boot2fuzzy: function to write MapleTree files for viewing bootstrap...
In hopach: Hierarchical Ordered Partitioning and Collapsing Hybrid (HOPACH)

Description Usage Arguments Value Note Author(s) References See Also Examples

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.

1
2
3

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

`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`

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

Thank you to Lisa Simirenko <lsimirenko@lbl.gov> for providing HOPACH views in MapleTree, and to Karen Vranizan <vranizan@uclink.berkeley.edu> for her input. The MapleTree software can be downloaded from: http://sourceforge.net/projects/mapletree/

Katherine S. Pollard <kpollard@gladstone.ucsf.edu>

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

hopach, boothopach, bootmedoids, hopach2tree

#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)