Nice looking five sets Venn diagrams in R

Question

In a paper I recently came across a nice 5 sets Venn diagram:

Would anyone know how to code producing such Venn diagram displays in R?

Most of the packages I looked at seem to produce the less clear version

Any thoughts?

EDIT: seems the Nature article used this web tool: http://bioinformatics.psb.ugent.be/webtools/Venn/ might still be nice to port it to some R package, especially the asymmetric Venns, which are currently not available in any package that I know of

Did you check the packages in [Venn Diagrams with R](http://stackoverflow.com/questions/1428946/venn-diagrams-with-r?rq=1)? — CL., Sep 07 '15 at 14:26
Yes I tried all of these! But they can only produce the fig at the bottom, not that at the top! Also some are restricted to 4 or fewer sets... — Tom Wenseleers, Sep 07 '15 at 14:34

Tom Wenseleers · Accepted Answer · 2019-03-14T14:17:57.237

32

For the record Adrian Dusa made a really nice new R package venn that makes Venn diagrams as above, for up to 7 sets :

library(venn)
venn(5, ilab=TRUE, zcolor = "style")

venn(7, ilab=TRUE, zcolor = "style")

Thanks Adrian for the cool package!

edited Mar 14 '19 at 14:17

answered Oct 14 '16 at 17:07

Tom Wenseleers

7,535
7
63
103

Could you provide a code example? – Herman Toothrot Jun 23 '22 at 20:21

score 9 · Answer 2 · edited Sep 17 '15 at 12:59

I also used the online Venn diagram generator at the University of Ghent Bioinformatics site and wanted my own function. The idea of course is to have each intersection region reasonably sized so that the text for the counts can all be the same size. Here is my attempt:

fiveCellVenn <- function(colorList=col2rgb(rainbow(5)),
                         cellCounts=seq(1,31,1),
                         cellLabels=c("one","two","three","four","five"),
                         saturation=.25){
  rotateVec <-function(vec,amount){
    return(c(vec[(amount+1):length(vec)], vec[1:amount]))
  }
  n=70
  xhull <- c()
  yhull <- c()
  for (i in 1:n){
    xhull <- c(xhull, cos((i*2*pi)/n))
    yhull <- c(yhull, sin((i*2*pi)/n))
  }
## The Venn cells begin as a 70-sided regular polygon
## plot(xhull, yhull)
## polygon(xhull, yhull)
## Multiply each unit vector in the hull by a scalar, arrived at by 
## iterative adjustment.
  adjust <-c(10,10.35,10.6,10.5,10.4,10.3,10.1,9.6,9,8.5,
             8,7.625,7.25,7.125,7,6.875,6.75,6.875,7,7.125,
             7.25,7.625,8.1,9.125,10.25,11.375,12.5,13.15,13.8,14.3,
             14.6,14.725,14.7,14.7,14.7,14.4,14.1,13.8,13.5,12.8,
             12.1,11.15,10.2,9.6,8.95,8.3,7.7,7,6.25,5.6,
             5,4.75,4.5,4.25,4,3.8,3.6,3.45,3.45,3.45,
             3.5,3.625,3.75,3.825,4,4.25,4.5,5.75,7.25,8.5)
  newxhull <- xhull*adjust
  newyhull <- yhull*adjust
## Text location was also done by hand:
  textLocationX <- c(-13,-3,8,9,-4,-7.5,7.5,-9,-8,4,6.5,-2,9,-4,1.4,4,-7.5,-3.5,7.5,-6,-6.5,6,1.5,4,-0.5,4.5,0,-5,-3.5,3.5,0)
  textLocationY <- c(1,12,8,-8,-12,6.5,4.5,1,-4,8.5,-6,8.5,-1.5,-8,-9,5,3.5,6,1.5,-6,-1.5,-2,8,-7,-6.5,2,5.5,2,-3.5,-4,0)
  textLocationMatrix <- matrix(cbind(textLocationX,textLocationY),nrow=31,ncol=2)
  plot(newxhull, newyhull, pch=".", xlim=c(-16,16), ylim=c(-16,16),
       axes=FALSE,xlab="",ylab="")
  newAdjust<-adjust
  for (i in 1:5){
    newxhull <- xhull*newAdjust
    newyhull <- yhull*newAdjust
    polygon(newxhull, newyhull, 
            border=rgb(colorList[1,i]/255, colorList[2,i]/255, colorList[3,i]/255, 1),
            lwd=2,
            col=rgb(colorList[1,i]/255, colorList[2,i]/255, colorList[3,i]/255,saturation))
    newAdjust <- rotateVec(newAdjust,14)
  }
  text(textLocationMatrix[,1], textLocationMatrix[,2],labels=as.character(cellCounts))
  text(textLocationMatrix[c(17,2,3,24,14),1]*c(2,1.25,1.5,2,2),
       textLocationMatrix[c(17,2,3,24,14),2]*c(2,1.35,1.5,2,2),
       labels=cellLabels)
##  uncomment and run to get points and grid for adjusting text location
##  points(textLocationMatrix[,1], textLocationMatrix[,2])
##  for (i in -16:16){
##   if (i%%5==0){
##     color="black"
##   }else{
##     color="lightblue"
##   }
##  abline(v=i,col=color)
##  abline(h=i, col=color)
##  }
}

