Thursday, March 3, 2011

OOMPA: Object-Oriented Microarray and Proteomic Analysis

http://bioinformatics.mdanderson.org/Software/OOMPA/


     source("http://bioinformatics.mdanderson.org/OOMPA/oompaLite.R")
     oompaLite() #A package needed for plotting colored dendrograms


Package Class Discovery

Clorored dendrogram


source("http://bioinformatics.mdanderson.org/OOMPA/oompaLite.R")
oompaLite()
oompainstall()


library(ClassDiscovery)

# simulate data from three different groups
d1 <- matrix(rnorm(100*10, rnorm(100, 0.5)), nrow=100, ncol=10, byrow=FALSE)
d2 <- matrix(rnorm(100*10, rnorm(100, 0.5)), nrow=100, ncol=10, byrow=FALSE)
d3 <- matrix(rnorm(100*10, rnorm(100, 0.5)), nrow=100, ncol=10, byrow=FALSE)
dd <- cbind(d1, d2, d3)

# perform hierarchical clustering using correlation
hc <- hclust(distanceMatrix(dd, 'pearson'), method='average')
cols <- rep(c('red', 'green', 'blue'), each=10)
labs <- paste('X', 1:30, sep='')

# plot the dendrogram with color-coded groups
plotColoredClusters(hc, labs=labs, cols=cols)

#cleanup
rm(d1, d2, d3, dd, hc, cols, labs)

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