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

• DOI: 10.1016/j.csbj.2021.10.020
• Publication Date: 2021-10-13T23:25:21Z
• Authors: Kerry A. Mullan; Liesl M. Bramberger; Prithvi Raj Munday; Gabriel Goncalves; Jerico Revote; Nicole A. Mifsud; Patricia T. Illing; Alison Anderson; Patrick Kwan; Anthony W. Purcell; Chen Li
• Keywords: Executable; Identification; Expression (computer science)

Volcano and other analytical plots (e.g., correlation plots, upset heatmaps) serve as important data visualization methods for transcriptomic proteomic analyses. Customizable generation of these is fundamentally a better understanding dysregulated expression therefore instrumental the ensuing pathway analysis biomarker identification. Here, we present an R-based Shiny application, termed ggVolcanoR, to allow customizable volcano heatmaps differential datasets, via user-friendly interactive interface in both local executable version web-based application without requiring programming expertise. Compared currently existing packages, ggVolcanoR offers more practical options optimize publication-quality analyzing comparing genes/proteins across multiple datasets. In addition, provides option download customized list filtered data, which can be directly used input downstream analysis. The source code available at https://github.com/KerryAM-R/ggVolcanoR webserver 1.0 has been deployed freely academic purposes https://ggvolcanor.erc.monash.edu/.