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https://github.com/gaospecial/ggVennDiagram

A 'ggplot2' implement of Venn Diagram.
https://github.com/gaospecial/ggVennDiagram

venn-diagram venn-plot

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A 'ggplot2' implement of Venn Diagram.

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README 

        



# ggVennDiagram



[![](http://cranlogs.r-pkg.org/badges/grand-total/ggVennDiagram)](https://cran.r-project.org/package=ggVennDiagram)

[![](http://cranlogs.r-pkg.org/badges/last-month/ggVennDiagram)](https://cran.r-project.org/package=ggVennDiagram)

[![](https://img.shields.io/badge/doi-10.1002/imt2.177-blue.svg)](https://doi.org/10.1002/imt2.177)

[![](https://www.r-pkg.org/badges/version/ggVennDiagram?color=green)](https://cran.r-project.org/package=ggVennDiagram)

[![](https://img.shields.io/badge/devel%20version-1.5.2-green.svg)](https://github.com/gaospecial/ggVennDiagram)

[![](https://codecov.io/gh/gaospecial/ggVennDiagram/branch/master/graph/badge.svg?token=c365345d-e34c-40f6-b2c0-881b5b2841e7)](https://app.codecov.io/gh/gaospecial/ggVennDiagram)



‘`ggVennDiagram`’ enables fancy Venn plot with 2-7 sets and generates

publication quality figure. It also support upset plot with unlimited

number of sets from version 1.4.4.



## Installation



You can install the released version of ggVennDiagram from

[CRAN](https://CRAN.R-project.org) with:



``` r

install.packages("ggVennDiagram")

```



And the development version from [GitHub](https://github.com/) with:



``` r

# install.packages("devtools")

devtools::install_github("gaospecial/ggVennDiagram")

```



## Citation



If you find **ggVennDiagram** is useful and used it in academic papers,

you may cite this package as:



1.  Gao, C.-H., Chen, C., Akyol, T., Dușa, A., Yu, G., Cao, B., and

    Cai, P. (2024). ggVennDiagram: intuitive Venn diagram software

    extended. [iMeta](https://onlinelibrary.wiley.com/journal/2770596x)

    3, 69. doi:

    [10.1002/imt2.177](https://onlinelibrary.wiley.com/doi/full/10.1002/imt2.177).

2.  Gao, C.-H., Yu, G., and Cai, P. (2021). ggVennDiagram: An Intuitive,

    Easy-to-Use, and Highly Customizable R Package to Generate Venn

    Diagram. Frontiers in Genetics 12, 1598. doi:

    [10.3389/fgene.2021.706907](https://www.frontiersin.org/articles/10.3389/fgene.2021.706907/full).



## Features



![](https://vnote-1251564393.cos.ap-chengdu.myqcloud.com/picgo/202403141008626.png)



**Notes**



The ggVennDiagram Shiny app can be accessed at Shinyapps.io

(), or

`ggVennDiagram::launch_app()` in local machine.



The [TBtools](https://github.com/CJ-Chen/TBtools-II) plugin can be

accessed through its plugin store.



## Example



`ggVennDiagram` maps the fill color of each region to quantity, allowing

us to visually observe the differences between different parts.



``` r

library(ggVennDiagram)

genes <- paste("gene",1:1000,sep="")

set.seed(20231214)

x <- list(A=sample(genes,300),

          B=sample(genes,525),

          C=sample(genes,440),

          D=sample(genes,350))

```



`ggVennDiagram` return a `ggplot` object, the fill/edge colors can be

further modified with `ggplot` functions.



``` r

library(ggplot2)

ggVennDiagram(x) + scale_fill_gradient(low="grey90",high = "red")

```






``` r



ggVennDiagram(x, set_color = c("blue","red","green","purple"))

```






`ggVennDiagram` support 2-7 dimension Venn plot. The generated figure is

generally ready for publish. The main function `ggVennDiagram()` will

check how many items in the first parameter and call corresponding

function automatically.



