vennpieR: combination of venn diagram and pie chart in R

I was wondering how to draw a venn diagram like pie chart in R, to show the distribution of my RNA-seq reads mapped onto different annotation regions (e.g. intergenic, intron, exons etc.). A google search returns several options, including the nice one from Xiaopeng's bam2x (see below). However, he told me it's not released yet. And it's javascript based.

Why not I just make one in R? 

Here is the design scratch:

And here is example code:

	## data input (number of reads mapped to each category)
	total=100
	rRNA=5 # mapped to nuclear rRNA regions
	mtRNA=7 # mapped to mitochondria genome
	# for the rest of above, then we divide into different category, like http://www.biomedcentral.com/1741-7007/8/149 did.
	intergenic=48
	introns=12
	exons=30
	upstream=3
	downstream=6
	not_near_genes=40
	rest=total-rRNA-mtRNA
	genic=rest-intergenic
	introns_and_exons=introns+exons-genic
	# parameter for pie chart
	iniR=0.2 # initial radius
	colors=list(NO='white',total='black',mtRNA='#e5f5e0',rRNA='#a1d99b',genic='#3182bd',intergenic='#fec44f',introns='#fc9272',exons='#9ecae1',upstream='#ffeda0',downstream='#fee0d2',not_near_genes='#d95f0e')
	library('plotrix')
	# from outer circle to inner circle
	#0 circle: blank
	pie(1, radius=iniR, init.angle=90, col=c('white'), border = NA, labels='')
	#4 circle: show genic:exons and intergenic:downstream
	floating.pie(0,0,c(exons, genic-exons+not_near_genes, downstream, mtRNA+rRNA+intergenic-not_near_genes-downstream),radius=5*iniR, startpos=pi/2, col=as.character(colors[c('exons','NO','downstream','NO')]),border=NA)
	#3 circle: show genic:introns and intergenic:not_near_genes | upstream
	floating.pie(0,0,c(genic-introns, introns, not_near_genes, intergenic-upstream-not_near_genes, upstream, mtRNA+rRNA),radius=4*iniR, startpos=pi/2, col=as.character(colors[c('NO','introns','not_near_genes','NO','upstream','NO')]),border=NA)
	#2 circle: divide the rest into genic and intergenic
	floating.pie(0,0,c(genic, intergenic, mtRNA+rRNA),radius=3*iniR, startpos=pi/2, col=as.character(colors[c('genic','intergenic','NO')]),border=NA)
	#1 circle: for rRNA+mtRNA+rest
	floating.pie(0,0, c(rest, rRNA,mtRNA), radius=2*iniR, startpos=pi/2, col=as.character(colors[c('NO','rRNA','mtRNA')]), border = NA)
	legend(0, 5*iniR, gsub("_"," ",names(colors)[-1]), col=as.character(colors[-1]), pch=19,bty='n', ncol=2)
	## or, in one column with reads count and %
	#names=gsub("_"," ",names(colors)[-1])
	#values = sapply(names(colors)[-1], get)
	#percent=format(100*values/total, digits=2, trim=T)
	#values = format(values, big.mark=",", scientific=FALSE, trim=T)
	#cl=as.character(colors[-1])
	#pchs=rep(19, length(cl)); pchs[1]=1;
	#legend(0, 5*iniR, paste(names," (",values,", ", percent,"%)", sep=""), col=cl, pch=pchs,bty='n', ncol=1, cex=0.6)

view raw venn_pie_chart.r hosted with ❤ by GitHub

Here is output:

You can also use par(mfrow=c(n,m)) to put multiple venn pieagram in one figure.