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Glimma: interactive graphics for gene expression analysis
MOTIVATION: Summary graphics for RNA-sequencing and microarray gene expression analyses may contain upwards of tens of thousands of points. Details about certain genes or samples of interest are easily obscured in such dense summary displays. Incorporating interactivity into summary plots would enab...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5870845/ https://www.ncbi.nlm.nih.gov/pubmed/28203714 http://dx.doi.org/10.1093/bioinformatics/btx094 |
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author | Su, Shian Law, Charity W Ah-Cann, Casey Asselin-Labat, Marie-Liesse Blewitt, Marnie E Ritchie, Matthew E |
author_facet | Su, Shian Law, Charity W Ah-Cann, Casey Asselin-Labat, Marie-Liesse Blewitt, Marnie E Ritchie, Matthew E |
author_sort | Su, Shian |
collection | PubMed |
description | MOTIVATION: Summary graphics for RNA-sequencing and microarray gene expression analyses may contain upwards of tens of thousands of points. Details about certain genes or samples of interest are easily obscured in such dense summary displays. Incorporating interactivity into summary plots would enable additional information to be displayed on demand and facilitate intuitive data exploration. RESULTS: The open-source Glimma package creates interactive graphics for exploring gene expression analysis with a few simple R commands. It extends popular plots found in the limma package, such as multi-dimensional scaling plots and mean-difference plots, to allow individual data points to be queried and additional annotation information to be displayed upon hovering or selecting particular points. It also offers links between plots so that more information can be revealed on demand. Glimma is widely applicable, supporting data analyses from a number of well-established Bioconductor workflows (limma, edgeR and DESeq2) and uses D3/JavaScript to produce HTML pages with interactive displays that enable more effective data exploration by end-users. Results from Glimma can be easily shared between bioinformaticians and biologists, enhancing reporting capabilities while maintaining reproducibility. AVAILABILITY AND IMPLEMENTATION: The Glimma R package is available from http://bioconductor.org/packages/Glimma/. |
format | Online Article Text |
id | pubmed-5870845 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-58708452018-03-29 Glimma: interactive graphics for gene expression analysis Su, Shian Law, Charity W Ah-Cann, Casey Asselin-Labat, Marie-Liesse Blewitt, Marnie E Ritchie, Matthew E Bioinformatics Applications Notes MOTIVATION: Summary graphics for RNA-sequencing and microarray gene expression analyses may contain upwards of tens of thousands of points. Details about certain genes or samples of interest are easily obscured in such dense summary displays. Incorporating interactivity into summary plots would enable additional information to be displayed on demand and facilitate intuitive data exploration. RESULTS: The open-source Glimma package creates interactive graphics for exploring gene expression analysis with a few simple R commands. It extends popular plots found in the limma package, such as multi-dimensional scaling plots and mean-difference plots, to allow individual data points to be queried and additional annotation information to be displayed upon hovering or selecting particular points. It also offers links between plots so that more information can be revealed on demand. Glimma is widely applicable, supporting data analyses from a number of well-established Bioconductor workflows (limma, edgeR and DESeq2) and uses D3/JavaScript to produce HTML pages with interactive displays that enable more effective data exploration by end-users. Results from Glimma can be easily shared between bioinformaticians and biologists, enhancing reporting capabilities while maintaining reproducibility. AVAILABILITY AND IMPLEMENTATION: The Glimma R package is available from http://bioconductor.org/packages/Glimma/. Oxford University Press 2017-07-01 2017-02-15 /pmc/articles/PMC5870845/ /pubmed/28203714 http://dx.doi.org/10.1093/bioinformatics/btx094 Text en © The Author 2017. 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 Su, Shian Law, Charity W Ah-Cann, Casey Asselin-Labat, Marie-Liesse Blewitt, Marnie E Ritchie, Matthew E Glimma: interactive graphics for gene expression analysis |
title | Glimma: interactive graphics for gene expression analysis |
title_full | Glimma: interactive graphics for gene expression analysis |
title_fullStr | Glimma: interactive graphics for gene expression analysis |
title_full_unstemmed | Glimma: interactive graphics for gene expression analysis |
title_short | Glimma: interactive graphics for gene expression analysis |
title_sort | glimma: interactive graphics for gene expression analysis |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5870845/ https://www.ncbi.nlm.nih.gov/pubmed/28203714 http://dx.doi.org/10.1093/bioinformatics/btx094 |
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