rma.para               package:RefPlus               R Documentation

_F_i_t_t_i_n_g _a _R_M_A _m_o_d_e_l

_D_e_s_c_r_i_p_t_i_o_n:

     Obtain reference quantiles and reference probe effects based on
     reference set  Train, and calculate the gene expression

_U_s_a_g_e:

     rma.para(Train, bg = TRUE, exp = FALSE)

_A_r_g_u_m_e_n_t_s:

   Train: An 'AffyBatch' object of the reference set microarrays.

      bg: A logical flag. If 'True'(by default), background correct 
          'Train' using default 'bg.correct.rma'. 

     exp: A logical flag. If 'True', calculate the RMA measurements of
          'Train'. If 'False', return 0.

_V_a_l_u_e:

Reference.Quantiles: Reference quantiles derived from 'Train'.

probe.effects: Estimated probe effects derived from 'Train'.

expression: RMA measurements of 'Train'.

_N_o_t_e:

     The RMA procedure requires a lot of computer memory.

_A_u_t_h_o_r(_s):

     Kai-Ming Chang(Kai-Ming.Chang@astrazeneca.com, kaiming@gmail.com)

_R_e_f_e_r_e_n_c_e_s:

     Chang,K.M., Harbron,C., South,M.C. (2006) An Exploration of 
     Extensions to the RMA Algorithm. (Submitted)

_S_e_e _A_l_s_o:

     'rmaplus','rmaref.predict'

_E_x_a_m_p_l_e_s:

     ## Use affybatch.example in Affy package
     data(affybatch.example)

     ## Background correct, estimate the probe effects, and calculate the 
     ## RMA intensities using rma.para function.
     Ex<-rma.para(affybatch.example,bg=TRUE,exp=TRUE)

     ## Calculate the rma intensities using rma function.
     Ex0<-exprs(rma(affybatch.example))

     plot(Ex$express[,1],Ex0[,1])

