QualityWeights             package:limma             R Documentation

_S_p_o_t _Q_u_a_l_i_t_y _W_e_i_g_h_t_s

_D_e_s_c_r_i_p_t_i_o_n:

     Functions to calculate quality weights for individual spots based
     on image analyis output file.

_U_s_a_g_e:

     wtarea(ideal=c(160,170))
     wtflags(w=0.1)
     wtIgnore.Filter

_A_r_g_u_m_e_n_t_s:

   ideal: numeric vector giving the ideal area or range of areas for a
          spot in pixels

       w: weight to be given to flagged spots

_D_e_t_a_i_l_s:

     These functions can be passed as an argument to 'read.maimages' to
     construct quality weights as the microarray data is read in.

     'wtarea' downweights unusually small or large spots and is
     designed for SPOT output. It gives weight 1 to spots which have
     areas in the ideal range, given in pixels, and linearly
     downweights spots which are smaller or larger than this range.

     'wtflags' is designed for GenePix output and gives weight
     'flagged.wt' to spots with 'Flags' value less than zero. 

     'wtIgnore.Filter' is designed for QuantArray output and sets the
     weights equal to the column 'Ignore Filter' produced by
     QuantArray. These weights are 0 for spots to be ignored and 1
     otherwise.

_V_a_l_u_e:

     A function which takes a dataframe or matrix as argument and
     produces a numeric vector of weights between 0 and 1

_A_u_t_h_o_r(_s):

     Gordon Smyth

_S_e_e _A_l_s_o:

     An overview of LIMMA functions for reading data is given in
     3.ReadingData.

_E_x_a_m_p_l_e_s:

     #  Read in spot output files from current directory and give full weight to 165
     #  pixel spots.  Note: for this example to run you must set fnames to the names
     #  of actual spot output files (data not provided).
     ## Not run: 
     RG <- read.maimages(fnames,source="spot",wt.fun=wtarea(165))
     #  Spot will be downweighted according to weights found in RG
     MA <- normalizeWithinArrays(RG,layout)
     ## End(Not run)

