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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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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8551465/
https://www.ncbi.nlm.nih.gov/pubmed/34745458
http://dx.doi.org/10.1016/j.csbj.2021.10.020
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author 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
author_facet 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
author_sort Mullan, Kerry A.
collection PubMed
description 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/.
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spelling pubmed-85514652021-11-04 ggVolcanoR: A Shiny app for customizable visualization of differential expression datasets 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 Comput Struct Biotechnol J Communications 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/. Research Network of Computational and Structural Biotechnology 2021-10-13 /pmc/articles/PMC8551465/ /pubmed/34745458 http://dx.doi.org/10.1016/j.csbj.2021.10.020 Text en © 2021 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Communications
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
ggVolcanoR: A Shiny app for customizable visualization of differential expression datasets
title ggVolcanoR: A Shiny app for customizable visualization of differential expression datasets
title_full ggVolcanoR: A Shiny app for customizable visualization of differential expression datasets
title_fullStr ggVolcanoR: A Shiny app for customizable visualization of differential expression datasets
title_full_unstemmed ggVolcanoR: A Shiny app for customizable visualization of differential expression datasets
title_short ggVolcanoR: A Shiny app for customizable visualization of differential expression datasets
title_sort ggvolcanor: a shiny app for customizable visualization of differential expression datasets
topic Communications
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8551465/
https://www.ncbi.nlm.nih.gov/pubmed/34745458
http://dx.doi.org/10.1016/j.csbj.2021.10.020
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