The parameter `category.names` is set names. And the parameter `label`

can label how many items are included in each parts.



``` r

ggVennDiagram(x,category.names = c("Stage 1","Stage 2","Stage 3", "Stage4"))

```






``` r



ggVennDiagram(x,category.names = c("Stage 1","Stage 2","Stage 3", "Stage4"), label = "none")

```






Set `label_alpha = 0` to remove label background.



``` r

ggVennDiagram(x, label_alpha=0)

```






## Showing intersection values



*Note: you need to install the GitHub version to enable these

functions.*



We implemented the `process_region_data()` to get intersection values.



``` r

y <- list(

  A = sample(letters, 8),

  B = sample(letters, 8),

  C = sample(letters, 8),

  D = sample(letters, 8)

)



process_region_data(Venn(y))

#> # A tibble: 15 × 4

#>    id      name    item      count

#>              

#>  1 1       A            3

#>  2 2       B            1

#>  3 3       C            3

#>  4 4       D            0

#>  5 1/2     A/B          0

#>  6 1/3     A/C          1

#>  7 1/4     A/D          2

#>  8 2/3     B/C          1

#>  9 2/4     B/D          3

#> 10 3/4     C/D          1

#> 11 1/2/3   A/B/C        1

#> 12 1/2/4   A/B/D        1

#> 13 1/3/4   A/C/D        0

#> 14 2/3/4   B/C/D        1

#> 15 1/2/3/4 A/B/C/D      0

```



If only several items were included, intersections may also be viewed

interactively by `plotly` method (if you have two many items, this is

useless).



``` r

ggVennDiagram(y, show_intersect = TRUE)

```



In web browser or RStudio, you will get:






# Customizing your plot



There are three components in a Venn plot: 1) the set labels; 2) the

edge of sets; and 3) the filling regions and labels (optional) of each

parts. We separately stored these data in a structured `VennPlotData`

object, in which labels, edges and regions are stored as data frames.



In general, `ggVennDiagram()` plot a Venn in three steps:



- get the coordinates of a applicable shape from internal `shapes`

  datasets.

- calculate sub regions of sets, including both the shape regions and

  sets members, and return a `VennPlotData` object that includes all

  necessary definitions. We implement a number of set operations

  functions to do this job.

- plot using `ggplot2` functions.



Please check `vignette("fully-customed", package = "ggVennDiagram")` for

more information.



# Venn Diagram for more than four sets



If you have reviewed my codes, you may find it is easy to support Venn

Diagram for more than four sets, as soon as you find a ideal parameter

to generate more circles or ellipses in the plot. The key point is to

let the generated ellipses have exactly one intersection for each

combination.



## Venn Diagram of up to seven sets



From v1.0, `ggVennDiagram` can plot up to seven dimension Venn plot.

Please note that the shapes for this five sets diagram, as well as those

for six and seven sets, are imported from the original package

[`venn`](https://CRAN.R-project.org/package=venn) authored by Adrian

Dușa.



However, Venn Diagram for more than four sets may be meaningless in some

conditions, as some parts may be omitted in such ellipses. Therefore, it

is only useful in specific conditions. For example, if the set

intersection of all group are extremely large, you may use several

ellipses to draw a “flower” to show that.



``` r

x <- list(A=sample(genes,300),

          B=sample(genes,525),

          C=sample(genes,440),

          D=sample(genes,350),

          E=sample(genes,200),

          F=sample(genes,150),

          G=sample(genes,100))



# two dimension Venn plot

ggVennDiagram(x[1:2],label = "none")



# three dimension Venn plot

ggVennDiagram(x[1:3],label = "none")



# four dimension Venn plot

ggVennDiagram(x[1:4],label = "none")



# five dimension Venn plot

ggVennDiagram(x[1:5],label = "none")



# six dimension Venn plot

ggVennDiagram(x[1:6],label = "none")



# seven dimension Venn plot

ggVennDiagram(x,label = "none")

```






## Native support of upset plot



From version 1.4.4, `ggVennDiagram` supports unlimited number of sets,

as it can draw a plain upset plot automatically when number of sets is

more than 7.



``` r

# add an extra member in list

x$H = sample(genes,500)

ggVennDiagram(x)

#> Warning in ggVennDiagram(x): Only support 2-7 dimension Venn diagram. Will give

#> a plain upset plot instead.

#> Warning: Removed 1 rows containing missing values (`position_stack()`).

```






Upset plot can also be used by setting `force_upset = TRUE`.



``` r

ggVennDiagram(x[1:4], force_upset = TRUE, order.set.by = "name", order.intersect.by = "none")

```






Since upset plot is consisted with upper panel and lower panel, and left

panel and right panel, the appearance should be adjusted with different

conditions. We provide two parameters, which are `relative_height` and

`relative_width` to do this.



For example, if we want to give more space to lower panel, just change

the `relative_height` from 3 (the default) to 2.



``` r

venn = Venn(x)

plot_upset(venn, nintersects = 30, relative_height = 2, relative_width = 0.3)

```






# Reference



Adrian Dușa (2024) *venn: Draw Venn Diagrams*, R package version 1.12.

.