rmaPara               package:affyPara               R Documentation

_P_a_r_a_l_l_e_l_i_z_e_d _P_M_A _p_r_e_p_r_o_c_e_s_s_i_n_g

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

     Parallelized preprocessing function, which converts an AffyBatch
     into an  ExpressionSet using the robust multi-array average (RMA)
     expression measure.

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

     rmaPara(cluster,
             object,
             ids = NULL,
             phenoData = new("AnnotatedDataFrame"), cdfname = NULL,
             verbose=FALSE)

_A_r_g_u_m_e_n_t_s:

 cluster: A cluster object obtained from the function makeCluster in
          the 'SNOW' package. 

  object: An object of class AffyBatch OR a 'character' vector with the
          names of CEL files OR a (partitioned) list of 'character'
          vectors with CEL file names.

     ids: List of 'ids' for summarization 

phenoData: An AnnotatedDataFrame object. 

 cdfname: Used to specify the name of an alternative cdf package. If
          set to 'NULL', the usual cdf package based on Affymetrix'
          mappings will be used. 

 verbose: A logical value. If 'TRUE' it writes out some messages. 

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

     Parallelized preprocessing function, which goes from raw probe
     intensities to expression values using the robust multi-array
     average (RMA) expression measure: Background correction: rma;
     Normalization: quantile; Summarization: medianpolish

     For the serial function and more details see the function 'rma'.

     For using this function a computer cluster using the 'snow'
     package has to be started.

     This is a wrapper function for 'preproPara'.

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

     An object of class ExpressionSet.

_A_u_t_h_o_r(_s):

     Markus Schmidberger schmidb@ibe.med.uni-muenchen.de, Ulrich
     Mansmann mansmann@ibe.med.uni-muenchen.de

_E_x_a_m_p_l_e_s:

     ## Not run: 
     library(affyPara)

     data(affybatch.example)

     c1 <- makeCluster(3)

     esset <- rmaPara(cluster, affybatch.example)
         
     stopCluster(c1)
     ## End(Not run)

