4.Normalization            package:limma            R Documentation

_N_o_r_m_a_l_i_z_a_t_i_o_n _o_f _M_i_c_r_o_a_r_r_a_y _D_a_t_a

_D_e_s_c_r_i_p_t_i_o_n:

     This page gives an overview of the LIMMA functions available to
     normalize data from spotted two-colour microarrays. Smyth and
     Speed (2003) give an overview of the normalization techniques
     implemented in the functions.

     Usually data from spotted microarrays will be normalized using
     'normalizeWithinArrays'. A minority of data will also be
     normalized using 'normalizeBetweenArrays' if diagnostic plots
     suggest a difference in scale between the arrays.

     In rare circumstances, data might be normalized using
     'normalizeForPrintorder' before using 'normalizeWithinArrays'.

     If one is planning analysis of single-channel information from the
     microarrays rather than analysis of differential expression based
     on log-ratios, then the data should be normalized using a single
     channel-normalization technique. Single channel normalization uses
     further options of the 'normalizeBetweenArrays' function. For more
     details see the _LIMMA User's Guide_ which includes a section on
     single-channel normalization.

     'normalizeWithinArrays' uses utility functions 'loessFit' and
     'normalizeRobustSpline'. 'normalizeBetweenArrays' uses utility
     functions 'normalizeMedians', 'normalizeMedianDeviations' and
     'normalizeQuantiles', none of which need to be called directly by
     users.

_B_a_c_k_g_o_u_n_d _C_o_r_r_e_c_t_i_o_n:

     Usually one doesn't need to explicitly ask for background
     correction of the intensities because this is done by default by
     'normalizeWithinArrays', which subtract the background from the
     foreground intensities before applying the normalization method.
     This default background correction method can be over-ridden by
     using 'backgroundCorrect' which offers a number of alternative
     background correct methods to simple subtraction. Simply use
     'backgroundCorrect' to correct the 'RGList' before applying
     'normalizeWithinArrays'.

     'kooperberg' is a Bayesian background correction tool designed
     specifically for GenePix data. 'kooperberg' is not currently used
     as the default method for GenePix data because it is
     computationally intensive. It requires several columns of the
     Genepix data files which are not read in my read.maimages, so you
     will need to use 'read.series' instead of 'read.maimages' if you
     wish to use 'kooperberg'.

_A_u_t_h_o_r(_s):

     Gordon Smyth

_R_e_f_e_r_e_n_c_e_s:

     Smyth, G. K., and Speed, T. P. (2003). Normalization of cDNA
     microarray data. In: _METHODS: Selecting Candidate Genes from DNA
     Array Screens: Application to Neuroscience_, D. Carter (ed.). To
     appear. <URL: http://www.statsci.org/smyth/pubs/normalize.pdf>

