ggVennDiagram: An Intuitive, Easy-to-Use, and Highly Customizable R Package to Generate Venn Diagram

Venn diagrams are widely used diagrams to show the set relationships in biomedical studies. In this study, we developed ggVennDiagram, an R package that could automatically generate high-quality Venn diagrams with two to seven sets. The ggVennDiagram is built based on ggplot2, and it integrates the...

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Vydané v:Frontiers in genetics Ročník 12; s. 706907
Hlavní autori: Gao, Chun-Hui, Yu, Guangchuang, Cai, Peng
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Frontiers Media S.A 07.09.2021
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ISSN:1664-8021, 1664-8021
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Shrnutí:Venn diagrams are widely used diagrams to show the set relationships in biomedical studies. In this study, we developed ggVennDiagram, an R package that could automatically generate high-quality Venn diagrams with two to seven sets. The ggVennDiagram is built based on ggplot2, and it integrates the advantages of existing packages, such as venn, RVenn, VennDiagram, and sf. Satisfactory results can be obtained with minimal configurations. Furthermore, we designed comprehensive objects to store the entire data of the Venn diagram, which allowed free access to both intersection values and Venn plot sub-elements, such as set label/edge and region label/filling. Therefore, high customization of every Venn plot sub-element can be fulfilled without increasing the cost of learning when the user is familiar with ggplot2 methods. To date, ggVennDiagram has been cited in more than 10 publications, and its source code repository has been starred by more than 140 GitHub users, suggesting a great potential in applications. The package is an open-source software released under the GPL-3 license, and it is freely available through CRAN ( https://cran.r-project.org/package=ggVennDiagram ).
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This article was submitted to Computational Genomics, a section of the journal Frontiers in Genetics
Edited by: Alfredo Pulvirenti, University of Catania, Italy
Reviewed by: Gregorio Iraola, Institut Pasteur de Montevideo, Uruguay; Rifat Hamoudi, University of Sharjah, United Arab Emirates
ISSN:1664-8021
1664-8021
DOI:10.3389/fgene.2021.706907