votes                package:GolubRR                R Documentation

_C_o_m_p_u_t_e _t_h_e _v_o_t_e_s _f_o_r _e_a_c_h _g_e_n_e.

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

     Golub et al define a method they call weighted voting. This
     function computes the vote cast for each class.

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

     votes(eset, c)

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

    eset: An instance of the 'exprSet' class. 

       c: A categorical variable, defining two classes. 

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

     A vote is defined to be the absolute value of the difference
     between the observed value for a gene and the average of the two
     within sample means.  The vote is cast for the group with mean
     closest to the expressed value of the gene. The weights are
     computed using 'P'.

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

     A list with the following components. 

 closer : A genes by samples array indicating which class is closest.

    mns : The average of the two within group means.

     wts: The wts are per gene and are computed using 'P'.

   vote : The numerical vote, a genes by samples array.

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

     R. Gentleman

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

     Molecular Classification of Cancer: Class Discovery and Class
     Prediction by  Gene Expression Monitoring, Science, 531-537, 1999,
     T. R. Golub and D. K. Slonim and P. Tamayo and C. Huard and M.
     Gaasenbeek and J. P. Mesirov and H. Coller and M.L. Loh and J. R.
     Downing and M. A. Caligiuri and C. D. Bloomfield and E. S. Lander

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

     'P', 'P'

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

        library(golubEsets)
        vts <- votes(golubMerge[1:20,], golubMerge$ALL)

