regressResult-class        package:ArrayTools        R Documentation

_C_l_a_s_s _t_o _C_o_n_t_a_i_n _t_h_e _R_e_g_r_e_s_s_i_o_n _R_e_s_u_l_t

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

     Class to Contain the Regression Result

_C_r_e_a_t_i_n_g _O_b_j_e_c_t_s:

     'regressResult' object is generally created from the 'regress'
     function See 'regress'

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


     '_I_D': contains probe ID/gene ID

     '_f_o_l_d_C_h_a_n_g_e': contains fold change value

     '_F_V_a_l_u_e': contains F statistics

     '_p_V_a_l_u_e': contains p value

     '_a_d_j_P_V_a_l': contains adjusted p value

     '_c_o_n_t_r_a_s_t': contains class '"contrastMatrix"'

     '_r_e_g_r_e_s_s_i_o_n_M_e_t_h_o_d': contains regression method: "limma",
          "regression",  or "permutation"

     '_a_d_j_u_s_t_m_e_n_t': contains method for multiple comparison adjustment

     '_s_i_g_n_i_f_i_c_a_n_t_I_n_d_e_x': contains a logical index indicating sigificant
          genes

     '_s_i_g_n_i_f_i_c_a_n_t_P_v_a_l_u_e_C_u_t_o_f_f': contains a cutoff p-value for choosing
          significant genes

     '_s_i_g_n_i_f_i_c_a_n_t_F_C_C_u_t_o_f_f': contains a fold change cutoff value for
          choosing significant genes 

     '_f_i_l_e_N_a_m_e': contains a file name for output purpose

     '_a_n_n_o_t_a_t_i_o_n': contains annotation

     '_n_o_r_m_a_l_i_z_a_t_i_o_n_M_e_t_h_o_d': contains normalization method - for output
          purpose

     '_f_i_l_t_e_r_M_e_t_h_o_d': contains filtered method - for output purpose

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


     _a_d_j_u_s_t_m_e_n_t 'signature(object = "regressResult")'{:  access the
          'adjustment' slot }

     _g_e_t_A_d_j_P 'signature(object = "regressResult")'{:   access the
          'adjPVal' slot }

     _g_e_t_A_n_n_o_t_a_t_i_o_n 'signature(object = "regressResult")'{:   access the
          'annotation' slot }

     _g_e_t_C_o_n_t_r_a_s_t 'signature(object = "regressResult")'{:   access the
          'contrast' slot }

     _g_e_t_F 'signature(object = "regressResult")'{:   access the 'FValue'
          slot}

     _g_e_t_F_C 'signature(object = "regressResult")'{:   access the
          'foldChange' slot }

     _g_e_t_F_C_C_u_t_o_f_f 'signature(object = "regressResult")'{:   access the
          'significantFCCutoff' slot}

     _g_e_t_F_i_l_e_N_a_m_e 'signature(object = "regressResult")'{:   access the
          'fileName' slot }

     _g_e_t_F_i_l_t_e_r_M_e_t_h_o_d 'signature(object = "regressResult")'{:   access
          the 'filterMethod' slot }

     _g_e_t_I_D 'signature(object = "regressResult")'{:   access the 'ID'
          slot  }

     _g_e_t_I_n_d_e_x 'signature(object = "regressResult")'{:   access the
          'significantIndex' slot}

     _g_e_t_N_o_r_m_a_l_i_z_a_t_i_o_n_M_e_t_h_o_d 'signature(object = "regressResult")'{:  
          access the 'normalizationMethod' slot}

     _g_e_t_P 'signature(object = "regressResult")'{:   access the 'pValue'
          slot }

     _g_e_t_P_C_u_t_o_f_f 'signature(object = "regressResult")'{:   access the
          'significantPvalueCutoff' slot }

     _O_u_t_p_u_t_2_H_T_M_L 'signature(object = "regressResult")'{:   create HTML
          file for sigificant genes in regressionResult}

     _r_e_g_r_e_s_s_i_o_n_M_e_t_h_o_d 'signature(object = "regressResult")'{:   access
          the 'regressionMethod' slot}

     _s_e_l_e_c_t_S_i_g_G_e_n_e 'signature(object = "regressResult")'{:   select
          significant genes for 'regressionResult' class}

     _s_h_o_w 'signature(object = "regressResult")'{:   print
          'regressResult'}

     _S_o_r_t 'signature(x = "regressResult")'{:   sort 'regressResult'}

     _s_u_m_m_a_r_y 'signature(object = "regressResult")'{:   print the
          summary for 'regressResult'}

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

     Xiwei Wu, Arthur Li

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

     data(eSetExample)
     design<- new("designMatrix", target=pData(eSetExample), covariates = "Treatment")
     contrast<- new("contrastMatrix", design.matrix = design, 
         compare1 = "Treated", compare2 = "Control")
     result<- regress(eSetExample, contrast)

