boot2fuzzy              package:hopach              R Documentation

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_D_e_s_c_r_i_p_t_i_o_n:

     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.

_U_s_a_g_e:

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

_A_r_g_u_m_e_n_t_s:

    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'

_V_a_l_u_e:

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

_N_o_t_e:

     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/

_A_u_t_h_o_r(_s):

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

_R_e_f_e_r_e_n_c_e_s:

     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.

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

_S_e_e _A_l_s_o:

     'hopach', 'boothopach', 'bootmedoids', 'hopach2tree'

_E_x_a_m_p_l_e_s:

     #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)

