hopach (version 2.32.0)

boot2fuzzy: function to write MapleTree files for viewing bootstrap estimated cluster membership probabilities based on hopach clustering results

Description

The MapleTree software (http://mapletree.sourceforge.net/) is an open source, cross-platform, visualization tool to graphically browse results of cluster analyses. The boot2fuzzy function takes a data matrix, plus corresponding hopach clustering output and bootstrap resampling output, and writes the (.cdt, .fct, and .mb) files needed to view these "fuzzy clustering" results in MapleTree.

Usage

boot2fuzzy(data, bootobj, hopach.genes, hopach.arrays = NULL, 
file="hopach", clust.wts = NULL, gene.wts = NULL, array.wts = NULL, 
gene.names = NULL)

Arguments

data

data matrix, data frame or exprSet of gene expression measurements. Each column corresponds to an array, and each row corresponds to a gene. All values must be numeric. Missing values are ignored.

bootobj

output of boothopach or bootmedoids applied to the genes - a matrix of bootstrap estimated cluster membership probabilities, with a row for each row in data and a column for each cluster.

hopach.genes

output of the hopach function applied to genes (rows of data.

hopach.arrays

optional output of the hopach function applied to arrays (columns of data.

file

name for the output files (the extensions .cdt, .mb and .fct will be added).

clust.wts

an optional vector of numeric weights for the clusters.

gene.wts

an optional vector of numeric weights for the genes.

array.wts

an optional vector of numeric weights for the arrays.

gene.names

optional vector of names or annotations for the genes, which can be different from the row names of data

Value

The function boot2fuzzy has no value. It writes three text files to the current working directory.

References

van der Laan, M.J. and Pollard, K.S. A new algorithm for hybrid hierarchical clustering with visualization and the bootstrap. Journal of Statistical Planning and Inference, 2003, 117, pp. 275-303.

http://www.stat.berkeley.edu/~laan/Research/Research_subpages/Papers/hopach.pdf

See Also

hopach, boothopach, bootmedoids, hopach2tree

Examples

#25 variables from two groups with 3 observations per variable
mydata<-rbind(cbind(rnorm(10,0,0.5),rnorm(10,0,0.5),rnorm(10,0,0.5)),cbind(rnorm(15,5,0.5),rnorm(15,5,0.5),rnorm(15,5,0.5)))
dimnames(mydata)<-list(paste("Var",1:25,sep=""),paste("Exp",1:3,sep=""))
mydist<-distancematrix(mydata,d="cosangle") #compute the distance matrix.

#clusters and final tree
clustresult<-hopach(mydata,dmat=mydist)

#bootstrap resampling
myobj<-boothopach(mydata,clustresult)

#write MapleTree files
boot2fuzzy(mydata,myobj,clustresult)