VennDiagram: a package for the generation of highly-customizable Venn and Euler diagrams in R

Hanbo Chen,Paul C Boutros

doi:10.1186/1471-2105-12-35

Abstract

BackgroundVisualization of orthogonal (disjoint) or overlapping datasets is a common task in bioinformatics. Few tools exist to automate the generation of extensively-customizable, high-resolution Venn and Euler diagrams in the R statistical environment. To fill this gap we introduce VennDiagram, an R package that enables the automated generation of highly-customizable, high-resolution Venn diagrams with up to four sets and Euler diagrams with up to three sets.ResultsThe VennDiagram package offers the user the ability to customize essentially all aspects of the generated diagrams, including font sizes, label styles and locations, and the overall rotation of the diagram. We have implemented scaled Venn and Euler diagrams, which increase graphical accuracy and visual appeal. Diagrams are generated as high-definition TIFF files, simplifying the process of creating publication-quality figures and easing integration with established analysis pipelines.ConclusionsThe VennDiagram package allows the creation of high quality Venn and Euler diagrams in the R statistical environment.

Highlights

Visualization of orthogonal or overlapping datasets is a common task in bioinformatics
Almost all existing packages cannot generate publicationquality Euler diagrams in R, VennEuler does generate Euler diagrams. To address these issues we introduce VennDiagram, an R package for generating highly customizable, highresolution Venn diagrams with up to four sets and Euler diagrams of two or three sets in the R statistical environment
The size of the overlap between all three circles does not alter the presentation of scaled Venn diagrams – the area is unchanged even if one system has zero overall intersection (i.e. AA ∩ AB ∩ AC = 0)! This conundrum results from the choice of circles to represent set size, which reduces the degrees of freedom by one

Summary

Introduction

Visualization of orthogonal (disjoint) or overlapping datasets is a common task in bioinformatics. Few tools exist to automate the generation of extensively-customizable, high-resolution Venn and Euler diagrams in the R statistical environment. Many experiments involve the integration of multiple datasets to understand complementary aspects of biology. These overlapping results can be visualized in a number of ways, including textual tables (e.g. two-way tables), network diagrams [1,2] and in some cases heatmaps [3,4]. For the purpose of this publication, Venn diagrams can be defined as diagrams that use simple geometrical shapes such as circles and ellipses to display all 2n-1 possible areas created by the interaction of n sets. The use of simple geometrical shapes reduces figure complexity and size relative to space-consuming tables or network layouts

Results

Discussion

Conclusion