clusterComp-class        package:clusterStab        R Documentation

_C_l_a_s_s "_c_l_u_s_t_e_r_C_o_m_p" _a _c_l_a_s_s _f_o_r _t_e_s_t_i_n_g _t_h_e _s_t_a_b_i_l_i_t_y _o_f _c_l_u_s_t_e_r_s
_i_n _m_i_c_r_o_a_r_r_a_y _d_a_t_a

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

     A specialized class representation used for testing the stability
     of clusters in microarray data.

_O_b_j_e_c_t_s _f_r_o_m _t_h_e _C_l_a_s_s:

     Objects are usually created by a call to 'clusterComp', although
     technically objects can be created by calls of the form
     'new("clusterComp", ...)'. However, the latter is probably not
     worth doing.

_S_l_o_t_s:

     '_c_l_u_s_t_e_r_s': Object of class '"vector"' showing the cluster
          membership for each sample when using all the data. 

     '_p_e_r_c_e_n_t': Object of class '"vector"' containing the percentage of
          subsamples that resulted in the same class membership for all
          samples. 

     '_f_r_e_q': Object of class '"vector"' containing the subsampling
          percentage used. Defaults to 0.8. 

     '_c_l_u_s_t_e_r_n_u_m': Object of class '"vector"' containing the number of
          clusters tested.

     '_i_t_e_r_a_t_i_o_n_s': Object of class '"vector"' containing the number of
          iterations performed. Defaults to 100.

     '_m_e_t_h_o_d': Object of class '"vector"' containing the agglomerative
          method used. Options include "average", "centroid", "ward",
          "single", "mcquitty", or "median".

_M_e_t_h_o_d_s:

     _s_h_o_w 'signature(object = "clusterComp")': Give a nice summary of
          results. 

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

     James W. MacDonald <jmacdon@med.umich.edu>

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

     A. Ben-Hur, A. Elisseeff and I. Guyon. A stability based method
     for discovering structure in clustered data. Pacific Symposium on
     Biocomputing, 2002. Smolkin, M. and Ghosh, D. (2003).  Cluster
     stability scores for microarray data in cancer studies. BMC
     Bioinformatics 4, 36 - 42.

