gcrma                 package:gcrma                 R Documentation

_R_o_b_u_s_t _M_u_l_t_i-_A_r_r_a_y _e_x_p_r_e_s_s_i_o_n _m_e_a_s_u_r_e _u_s_i_n_g _s_e_q_u_e_n_c_e _i_n_f_o_r_m_a_t_i_o_n

_D_e_s_c_r_i_p_t_i_o_n:

     This function converts an 'AffyBatch' into an 'exprSet' using the
     robust multi-array average (RMA) expression measure with help of
     probe sequence.

_U_s_a_g_e:

     gcrma(object,affinity.info=NULL,
                       type=c("fullmodel","affinities","mm","constant"),
                       k=6*fast+0.5*(1-fast),stretch=1.15*fast+1*(1-fast),correction=1,
                       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'.

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

       k: A tuning factor.

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

 stretch: 

correction: .

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: Logicalvalue. If 'TRUE' a faster add-hoc algorithm is used.

_D_e_t_a_i_l_s:

     Note that this expression measure is given to you in log base 2
     scale. This differs from most of the other expression measure
     methods.

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

_V_a_l_u_e:

     An 'exprSet'.

_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.expr<-gcrma(Dilution,affinity.info=ai,type="affinities")
     }

