processArrayData {arrayMagic}R Documentation

processArrayData

Description

Usage




Arguments

subtractBackground logical
spotsRemovedBeforeNormalisation vector of character strings; all spots which match the strings are removed from the the whole analysis, i.e. already before normalisation
spotsSetToZeroWeightAndRemovedAfterNormalisation vector of character strings; all spots which match the strings become zero weight (weights are only used by loess type normalisations) and are removed after normalisation
spotIdentifier character string
mergeSlides logical; at this point only used for consistency tests of a hypothetical slide merge operation with respect to mergeSlidesColumn
slideDescriptionFile character string; the first line of the file must contain all column names, in particular the column fileNameColum and possibly slideNumberColumn must be included
fileNameColumn character string; required; default: "fileName"
slideNumberColumn character string; optional; if missing it is set to fileNameColumn; default: missing
mergeSlidesColumn character string; optional; cf. mergeSlides
sampleAnnotationColumns possible values: a vector of character strings or NA; sampleAnnotationColumns define all columns (hybridisation covariates) which are relevant for any further analysis. If mergeSlides is set to TRUE the annotation should be consistent for replicas. All columns in slideDescriptionFile are taken if set to NULL and all except of fileNameColumn and slideNumberColumn are taken if set to NA.
loadPath character string; the path is used to load the slideDescriptionFile and data files; note: . refers to the current/working directory
savePath character string; the path is used to save the results if the path does not exist a directory is created; note: . refers to the current/working directory
normalisationMethod character string; default: "vsn"; cf. normalise
imageFileType character string; default: "GenePix"; cf. readImageFiles
channelsSeparately logical; default FALSE
hybridisationGroups list of numeric vectors; default missing
objectsFileName character string; filename for saving of list of result objects
plotOutput character string specifying either "screen" or "pdf"; default: "screen"

Author(s)

Andreas Buness <a.buness@dkfz.de>

See Also

normalise spotSlideMerge

Examples

       LOADPATH <- file.path(.path.package("arrayMagic"), "data")
       SAVEPATH <- LOADPATH
        SLIDEDESCRIPTIONFILE <- "slideDescription.txt"
  
        resultList <- processArrayData(
                             loadPath=LOADPATH, 
                              savePath=SAVEPATH,
                             slideDescriptionFile=SLIDEDESCRIPTIONFILE,
                             sampleAnnotationColumns=NA
                  )
       writeToFile(exprSetArrayObject=resultList$exprSetArrayObject,
                   arrayDataObject=resultList$arrayDataObject,
                   fileName=file.path(SAVEPATH,"normalisedData.txt"))
       summarizedResult <- slideMerge(
                                           exprSetArrayObject=resultList$exprSetArrayObject,
                                           slideMergeVariable="replicates",
                                           sampleAnnotationColumns=
                                              resultList$sampleAnnotationColumns
                                          )

        qPL <- qualityParameters(arrayDataObject=resultList$arrayDataObject,
                         exprSetArrayObject=resultList$exprSetArrayObject)

        visualiseQualityParameters(qualityParametersList=qPL$qualityParameters)

        qualityDiagnostics(exprSetArrayObject=resultList$exprSetArrayObject,
                    arrayDataObject=resultList$arrayDataObject,
                    normObject=resultList$normObject,
                    qualityParametersList=qPL)

         resultListG <- processArrayData(
                             loadPath=LOADPATH, 
                              savePath=SAVEPATH,
                             slideDescriptionFile=SLIDEDESCRIPTIONFILE,
                             sampleAnnotationColumns=NA,
                             plotOutput="pdf",
                             hybridisationGroups = list((1:4),(5:9))
                  )
        
 

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