boxplotPara             package:affyPara             R Documentation

_P_a_r_a_l_l_e_l_i_z_e_d _B_o_x _P_l_o_t_s _f_o_r _M_i_c_r_o_a_r_r_a_y _D_a_t_a

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

     Parallelized functions for Box Plots for Microarray Data. And
     optimized plots for a large number of microarrays.

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

     boxplotPara(object,
                     nSample=if(length(object)> 200) nSample<-200 else nSample <- length(object),
                     iqrMethod=TRUE, percent=0.05,
                     typDef="mean", plot=TRUE,        
                     plotAllBoxes=TRUE,
                     cluster, verbose = getOption("verbose")) 

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

 nSample: A numeric value. Indicates the number of maximal samples that
          should be plot at the same boxplot.  default: 250 

iqrMethod: A logical value, if TRUE the second method will be
          considered to calculate the  "bad" quality Samples otherwise
          the first Method. See Details. default: TRUE 

 percent: A numeric value [0.0-1.1]. If iqrMethod=TRUE the second
          method will be considered to  calculate the "bad" quality
          Samples otherwise the first Method. default: 0.05 

  typDef: A character value. Indicates how the default Sample should be
          calculated.  As median or mean from all Samples value. Only
          three possibilities: "media", "mean", c("median", "mean").
          default: "mean" 

    plot: A logical value. Indicates if graphics should be drawn.
          default: TRUE

plotAllBoxes: A logical value. If TRUE then all Samples will be ploted,
           if FALSE only bad arrays will be plotted. default: TRUE 

  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.

 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:

     'boxplotPara' is the parallelized function for box plots of probe
     intensities.  It is a function to check and control the Data
     quality of the samples using the boxplot methode.  For serial
     function an more details see boxplot. This function is optimized
     for huge numbers of microarray data.

     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.

     We need to calculate a default Sample as reference , which has
     been built from all Samples data.  Therefore the first is the
     calculation of the boxplot.stats, it will be made parallel at the
     cluster. The calculated values are merged at the master as well as
     the following calculations, plots and histograms There are two
     possibility to calculate the limits between the "good-bad" 
     quality Samples: 1. From the differences between defaultSample
     values (only media, HL nad HU will be considered) and all the
     samples.  At limit will be considered as critical and it help to
     calculate the "bad" quality Samples. (it is fixed as parameter and
     thus do it not so sure)  2. From the median and IQR obtained from
     a boxplot, which is calculated from all Samples values.  The
     outliers of these boxplot are the "bad" quality Samples. It should
     be as default parameter.

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

     boxplotPara returns a list with elements from the boxplot.stats
     function ('stats', 'n', 'conf', 'out', 'group', 'names') and 
     'QualityPS', 'values_boxP' and 'results_boxP'. 

qualityPS: is a list which contains all "bad" quality Arrays classified
          in levels.

values_boxP: contains the calculated differences and limits, which are
          used to make the classification of the Arrays in levels.

results_boxP: summary from 'qualityPS' as matrix, which contains only
          the Arrays that are considered as "bad" quality and in which
          levels are they classified. Possible values are 0 if the
          Array is not at this levels and 1 if it is classified as
          "bad" sample at this level

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

     Esmeralda Vicedo <e.vicedo@gmx.net>, 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)

       ##boxplot of Dulution data (affybatch) 
       box1 <- boxplotPara(Dilution)

       ## boxplots to a pdf file
       pdf(file="boxplot.pdf", title="AffyBatch Boxplot")
       box2 <- boxplotPara(Dilution)
       dev.off()

       stopCluster()
     }
     ## End(Not run)

