Tan Hui Hui Jenny wrote:
I'm trying to plot Venn diagrams with more than 3 sets (5 actually) in order to
describe graphically the genetic variation between populations.
I tried the limma library but realised it can only plot 3 sets.
Is there any solution? Of course I could plot the chart manually but it'll take too long (have other datasets)..... One of my dataset is given below.
Hi Jenny,
Best I could do is four sets. The code is a bit rough but consistent
with the vennDiagram function in the limma package.
Jim
show.circle<-function(x,y,radius,border=NULL,col=NA) {
angles<-seq(0,2*pi,by=0.04*pi)
xpos<-cos(angles)*radius+x
ypos<-sin(angles)*radius+y
polygon(xpos,ypos)
}
venn4<-function(vo,mar=rep(1,4)) {
dimvo<-dim(vo)
if(dimvo[2] != 4)
stop("Usage: venn4(vo,mar=rep(1,4))/n/twhere vo has 4 columns")
plot(0,0,type="n",xlim=c(-2,2),ylim=c(-2,2),xlab="",ylab="",axes=FALSE)
par(mar=mar)
show.circle(-0.5,0.5,1.5)
show.circle(0.5,0.5,1.5)
show.circle(-0.5,-0.5,1.5)
show.circle(0.5,-0.5,1.5)
outside<-sum(apply(vo,1,sum) == 0)
text(-1.2,1.4,"A")
text(1.2,1.4,"B")
text(-1.2,-1.1,"C")
text(1.2,-1.1,"D")
text(0,1.4,"AB")
text(-1.3,0.15,"AC")
text(1.2,0.15,"BD")
text(0,-1.1,"CD")
text(-0.6,0.9,"ABC")
text(0.6,0.9,"ABD")
text(-0.83,-0.5,"ACD")
text(0.83,-0.5,"BCD")
text(0,0.1,"ABCD")
par(xpd=TRUE,cex=1.5)
text(0,-2.4,outside)
onlyone<-apply(vo,1,sum) == 1
A<-sum(onlyone & vo[,1])
text(-1.2,1.1,A)
B<-sum(onlyone & vo[,2])
text(1.2,1.1,B)
C<-sum(onlyone & vo[,3])
text(-1.2,-1.4,C)
D<-sum(onlyone & vo[,4])
text(1.2,-1.4,D)
onlytwo<-apply(vo,1,sum) == 2
AB<-sum(onlytwo & vo[,1] & vo[,2])
text(0,1.1,AB)
AC<-sum(onlytwo & vo[,1] & vo[,3])
text(-1.3,-0.15,AC)
BD<-sum(onlytwo & vo[,2] & vo[,4])
text(1.2,-0.15,BD)
CD<-sum(onlytwo & vo[,3] & vo[,4])
text(0,-1.4,CD)
onlythree<-apply(vo,1,sum) == 3
ABC<-sum(onlythree & vo[,1] & vo[,2] & vo[,3])
text(-0.74,0.65,ABC)
ABD<-sum(onlythree & vo[,1] & vo[,2] & vo[,4])
text(0.74,0.65,ABD)
ACD<-sum(onlythree & vo[,1] & vo[,3] & vo[,4])
text(-0.7,-0.75,ACD)
BCD<-sum(onlythree & vo[,2] & vo[,3] & vo[,4])
text(0.7,-0.75,BCD)
ABCD<-sum(apply(vo,1,sum) == 4)
text(0,-0.2,ABCD)
par(mar=c(5,4,4,2)+0.1,xpd=FALSE,cex=1)
}
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