xcluster2r {ctc}R Documentation

Importing Xcluster/Cluster output

Description

Converting Xcluster/Cluster output (.gtr or .atr) to R hclust file

Usage

xcluster2r(file,distance="euclidean",labels=FALSE,fast=FALSE,clean=FALSE,dec='.')

Arguments

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

Details

See xcluster for more details.

Value

An object of class hclust which describes the tree produced by the clustering process.

Note

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

Author(s)

Antoine Lucas, http://genopole.toulouse.inra.fr/~lucas/R

See Also

xcluster, r2xcluster, hclust

Examples

#    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)

[Package ctc version 1.2.7 Index]