Load all the source and libraries
source("http://bioconductor.org/biocLite.R")
## Bioconductor version 2.13 (BiocInstaller 1.12.0), ?biocLite for help
## Upgrade to R-3.0.1 or some packages may not load properly.
biocLite()
## BioC_mirror: http://bioconductor.org
## Using Bioconductor version 2.13 (BiocInstaller 1.12.0), R version 3.0.0.
biocLite("limma")
## BioC_mirror: http://bioconductor.org
## Using Bioconductor version 2.13 (BiocInstaller 1.12.0), R version 3.0.0.
## Installing package(s) 'limma'
##
## The downloaded source packages are in
## '/private/var/folders/nn/mky1r73s295cp1qbt_z8pls0ppkbr7/T/RtmpgsQ3Hn/downloaded_packages'
library(limma)
Load the data and create the data structure
hsb2 <- read.csv("http://www.ats.ucla.edu/stat/data/hsb2.csv")
attach(hsb2)
hw <- (write >= 60)
hm <- (math >= 60)
hr <- (read >= 60)
c3 <- cbind(hw, hm, hr)
a <- vennCounts(c3)
a
## hw hm hr Counts
## 1 0 0 0 113
## 2 0 0 1 18
## 3 0 1 0 8
## 4 0 1 1 8
## 5 1 0 0 12
## 6 1 0 1 8
## 7 1 1 0 11
## 8 1 1 1 22
## attr(,"class")
## [1] "VennCounts"
Plot the Venn diagram
vennDiagram(a)