xcluster2r {ctc} | R Documentation |
Converting Xcluster/Cluster output (.gtr or .atr) to R hclust file
xcluster2r(file,distance="euclidean",labels=FALSE,fast=FALSE,clean=FALSE,dec='.')
file |
the path of a Xcluster/Cluster file (.gtr or .atr) |
distance |
The distance measure used with Xcluster/Cluster. This must be one of
"euclidean" , "pearson" or "notcenteredpearson" .
Any unambiguous substring can be given. |
labels |
a logical value indicating whether we use labels values (in the .cdt file) or not. |
fast |
a logical value indicating whether we reorganize data
like R (Fast=FALSE ) or we let them like Xcluster/Cluster did |
clean |
a logical value indicating whether you want the true
distances (clean=FALSE ), or you want a clean dendogramme |
dec |
the character used in the file for decimal points |
See xcluster for more details.
An object of class hclust which describes the tree produced by the clustering process.
Xcluster is a C program made by Gavin Sherlock that performs hierarchical clustering, K-means and SOM.
Xcluster is copyrighted. To get or have information about Xcluster: http://genome-www.stanford.edu/~sherlock/cluster.html
Cluster is a program made by Michael Eisen that performs hierarchical clustering, K-means and SOM.
Cluster is copyrighted. To get or have information about Cluster: http://rana.lbl.gov/EisenSoftware.htm
Antoine Lucas, http://genopole.toulouse.inra.fr/~lucas/R
# Create data .Random.seed <- c(1, 416884367 ,1051235439) m <- matrix(rep(1,3*24),ncol=3) m[9:16,3] <- 3 ; m[17:24,] <- 3 #create 3 groups m <- m+rnorm(24*3,0,0.5) #add noise m <- floor(10*m)/10 #just one digits r2xcluster(m) # And once you have Xcluster program: # #system('Xcluster -f xcluster.txt -e 0 -p 0 -s 0 -l 0') #h <- xcluster2r('xcluster.gtr') #library(mva) #plot(h,hang=-1)