gridcheck              package:maanova              R Documentation

_P_l_o_t _g_r_i_d-_b_y-_g_r_i_d _d_a_t_a _c_o_m_p_a_r_i_s_o_n _f_o_r _a_r_r_a_y_s

_D_e_s_c_r_i_p_t_i_o_n:

     This function is used to check microarray data quality. It can
     check the data within the same array or cross different arrays.

     Normally, on one array, the intensity data for both channels (Cy5
     and Cy3) should be highly correlated (also apparent on the RI
     plot). The intensity data for the same sample on different arrays
     should be highly correlated too. Normally if an error happened in
     gridding, only a few blocks will be gridded. This function does
     the scatter plot on a grid basis to check the quality of
     hybridization and gridding. 

     If you only provide array1 (either an integer or a vector), it
     will do grid check within the same array, that is, for each slide,
     there will be one scatter plot for log2(Red) versus log2(Green)
     for each grid. If you provide array1 and array2 (both need to be
     one integer), it will check the data for the same sample (sample
     ID information is in experimental design) for these two arrays. If
     there's no common sample on these two arrays, the function will
     report an error. 

     In either case, you should see a nearly linear curve in all plots.
     If there were errors in hybridization and/or gridding, some of the
     plots will look messy. Then you have to check if something wrong
     happened, e.g., miss labeling, wrong gridding, etc.

     If you don't have grid information for the data, this function
     will be unavailable.

     Note that this function only works for 2-dye array.

_U_s_a_g_e:

     gridcheck(rawdata, array1, array2, highlight.flag = TRUE, flag.color = "Red",
               margin = c(3.1, 3.1, 3.1, 1.1)) 

_A_r_g_u_m_e_n_t_s:

 rawdata: An object of class 'madata'.

  array1: A list of array numbers for which you want to do grid
          checking. All arrays will be checked by default. If you want
          to compare the same sample across arrays, this parameter must
          be an integer to indicate the first array number.

  array2: The second array number if you want to do cross array
          comparisons.

highlight.flag: A logical parameter to indicate whether to highlight
          the bad spot or not.

flag.color: The color for bad spot; default is red.

  margin: A numerical vector of the form c(bottom, left, top, right)
          which gives the lines of the margin to be specified on the
          four sides of the plot. Read 'par' for details.

_N_o_t_e:

     This function will plot one figure for each array. So if you have
     many arrays, there will be many figures generated.

_A_u_t_h_o_r(_s):

     Hao Wu

_E_x_a_m_p_l_e_s:

     ## Not run: 
     # load in data
     data(kidney)
     # grid check on the first arrays
     gridcheck(kidney.raw, array1=1, margin=c(1,1,1,1))
     graphics.off()
     # grid check array 1 versus array 2
     gridcheck(kidney.raw, array1=1, array2=2)
     graphics.off()
     ## End(Not run)