Then

fiveCellVenn()

yields a Venn similar to your first one. I don't have the rep to post an image yet. You'll probably want to subdue the colors and move the cell names around.

Very nice! Many thanks for this - looks splendid! You could also consider smoothing the polygons slightly to make them look even nicer, as in http://gis.stackexchange.com/questions/24827/how-to-smooth-the-polygons-in-a-contour-map/24929#24929 Could be nice to generalize also to other nrs of sets. Maybe get in touch with one of the venn diagram R packages - they might be interested to include this one! — Tom Wenseleers, Sep 17 '15 at 12:28
with the spline.poly() function in the link above something along the lines of plot(newxhull,newyhull); polygon(spline.poly(as.data.frame(list(x=newxhull,y=newyhull))[-seq(1, length(newxhull), by = 2),],100,k=3)) could be used to smooth the polygons a bit — Tom Wenseleers, Sep 17 '15 at 12:54

score 3 · Answer 3 · edited Jul 05 '18 at 15:15

3

library(venn); library(tidyverse); library(stringr); 

p_th = 0.0;

data <- read_csv("finaldf.csv")
data

venn = 
  list(A = 
     data %>% 
     filter(CVA > p_th) %>% 
     .$phrase,
   B = 
     data %>% 
     filter(IHD > p_th) %>% 
     .$phrase,
   C = 
     data %>% 
     filter(CM > p_th) %>% 
     .$phrase,
   D = 
     data %>% 
     filter(ARR > p_th) %>% 
     .$phrase,
   E = 
     data %>% 
     filter(VD > p_th) %>% 
     .$phrase,
   G = 
     data %>% 
     filter(CHD > p_th) %>% 
     .$phrase);

png("ven.png", width = 800, height = 800)

venn.result =
  venn(venn, ilabels = TRUE, 
       zcolor = "style", size = 25, cexil = 1.2, cexsn = 1.5);


dev.off()

6 set Venn diagram

edited Jul 05 '18 at 15:15

Tung

26,371
7
91
115

answered Mar 15 '18 at 00:57

Vasuji

31
3

This looks great. Thanks for sharing! Can you make this more useful and reproducible by adding `dput(data)` to your answer? – Tung Jul 05 '18 at 15:15
1

@Dibakar how does the `final_df.csv` looks like – Nov 03 '21 at 06:22

score 0 · Answer 4 · answered Mar 20 '20 at 15:49

0

Maybe you can try VennDetail which will not only help you to generate the venndiagram and also give you the options to generate a 'vennpie' figure. You can also easily extract each subset based on the figure.

answered Mar 20 '20 at 15:49

bioguo

61
4

Nice looking five sets Venn diagrams in R

4 Answers4