns candidate causal gene(s) to a risk variant identified by a genetic association study such as a GWAS. The method combines user-supplied functional annotation such as expression quantitative trait loci (eQTL) or Hi-C genome conformation data and reports the most likely candidate genes. In the absence of annotation data, geneAttribution relies on the distances between the genes and the input variant. AVAILABILITY AND IMPLEMENTATION: The package is freely available from http://www.bioconductor.org/. A quick-start vignette is included with the package. Oxford University Press 2017-02-15 2016-11-29 /pmc/articles/PMC5408921/ /pubmed/28035029 http://dx.doi.org/10.1093/bioinformatics/btw698 Text en © The Author 2016. Published by Oxford University Press. 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 Applications Notes
Wuster, Arthur
Chang, Diana
Behrens, Timothy W
Bhangale, Tushar R
geneAttribution: trait agnostic identification of candidate genes associated with noncoding variation
title geneAttribution: trait agnostic identification of candidate genes associated with noncoding variation
title_full geneAttribution: trait agnostic identification of candidate genes associated with noncoding variation
title_fullStr geneAttribution: trait agnostic identification of candidate genes associated with noncoding variation
title_full_unstemmed geneAttribution: trait agnostic identification of candidate genes associated with noncoding variation
title_short geneAttribution: trait agnostic identification of candidate genes associated with noncoding variation
title_sort geneattribution: trait agnostic identification of candidate genes associated with noncoding variation
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5408921/
https://www.ncbi.nlm.nih.gov/pubmed/28035029
http://dx.doi.org/10.1093/bioinformatics/btw698
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