Here is a post which discusses Venn diagram from list of clusters and co-occurring factors.

For easy solution use package venneuler:

require(venneuler)
v <- venneuler(c(A=450, B=1800, "A&B"=230))
plot(v)

For more advanced and customized solutions check package VennDiagram.

library(VennDiagram) 
venn.diagram(list(B = 1:1800, A = 1571:2020), fill = c("lightblue", "green"), 
             alpha = c(0.5, 0.5), lwd =0, "venn_diagram.tiff")

Something quite interesting that I learned from the VizBi conference (workshop on visualizing biological data) last month concerns depicting relationships linearly vs by area. Humans can proportionally relate objects of different lengths. That is if A = 10 and B = 5, A looks exactly twice as long, and if A = 10 and B = 9.8, B looks shorter. If A and B are depicted by area, things get difficult to discern because perceived differences in area relate to one another not by the power of 1.0 but by 0.6-0.7. Thus, one loses the degree of difference between objects when using area. · Although Venn diagrams are popular and convenient, this information is something to keep in mind when trying to depict the relationships. · Added 27 Apr 2011: Try Hohli at charts.hohli.com. With Hohli, you can create a Venn diagram and customize its look and feel. One can specify a title, choose data points, and alter the background. Hohli also allows you to create other charts, including scatter plots and other line charts.