GetStabilityGLM-methods     package:GeneSelector     R Documentation

_S_t_a_b_i_l_i_t_y _m_e_a_s_u_r_e_s _f_o_r _s_i_g_n_i_f_i_c_a_n_c_e _f_i_n_d_i_n_g_s

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

     Assesses the stability of the set of genes declared statistically
     significant for differential expression. To this end, p-values or
     adjusted p-values are used to generate binary response variables
     for a logistic regression model. As single covariate, the ranks
     obtained from the original dataset are used. Analogously to the
     linear model approach, weights are incorporated to attribute more
     importance to higher ranked genes. The deviance(s) resulting from
     these models are used as stability measure.

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

     The input is an object of class 'RepeatRanking'.


     _R_R = "_R_e_p_e_a_t_R_a_n_k_i_n_g" signature 1

     For further argument and output information, consult
     GetStabilityGLM.

