ggVolcanoR: A Shiny app for customizable visualization of differential expression datasets

Volcano and other analytical plots (e.g., correlation plots, upset plots, and heatmaps) serve as important data visualization methods for transcriptomic and proteomic analyses. Customizable generation of these plots is fundamentally important for a better understanding of dysregulated expression dat...

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Bibliographic Details
Published in:Computational and structural biotechnology journal 2021-01, Vol.19, p.5735-5740
Main Authors: Mullan, Kerry A., Bramberger, Liesl M., Munday, Prithvi Raj, Goncalves, Gabriel, Revote, Jerico, Mifsud, Nicole A., Illing, Patricia T., Anderson, Alison, Kwan, Patrick, Purcell, Anthony W., Li, Chen
Format: Article
Language:English
Subjects:
Communications
Correlation plot
Data visualization
Differential expression data
Heatmap
Proteomics
Transcriptomics
Upset plot
Volcano plot
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Summary:Volcano and other analytical plots (e.g., correlation plots, upset plots, and heatmaps) serve as important data visualization methods for transcriptomic and proteomic analyses. Customizable generation of these plots is fundamentally important for a better understanding of dysregulated expression data and is therefore instrumental for the ensuing pathway analysis and biomarker identification. Here, we present an R-based Shiny application, termed ggVolcanoR, to allow for customizable generation and visualization of volcano plots, correlation plots, upset plots, and heatmaps for differential expression datasets, via a user-friendly interactive interface in both local executable version and web-based application without requiring programming expertise. Compared to currently existing packages, ggVolcanoR offers more practical options to optimize the generation of publication-quality volcano and other analytical plots for analyzing and comparing dysregulated genes/proteins across multiple differential expression datasets. In addition, ggVolcanoR provides an option to download the customized list of the filtered dysregulated expression data, which can be directly used as input for downstream pathway analysis. The source code of ggVolcanoR is available at https://github.com/KerryAM-R/ggVolcanoR and the webserver of ggVolcanoR 1.0 has been deployed and is freely available for academic purposes at https://ggvolcanor.erc.monash.edu/.
ISSN:2001-0370
2001-0370
DOI:10.1016/j.csbj.2021.10.020