boot2fuzzy {hopach} | R Documentation |
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.
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)