xcluster2r                package:ctc                R Documentation

_I_m_p_o_r_t_i_n_g _X_c_l_u_s_t_e_r/_C_l_u_s_t_e_r _o_u_t_p_u_t

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

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

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

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

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

    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 dendrogram
          (see details below).

     dec: the character used in the file for decimal points

_D_e_t_a_i_l_s:

     See *xcluster* for more details.

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

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

_N_o_t_e:

     _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_: <URL:
     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_: <URL: http://rana.lbl.gov/EisenSoftware.htm>

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

     Antoine Lucas, <URL:
     http://mulcyber.toulouse.inra.fr/projects/amap/>

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

     Antoine Lucas and Sylvain Jasson, _Using amap and ctc Packages for
     Huge Clustering_, R News, 2006, vol 6, issue 5 pages 58-60.

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

     'xcluster', 'r2xcluster', 'hclust', 'hcluster'

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

     #    Create data
     set.seed(1)
     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')
     #plot(h,hang=-1)

