Abstract
Background
Visualization of orthogonal (disjoint) or overlapping datasets is a common task in bioinformatics. Few tools exist to automate the generation of extensivelycustomizable, highresolution 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 highlycustomizable, highresolution Venn diagrams with up to four sets and Euler diagrams with up to three sets.
Results
The 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 highdefinition TIFF files, simplifying the process of creating publicationquality figures and easing integration with established analysis pipelines.
Conclusions
The VennDiagram package allows the creation of high quality Venn and Euler diagrams in the R statistical environment.
Background
The visualization of complex datasets is an increasingly important part of biology. 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. twoway tables), network diagrams [1,2] and in some cases heatmaps [3,4]. Venn diagrams have seen increasing use due to their familiarity, easeofinterpretation, and graphical simplicity. 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 2^{n}1 possible areas created by the interaction of n sets. The use of simple geometrical shapes reduces figure complexity and size relative to spaceconsuming tables or network layouts.
However, despite this popularity, there are currently few packages for generating Venn diagrams in the widelyused R statistical environment. These packages are limited in their ability to generate highresolution, publicationquality Venn diagrams in that they allow little customization of colours, linetypes, labelplacement, and label font. Numerous specialcases are handled inappropriately, and the output is not usually in the format of highresolution, publicationquality TIFF files. Other, nonRbased local or webbased software capable of generating Venn diagrams exist, such as Venny [5], BioVenn [6], ConSet [7], and VennMaster [8]. All of these suffer from some of the weaknesses listed above. Further, integration into standard Rbased statistical/computational pipelines such as the widely used BioConductor libraries of the R statistical environment [9] is viable, but not technically trivial.
Additionally, if some intersecting or nonintersecting areas in a Venn diagram do not exist, another class of diagrams called Euler diagrams may be more desirable. Euler diagrams are equivalent to Venn diagrams when all intersecting and nonintersecting areas exist. However, areas containing zero elements are shown on Venn diagrams (by definition), whereas Euler diagrams show only nonzero areas. In many cases, Euler diagrams further reduce figure complexity, increase graphical accuracy and improve overall readability relative to Venn diagrams. Unfortunately, almost all existing packages cannot generate publicationquality Euler diagrams in R, although 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.
Implementation
The VennDiagram package has been developed in and designed for the R statistical environment. The R environment is opensource and available online under the GNU General Public License (GPLv2). R was chosen because of its opensource nature, versatile functions, and general preference within the bioinformatics community. The use of R should facilitate integration with existing dataanalysis pipelines. All code was designed and tested using version 2.12.1 (32bit and 64bit versions) of R. The VennDiagram package is available as Additional Files 1 (linux .tar.gz file) and 2 (windows .zip file).
Additional file 1. The VennDiagram R package as a linuxcompatible .tar.gz file
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Additional file 2. The VennDiagram R package as a windowscompatible .zip file
Format: ZIP Size: 64KB Download file
VennDiagram uses the grid package for graphics. The grid package is a base (standard) package available in all installations, and offers more manoeuvrability than default R graphics in terms of graphical options and the existence of modifiable grid objects. VennDiagram uses these features to dynamically stretch/compress diagrams to fit the dimensions of the output file and to offer a vast number of graphical options.
Results
Almost all graphical options in the VennDiagram package have been parameterized and made customizable. Default values were selected to generate sensible diagrams, so in simple cases a high level of customization is not required. Figure 1 highlights the diversity of parameterizations available. Four major graphical parameter groups exist: shapefill, shapeline, labels and titles. Shapefill refers to the colours within each circle or ellipse. All colours available in the R environment can be used, and alphablending can be adjusted on a pershape basis. Shapelines are the lines that surround each circle or ellipse. They can be entirely absent (figure 1C), solid (figures 1A and 1B), or any other R linetype available (figure 1D). Their colour can be changed, and each shape can have a separate set of parameters. Labels refer both to the captions describing each circle or ellipse and to the numbers within them. Again, these can be customized in terms of colour, fonttype, and fontsize with any available R parameter. The positions of caption labels can also be customized. Titles, which include the main title and the subtitle as demonstrated in figure 1D, can also be customized in the same way as labels.
Figure 1. The four types of Venn diagrams drawn by the VennDiagram package. A) A oneset Venn diagram showing rudimentary customizable features such as label font size, label font face, and shapefill. B) A twoset Venn diagram showing more advanced features such as scaling, individual shapefill specifications, and individual caption label placement. C) A threeset Venn diagram showing a different shapeline type ("transparent") and the "text" option of caption label placement where the caption labels are attached to area labels. D) A fourset Venn diagram showing a combination of all previous features plus the ability to customize titles. The code to generate all diagrams shown here is included in Additional File 3.
Beyond these specific graphic elements, VennDiagram also offers many general options, such as the scaling, rotation, or inversion of diagrams. Diagram scaling was implemented with the goal of displaying Venn diagrams where the graphical sizes of the partial areas (areas bound on all sides by curves and that cannot be further subdivided) actually correspond to the numerical values of the number of elements within each region. Scaling of twoset Venn diagrams and a select number of threeset Venn diagrams is possible  we discuss below the challenges of making this possible for all threeset cases. The use of scaling can sometimes lead to overlapping areas being too small for numeric labels. Figure 2, row 1, column 1 shows a programmatically generated connecting line that allows special handling of this case. Automatic recognition of a large number of Euler diagrams is implemented, but this mode can be deactivated with a functioncall parameter to plot standard Venn diagrams instead. Figure 2, row 1, columns 2 and 3 show two examples of twoset Euler diagrams. Rows 2 and 3 show a subset of implemented threeset Euler diagrams with row 3 showing those of the scalable variety. We note that figure 2 is presented in black and white to highlight compositional differences across diagrams, but the graphical parameters and customizations used in figure 1 are fully available. While VennDiagram defaults to writing graphics to highresolution TIFF files, if the filename parameter is set to NULL the raw grid object can be returned and used in any graphics mode available in R. The code to generate all figures is given in Additional File 3 and an example of all available parameterizations is shown in Additional File 4.
