maigesRaw-class          package:maigesPack          R Documentation

_m_a_i_g_e_s_R_a_w _c_l_a_s_s, _s_t_o_r_e _r_a_w _m_i_c_r_o_a_r_r_a_y _d_a_t_a_s_e_t_s

_D_e_s_c_r_i_p_t_i_o_n:

     This class describes objects to handle intensity values and
     information about genes and samples used in the data. Objects of
     this class are obtained from class 'maigesPreRaw' using function
     'createMaigesRaw'.

_D_e_t_a_i_l_s:

     This class of objects defines a real raw object that is used to do
     the normalisation. Objects of this class are generated from
     objects of class 'maigesPreRaw' using the function
     'createMaigesRaw'. Here it is possible to do several plots for
     exploratory analysis using functions from _marray_ package. Using
     the function 'selSpots', you select spots to use in the
     normalisation method, that is done by the functions 'normLoc',
     'normOLIN', 'normRepLoess', 'normScaleLimma' and
     'normScaleMarray'.

_S_l_o_t_s:


     '_S_f': numeric matrix containing the test samples spots intensity
          values, spots corresponding to rows and data tables (or
          chips) corresponding to columns.

     '_S_b': numeric matrix containing the test samples local background
          values, spots corresponding to rows and data tables (or
          chips) corresponding to columns.

     '_S_d_y_e': character vector with length equal the length of data
          files (chips), specifying the channel ('ch1' or 'ch2') used
          to label each test sample in each chip.

     '_R_f': numeric matrix containing the reference samples spots
          intensity values, spots corresponding to rows and data tables
          (or chips) corresponding to columns.

     '_R_f': numeric matrix containing the reference samples spots
          intensity values, spots corresponding to rows and data tables
          (or chips) corresponding to columns.

     '_R_d_y_e': character vector with length equal the length of data
          files (chips), specifying the channel ('ch1' or 'ch2') used
          to label each reference sample in each chip.

     '_F_l_a_g': matrix specifying the flags for the spots, as in the
          matrices above, rows and columns correspond to genes and
          samples, respectively. Type o value may be numeric or
          character, depending of the flags used.

     '_B_a_d_S_p_o_t_s': logical vector specifying spots that was judged as bad
          ones. By default this slot is created as a vector of FALSEs
          with same length as number of spots.

     '_U_s_e_S_p_o_t_s': logical matrix indexing the spots to be used for
          normalisation.

     '_G_e_n_e_G_r_p_s': a logical matrix with rows representing the spots and
          columns representing different gene groups. Each column give
          the index of spots in that gene group.

     '_P_a_t_h_s': list containing 'graphNEL' objects specifying gene
          regulatory networks (or pathways). The first object in this
          list is a char string giving the gene label used to match the
          genes.

     '_L_a_y_o_u_t': a list containing the number of rows ('gridR') and
          columns ('gridC') of grids, the number of rows ('spotR') and
          columns ('spotC') of spots inside each grid and the total
          number of spots.

     '_G_l_a_b_e_l_s': data frame giving the gene labels. These labels are
          generally used during the data analysis.

     '_S_l_a_b_e_l_s': data frame giving the sample labels. These labels are
          generally used during the data analysis.

     '_N_o_t_e_s': char string that receives any comment about the dataset.
          The dataset description is stored in this slot.

     '_D_a_t_e': char string giving the date and hour that the object was
          created.

     '_V._i_n_f_o': list containg three characters. The first one is a
          string containing the R version used when the object was
          created. The second is a char vector with base packages and
          the last one is another char vector with additional packages
          and version numbers.

_M_e_t_h_o_d_s:


     [ 'signature(x = 'maigesRaw')': subsetting operator for spots on
          the array or arrays in the batch, ensures that all slots are
          subset properly.

     _b_o_x_p_l_o_t 'signature(x = 'maigesRaw')': boxplot method for
          'maigesRaw' class. Display boxplots of the slides and print
          tip groups using package _marray_.

     _d_i_m 'signature(x = 'maigesRaw', value = 'numeric')': get the
          dimensions of the object, numeric vector of length two.

     _i_m_a_g_e 'signature(x = 'maigesRaw')': image method for 'maigesRaw'
          class. Display colour representation of the slides using
          package _marray_.

     _p_l_o_t 'signature(x = 'maigesRaw')': plot method for 'maigesRaw'
          class. Display _MA_ plots.

     _p_r_i_n_t 'signature(x = 'maigesRaw')': print method for 'maigesRaw'
          class.

     _s_h_o_w 'signature(x = 'maigesRaw')': show method for 'maigesRaw'
          class.

     _s_u_m_m_a_r_y 'signature(x = 'maigesRaw')': summary method for
          'maigesRaw' class.

_A_u_t_h_o_r(_s):

     Gustavo H. Esteves <gesteves@vision.ime.usp.br>

_S_e_e _A_l_s_o:

     'createMaigesRaw', 'selSpots', 'normLoc', 'normOLIN',
     'normRepLoess', 'normScaleLimma' and 'normScaleMarray'.

