RankingEbam-methods       package:GeneSelector       R Documentation

_R_a_n_k_i_n_g _b_a_s_e_d _o_n _t_h_e _e_m_p_i_r_i_c_a_l _b_a_y_e_s _a_p_p_r_o_a_c_h _o_f _E_f_r_o_n

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

     The approach of Efron and colleagues is based on a mixture model
     for subpopulations: genes that are differentially expressed and
     those that are not. The posterior probability for differential
     expression serves as statistic. The function described below is
     merely a wrapper for the function 'z.ebam' from the package
     'siggenes'.

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

     The input (gene expression and class labels)  can be given in
     three different ways:


     _x = "_m_a_t_r_i_x", _y = "_n_u_m_e_r_i_c" signature 1

     _x = "_m_a_t_r_i_x", _y = "_f_a_c_t_o_r" signature 2

     _x = "_E_x_p_r_e_s_s_i_o_n_S_e_t", _y = "_c_h_a_r_a_c_t_e_r" signature 3

     For further argument and output information, consult  RankingEbam.

