normalizeAffyBatchLoessPara     package:affyPara     R Documentation

_P_a_r_a_l_l_e_l_i_z_e_d _l_o_e_s_s _n_o_r_m_a_l_i_z_a_t_i_o_n

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

     Parallelized loess normalization of arrays.

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

     normalizeAffyBatchLoessPara(object,
             phenoData = new("AnnotatedDataFrame"), cdfname = NULL,
             type=c("separate","pmonly","mmonly","together"), 
             subset = NULL,
             epsilon = 10^-2, maxit = 1, log.it = TRUE, 
             span = 2/3, family.loess ="symmetric",
             cluster, verbose = getOption("verbose")) 

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

  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.

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. 

    type: A string specifying how the normalization should be applied.

  subset: a subset of the data to fit a loess to.

 epsilon: a tolerance value (supposed to be a small value - used as a
          stopping criterium).

   maxit: maximum number of iterations.

  log.it: logical. If 'TRUE' it takes the log2 of mat

    span: parameter to be passed the function loess

family.loess: parameter to be passed the function loess. "gaussian" or
          "symmetric" are acceptable values for this parameter.

 cluster: A cluster object obtained from the function makeCluster in
          the SNOW package.  For default '.affyParaInternalEnv$cl' 
          will be used. 

 verbose: A logical value. If 'TRUE' it writes out some messages.
          default: getOption("verbose") 

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

     Parallelized loess normalization of arrays.

     For the serial function and more details see the function
     'normalize.AffyBatch.loess'.

     For using this function a computer cluster using the SNOW package
     has to be started.  Starting the cluster with the command
     'makeCluster' generates an cluster object in the affyPara
     environment (.affyParaInternalEnv) and  no cluster object in the
     global environment. The cluster object in the affyPara environment
     will be used as default cluster object,  therefore no more cluster
     object handling is required.   The 'makeXXXcluster' functions from
     the package SNOW can be used to create an cluster object in the
     global environment and  to use it for the preprocessing functions.

     In the loess normalization the arrays will compared by pairs.
     Therefore at every node minimum two arrays have to be!

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

     An AffyBatch of normalized objects.

_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)
     if (require(affydata)) {
       data(Dilution)

       makeCluster(3)

       AffyBatch <- normalizeAffyBatchLoessPara(Dilution, verbose=TRUE)

       stopCluster()
     }
     ## End(Not run)