Figure 2. Selected Venn diagram special cases and Euler diagrams drawn by the VennDiagram package. Row 1, column 1: automatically drawn, customizable lines that optimize display of partial areas when individual partial areas become too small in twoset Venn diagrams. Row 1, column 2: a twoset Euler diagram showing total inclusion of one of the sets. Row 1, column 3: a twoset Euler diagram showing two distinct sets. Row 2, column 1: a threeset Euler diagram where one set has no discrete elements. Row 2, column 2: a threeset Euler diagram where one set has no discrete elements is totally included in one of the other two sets. Row 2, column 3: a threeset Euler diagram where two sets have no discrete elements and are included in a larger third set. Row 3, column 1: a threeset Euler diagram showing total inclusion of two sets that are distinct from the third set. Row 3, column 2: a threeset Euler diagram where one set is totally included in another set, which is itself totally included in the third set. Row 3, column 2: a threeset Euler diagram showing three distinct sets. The code to generate all diagrams shown here is included in Additional File 3.
Additional file 3. Code to generate all Venn diagrams in Figures 1 and 2.
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Additional file 4. Illustration of the parameters available in VennDiagram.
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This file can be viewed with: Microsoft PowerPoint Viewer
Discussion
During development of the VennDiagram package, it was discovered that it was impossible to draw accurate, scaled Venn diagrams with three sets using circles. This conundrum is illustrated in the following scenario. In a system of two circles A and B, the distances between the centres of the circles, d_{AB}, could be determined as long as the areas (A_{A }and A_{B }respectively) and the intersection area (A_{A }∩ A_{B}) are both known. This is possible because in a twocircle system a single A_{A }∩ A_{B }corresponds to a unique value for d_{AB}. Therefore, a system of three circles A, B, and C, d_{AB}, d_{BC}, d_{AC }could be calculated as long as A_{A}, A_{B}, A_{C}, A_{A }∩ A_{B}, A_{A }∩ A_{C}, A_{B }∩ A_{C }are all known. However, d_{AB}, d_{BC}, d_{AC }make a unique triangle, implying that a Venn diagram can be drawn without ever knowing the overall intersection A_{A }∩ A_{B }∩ A_{C}. In other words, 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. A_{A }∩ A_{B }∩ A_{C }= 0)! This conundrum results from the (arbitrary) choice of circles to represent set size, which reduces the degrees of freedom by one. Unique solutions can be identified by using ellipses or polygons to draw Venn diagrams but the resulting diagrams would lose the instant recognisability and familiarity associated with circular Venn diagrams, defeating the point of a convenient display of information. Noncircular diagrams would also require iterative algorithms to compute the positions and sizes of the shapes, greatly increasing computational burdens, as has been discussed by others [10]. Consequently, scaling of threeset Venn diagrams is disabled in the VennDiagram package. Similarly, Venn diagrams containing more than four sets [11,12] were not implemented in the VennDiagram package because they become too complex for intuitive visualization.
A general caveat when using Euler diagrams is that although they reduce the graphical complexity of some Venn diagrams, their nontraditional shapes may also be less recognizable in some cases. When empty areas are present, the user needs to choose between the familiarity of Venn diagrams and the increased accuracy of Euler diagrams. Figure 3 illustrates a situation where either a Venn or an Euler diagram may be appropriate depending on user preferences.
Figure 3. A sidebyside comparison of an Euler diagram and a Venn diagram for the same hypothetical sets. A) The Euler diagram shows only nonzero areas and can therefore be more graphically accurate. B) The Venn diagram shows the nonexistent area as an area with zero content. Though this is not graphically accurate, it preserves the recognisability of a Venn diagram.
The VennDiagram package handles all twoset Euler diagrams and the majority of all conceivable threeset Euler diagrams. Threeset Euler diagrams that could not be drawn using circles or ellipses are not supported. For example, an Euler diagram for the case where two nonintersecting sets comprise the third set cannot be drawn using circles and ellipses, though it may be drawn using polygons. This type of figure lacks a ready analytical layout and would require iterative fitting; no polygonrequiring Euler diagrams are available, but standard Venn diagrams are available for these few unsupported cases.
After comparing with other programs capable of generating Venn diagrams (Table 1), advantages of the VennDiagram package include:
• Drawing Euler diagrams using circles and/or ellipses with two or three sets
• Offering greater customizability to generate more elegant diagrams
• Availability in the widelyused R statistical environment
• Generating high resolution TIFF files that are standard in publications
Table 1. A comparison of the features of various programs capable of generating Venn diagrams.
Conclusions
The VennDiagram package advances both the easeofuse and the degree of customizability in the generation of Venn diagrams in a bioinformatics context. While other tools offer much of the functionality presented here, the implementation of all features together in the widelyused R statistical environment will promote the usage of automatically generated Venn diagrams within computational pipelines.
Availability and Requirements
Authors' contributions
HC and PCB conceived of the project. HC wrote the software, which HC and PCB tested and debugged. HC wrote the first draft of the manuscript, which all authors revised and approved.
Acknowledgements
The authors thank all members of the Boutros lab for support, and especially Dr. Kenneth Chu and Daryl Waggott for help in generating the windowscompatible version of this package.. This study was conducted with the support of the Ontario Institute for Cancer Research to PCB through funding provided by the Government of Ontario. This work was financially supported by grant number MOP57903 from the Canadian Institutes of Health Research (to PCB and Dr. Allan B. Okey).
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