bg.adjust.gcrma            package:gcrma            R Documentation

_G_C_R_M_A _b_a_c_k_g_r_o_u_n_d _a_d_j_u_s_t (_i_n_t_e_r_n_a_l _f_u_n_c_t_i_o_n)

_D_e_s_c_r_i_p_t_i_o_n:

     This function performs background adjustment (optical noise and
     non-specific binding on an 'AffyBatch' project and returns an
     'AffyBatch' object in which the PM intensities are adjusted.

_U_s_a_g_e:

     bg.adjust.gcrma(object,affinity.info=NULL,
           affinity.source=c("reference","local"),
           NCprobe=NULL,
           type=c("fullmodel","affinities","mm","constant"),
           k=6*fast+0.5*(1-fast),stretch=1.15*fast+1*(1-fast),correction=1,
           GSB.adjust=TRUE,
           rho=.7,optical.correct=TRUE,verbose=TRUE,fast=TRUE)

_A_r_g_u_m_e_n_t_s:

  object: an 'AffyBatch'

affinity.info: 'NULL' or an 'AffyBatch' containing the affinities in
          the 'exprs' slot. This object can be created using the
          function 'compute.affinities'.

affinity.source: 'reference': use the package internal Non-specific
          binding data or 'local': use the experimental data in
          'object'. If 'local' is chosen, either MM probes or a
          user-defined list of probes (see 'NCprobes') are used to
          estimate affinities.

 NCprobe: 

    type: "fullmodel" for sequence and MM model. "affinities" for
          sequence information only. "mm" for using MM without sequence
          information.

       k: A tuning factor.

 stretch: 

correction: .

GSB.adjust: Logical value. If 'TRUE', probe effects in specific binding
          will be adjusted.

     rho: correlation coefficient of log background intensity in a pair
          of pm/mm probes. Default=.7

optical.correct: Logical value. If 'TRUE', optical background
          correction is performed.

 verbose: Logical value. If 'TRUE' messages about the progress of the
          function is printed.

    fast: Logical value. If 'TRUE' a faster ad hoc algorithm is used.

_D_e_t_a_i_l_s:

     The returned value is an 'AffyBatch' object, in which the PM probe
     intensities have been background adjusted. The rest is left the
     same as the starting 'AffyBatch' object.

     The tunning factor 'k' will have different meainngs if one uses
     the fast (ad hoc) algorithm or the empirical bayes approach. See
     Wu et al. (2003)

_V_a_l_u_e:

     An 'AffyBatch'.

_A_u_t_h_o_r(_s):

     Rafeal Irizarry

_E_x_a_m_p_l_e_s:

      if(require(affydata) & require(hgu95av2probe) & require(hgu95av2cdf)){
               data(Dilution)
               ai <- compute.affinities(cdfName(Dilution))
               Dil.adj<-bg.adjust.gcrma(Dilution,affinity.info=ai,type="affinities")
          }