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Postgwas: Advanced GWAS Interpretation in R

We present a comprehensive toolkit for post-processing, visualization and advanced analysis of GWAS results. In the spirit of comparable tools for gene-expression analysis, we attempt to unify and simplify several procedures that are essential for the interpretation of GWAS results. This includes th...

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Detalles Bibliográficos
Autores principales: Hiersche, Milan, Rühle, Frank, Stoll, Monika
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3747239/
https://www.ncbi.nlm.nih.gov/pubmed/23977141
http://dx.doi.org/10.1371/journal.pone.0071775
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author Hiersche, Milan
Rühle, Frank
Stoll, Monika
author_facet Hiersche, Milan
Rühle, Frank
Stoll, Monika
author_sort Hiersche, Milan
collection PubMed
description We present a comprehensive toolkit for post-processing, visualization and advanced analysis of GWAS results. In the spirit of comparable tools for gene-expression analysis, we attempt to unify and simplify several procedures that are essential for the interpretation of GWAS results. This includes the generation of advanced Manhattan and regional association plots including rare variant display as well as novel interaction network analysis tools for the investigation of systems-biology aspects. Our package supports virtually all model organisms and represents the first cohesive implementation of such tools for the popular language R. Previous software of that range is dispersed over a wide range of platforms and mostly not adaptable for custom work pipelines. We demonstrate the utility of this package by providing an example workflow on a publicly available dataset.
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spelling pubmed-37472392013-08-23 Postgwas: Advanced GWAS Interpretation in R Hiersche, Milan Rühle, Frank Stoll, Monika PLoS One Research Article We present a comprehensive toolkit for post-processing, visualization and advanced analysis of GWAS results. In the spirit of comparable tools for gene-expression analysis, we attempt to unify and simplify several procedures that are essential for the interpretation of GWAS results. This includes the generation of advanced Manhattan and regional association plots including rare variant display as well as novel interaction network analysis tools for the investigation of systems-biology aspects. Our package supports virtually all model organisms and represents the first cohesive implementation of such tools for the popular language R. Previous software of that range is dispersed over a wide range of platforms and mostly not adaptable for custom work pipelines. We demonstrate the utility of this package by providing an example workflow on a publicly available dataset. Public Library of Science 2013-08-19 /pmc/articles/PMC3747239/ /pubmed/23977141 http://dx.doi.org/10.1371/journal.pone.0071775 Text en © 2013 Hiersche et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Hiersche, Milan
Rühle, Frank
Stoll, Monika
Postgwas: Advanced GWAS Interpretation in R
title Postgwas: Advanced GWAS Interpretation in R
title_full Postgwas: Advanced GWAS Interpretation in R
title_fullStr Postgwas: Advanced GWAS Interpretation in R
title_full_unstemmed Postgwas: Advanced GWAS Interpretation in R
title_short Postgwas: Advanced GWAS Interpretation in R
title_sort postgwas: advanced gwas interpretation in r
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3747239/
https://www.ncbi.nlm.nih.gov/pubmed/23977141
http://dx.doi.org/10.1371/journal.pone.0071775
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