normalize.quantiles.probeset     package:affyPLM     R Documentation

_Q_u_a_n_t_i_l_e _N_o_r_m_a_l_i_z_a_t_i_o_n _a_p_p_l_i_e_d _t_o _p_r_o_b_e_s_e_t_s

_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.AffyBatch.quantiles.probeset(abatch,type=c("separate","pmonly","mmonly","together"),use.median=FALSE,use.log=TRUE)

_A_r_g_u_m_e_n_t_s:

  abatch: An 'AffyBatch'

    type: how should MM and PM values be handled

use.median: use median rather than mean

 use.log: take logarithms, then normalize

_D_e_t_a_i_l_s:

     This function applies the quantile method in a probeset specific
     manner.

     In particular a probeset summary is normalized using the quantile
     method and then the probes adjusted accordingly.

_V_a_l_u_e:

     A normalized 'AffyBatch'.

_A_u_t_h_o_r(_s):

     Ben Bolstad, bmb@bmbolstad.com

_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 Unpublished manuscript 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', 'normalize.quantiles'