normalize.quantiles           package:affy           R Documentation

_Q_u_a_n_t_i_l_e _N_o_r_m_a_l_i_z_a_t_i_o_n

_D_e_s_c_r_i_p_t_i_o_n:

     Using a normalization based upon quantiles, this function
     normalizes a matrix of probe level intensities.

_U_s_a_g_e:

       normalize.quantiles(x,copy=TRUE)
       normalize.AffyBatch.quantiles(abatch, type=c("separate","pmonly","mmonly","together"))

_A_r_g_u_m_e_n_t_s:

       x: A matrix of intensities where each column corresponds to a
          chip and each row is a probe.

    copy: Make a copy of matrix before normalizing. Usually safer to
          work with a copy

  abatch: An 'AffyBatch'

    type: A string specifying how the normalization should be applied.
          See details for more.

_D_e_t_a_i_l_s:

     This method is based upon the concept of a quantile-quantile plot
     extended to n dimensions. No special allowances are made for
     outliers. If you make use of quantile normalization either through
     'rma' or 'expresso' please cite Bolstad et al, Bioinformatics
     (2003).

     The type arguement should be one of
     '"separate","pmonly","mmonly","together"' which indicates whether
     to normalize only one probe type (PM,MM) or both together or
     separately.

_V_a_l_u_e:

     A normalized 'AffyBatch'.

_A_u_t_h_o_r(_s):

     Ben Bolstad, bolstad@stat.berkeley.edu

_R_e_f_e_r_e_n_c_e_s:

     Bolstad, B (2001) _Probe Level Quantile Normalization of High
     Density Oligonucleotide Array Data_. Unpublished manuscript <URL:
     http://oz.berkeley.edu/~bolstad/stuff/qnorm.pdf>

     Bolstad, B. M., Irizarry R. A., Astrand, M, and Speed, T. P.
     (2003) _A Comparison of Normalization Methods for High Density
     Oligonucleotide Array Data Based on Bias and Variance._
     Bioinformatics 19(2) ,pp 185-193. <URL:
     http://www.stat.berkeley.edu/~bolstad/normalize/normalize.html>

_S_e_e _A_l_s_o:

     'normalize'

