02.Classes               package:limma               R Documentation

_C_l_a_s_s_e_s _D_e_f_i_n_e_d _b_y _t_h_i_s _P_a_c_k_a_g_e

_D_e_s_c_r_i_p_t_i_o_n:

     This package defines the following data classes.

      '_R_G_L_i_s_t'  A class used to store raw intensities as they are read
          in from an image analysis output file, usually by
          'read.maimages'.

      '_M_A_L_i_s_t'  Intensities converted to M-values and A-values, i.e.,
          to with-spot and whole-spot contrasts on the log-scale.
          Usually created from an 'RGList' using 'MA.RG' or
          'normalizeWithinArrays'. Objects of this class contain one
          row for each spot. There may be more than one spot and
          therefore more than one row for each probe.

      '_E_L_i_s_t_R_a_w'  A class to store raw intensities for one-channel
          microarray data. May or may not be background corrected.
          Usually created by 'read.maimages'.

      '_E_L_i_s_t'  A class to store normalized log2 expression values for
          one-channel microarray data. Usually created by
          'normalizeBetweenArrays'.

      '_M_A_r_r_a_y_L_M'  Store the result of fitting gene-wise linear models
          to the normalized intensities or log-ratios. Usually created
          by 'lmFit'. Objects of this class normally contain only one
          row for each unique probe.

      '_T_e_s_t_R_e_s_u_l_t_s'  Store the results of testing a set of contrasts
          equal to zero for each probe. Usually created by
          'decideTests'. Objects of this class normally contain one row
          for each unique probe.

     All these data classes obey many analogies with matrices. In the
     case of 'RGList', 'MAList', 'EListRaw' and 'EList', rows
     correspond to spots or probes and columns to arrays. In the case
     of 'MarrayLM', rows correspond to unique probes and the columns to
     parameters or contrasts. The functions 'summary', 'dim', 'length',
     'ncol', 'nrow', 'dimnames', 'rownames', 'colnames' have methods
     for these classes. Objects of any of these classes may be
     subsetted. Multiple data objects may be combined by rows (to add
     extra probes) or by columns (to add extra arrays).

     Furthermore all of these classes may be coerced to actually be of
     class 'matrix' using 'as.matrix', although this entails loss of
     information. Fitted model objects of class 'MArrayLM' can be
     coerced to class 'data.frame' using 'as.data.frame'.

     The first three classes belong to the virtual class
     'LargeDataObject'. A 'show' method is defined for
     'LargeDataOject's which uses the utility function 'printHead'.

_A_u_t_h_o_r(_s):

     Gordon Smyth