rmaplus               package:RefPlus               R Documentation

_D_e_r_i_v_e _R_M_A+ _i_n_t_e_n_s_i_t_i_e_s

_D_e_s_c_r_i_p_t_i_o_n:

     Calculate the RMA+ intensities using pre-stored reference
     quantiles and probe effects. The reference quantiles and the probe
     effects are the estimated  parameter values from RMAing a set of
     microarrays (e.g. a reference set).

_U_s_a_g_e:

     rmaplus(Future, rmapara, r.q, p.e, bg = TRUE)

_A_r_g_u_m_e_n_t_s:

  Future: An 'affybatch' object of the microarrays to be  pre-processed
          using the RMA+ methods.

 rmapara: Output of 'rma.para' function that the contain reference 
          quantiles and the reference probe effects.

     r.q: The pre-stored vector of the quantiles that the  probe
          intensity data of a microarray should be normalized to.

     p.e: A pre-stored list of probe effects. It is a probe.coefs
          object of  PLMset class in 'affyPLM' package.

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

_V_a_l_u_e:

     The RMA+ intensities of 'Future'.

_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:

     'PLMset-class','rma.para', 'rmaref.predict'

_E_x_a_m_p_l_e_s:

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

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

     ## Background correct, estimate the probe effects, and calculate the 
     ## RMA intensities using rma.para function.
     Para<-rma.para(affybatch.example,bg=TRUE,exp=TRUE)
     Ex1<-Para[[3]]
      
     ## Calculate the RMA+ intensity using rmaplus function. 
     Ex2<-rmaplus(affybatch.example, rmapara=Para, bg = TRUE)

