maiges-class           package:maigesPack           R Documentation

_m_a_i_g_e_s _c_l_a_s_s, _s_t_o_r_e _n_o_r_m_a_l_i_s_e_d _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 ratio of intensities (_W_)
     and average of intensities (_A_) values values and information
     about genes and samples used in the data. Objects of this class
     are created from class 'maigesRaw' using the functions 'normLoc',
     'normOLIN', 'normRepLoess', 'normScaleLimma' and/or
     'normScaleMarray' to do the normalisation.

     Here, the _M=log(R/G)_ value of intensity ratio was redefined as
     _W=log(Test/Ref)_, where _Test_ and _Ref_ are the test and
     reference samples.

_D_e_t_a_i_l_s:

     This defines the main class of objects defined in this package. It
     is created from 'maigesRaw' class using the normalisation
     functions 'normLoc', 'normOLIN', 'normRepLoess', 'normScaleLimma'
     and 'normScaleMarray'. From this class of objects it is possible
     to do any type of analysis defined by several functions in this
     package. Also, it is possible to summarise spots (or samples)
     information using the function 'summarizeReplicates'.

_S_l_o_t_s:


     '_W': numeric matrix containing the ratio values (in log2 scale)
          between the test and reference sample intensities (W values).
          Spots are indexed by rows and samples by columns.

     '_A': numeric matrix containing the mean intensity values between
          test and reference samples (also in log2 scale).  Spots
          corresponding to rows and samples (or chips) corresponding to
          columns, too.

     '_S_D': numeric matrix containing the standard deviation of W values
          when the lowess step is repeated several times.

     '_I_C_1': numeric matrix containing the left margin of confidence
          interval defined by repeated lowess during the normalisation
          step.

     '_I_C_2': numeric matrix containing the right margin of confidence
          interval defined above.

     '_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 = 'maiges')': 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 = 'maiges')': boxplot method for 'maiges'
          class. Display boxplots of the slides and print tip groups
          using package _marray_ or boxplots of one gene previously
          defined.

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

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

     _p_l_o_t 'signature(x = 'maiges')': plot method for 'maiges' class.
          Display 'MA' plots.

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

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

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

_A_u_t_h_o_r(_s):

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

_S_e_e _A_l_s_o:

     'normLoc', 'normOLIN', 'normRepLoess', 'normScaleLimma',
     'normScaleMarray' and 'summarizeReplicates'.

