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gtrellis: an R/Bioconductor package for making genome-level Trellis graphics

BACKGROUND: Trellis graphics are a visualization method that splits data by one or more categorical variables and displays subsets of the data in a grid of panels. Trellis graphics are broadly used in genomic data analysis to compare statistics over different categories in parallel and reveal multiv...

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Detalles Bibliográficos
Autores principales: Gu, Zuguang, Eils, Roland, Schlesner, Matthias
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4835841/
https://www.ncbi.nlm.nih.gov/pubmed/27089965
http://dx.doi.org/10.1186/s12859-016-1051-4
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author Gu, Zuguang
Eils, Roland
Schlesner, Matthias
author_facet Gu, Zuguang
Eils, Roland
Schlesner, Matthias
author_sort Gu, Zuguang
collection PubMed
description BACKGROUND: Trellis graphics are a visualization method that splits data by one or more categorical variables and displays subsets of the data in a grid of panels. Trellis graphics are broadly used in genomic data analysis to compare statistics over different categories in parallel and reveal multivariate relationships. However, current software packages to produce Trellis graphics have not been designed with genomic data in mind and lack some functionality that is required for effective visualization of genomic data. RESULTS: Here we introduce the gtrellis package which provides an efficient and extensible way to visualize genomic data in a Trellis layout. gtrellis provides highly flexible Trellis layouts which allow efficient arrangement of genomic categories on the plot. It supports multiple-track visualization, which makes it straightforward to visualize several properties of genomic data in parallel to explain complex relationships. In addition, gtrellis provides an extensible framework that allows adding user-defined graphics. CONCLUSIONS: The gtrellis package provides an easy and effective way to visualize genomic data and reveal high dimensional relationships on a genome-wide scale. gtrellis can be flexibly extended and thus can also serve as a base package for highly specific purposes. gtrellis makes it easy to produce novel visualizations, which can lead to the discovery of previously unrecognized patterns in genomic data. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-016-1051-4) contains supplementary material, which is available to authorized users.
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spelling pubmed-48358412016-04-20 gtrellis: an R/Bioconductor package for making genome-level Trellis graphics Gu, Zuguang Eils, Roland Schlesner, Matthias BMC Bioinformatics Software BACKGROUND: Trellis graphics are a visualization method that splits data by one or more categorical variables and displays subsets of the data in a grid of panels. Trellis graphics are broadly used in genomic data analysis to compare statistics over different categories in parallel and reveal multivariate relationships. However, current software packages to produce Trellis graphics have not been designed with genomic data in mind and lack some functionality that is required for effective visualization of genomic data. RESULTS: Here we introduce the gtrellis package which provides an efficient and extensible way to visualize genomic data in a Trellis layout. gtrellis provides highly flexible Trellis layouts which allow efficient arrangement of genomic categories on the plot. It supports multiple-track visualization, which makes it straightforward to visualize several properties of genomic data in parallel to explain complex relationships. In addition, gtrellis provides an extensible framework that allows adding user-defined graphics. CONCLUSIONS: The gtrellis package provides an easy and effective way to visualize genomic data and reveal high dimensional relationships on a genome-wide scale. gtrellis can be flexibly extended and thus can also serve as a base package for highly specific purposes. gtrellis makes it easy to produce novel visualizations, which can lead to the discovery of previously unrecognized patterns in genomic data. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-016-1051-4) contains supplementary material, which is available to authorized users. BioMed Central 2016-04-18 /pmc/articles/PMC4835841/ /pubmed/27089965 http://dx.doi.org/10.1186/s12859-016-1051-4 Text en © Gu et al. 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Software
Gu, Zuguang
Eils, Roland
Schlesner, Matthias
gtrellis: an R/Bioconductor package for making genome-level Trellis graphics
title gtrellis: an R/Bioconductor package for making genome-level Trellis graphics
title_full gtrellis: an R/Bioconductor package for making genome-level Trellis graphics
title_fullStr gtrellis: an R/Bioconductor package for making genome-level Trellis graphics
title_full_unstemmed gtrellis: an R/Bioconductor package for making genome-level Trellis graphics
title_short gtrellis: an R/Bioconductor package for making genome-level Trellis graphics
title_sort gtrellis: an r/bioconductor package for making genome-level trellis graphics
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4835841/
https://www.ncbi.nlm.nih.gov/pubmed/27089965
http://dx.doi.org/10.1186/s12859-016-1051-4
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