R/doClusterAnalysis.R

In uebvhir/BasicP4microArrays: Functions to create and run simple-to-complex microarray analysis pipeline

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loadFromFile <- function (fileName, pos = 1) {
  tempEnv <- new("environment")
  load(fileName, tempEnv)
  varNames <- ls(tempEnv)
  myVarName <- varNames[pos]
  load(fileName)
  myVar <- eval(parse(text = myVarName))
  return(myVar)
}
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#'doClusterAnalysis
#'
#'Function to perform cluster analysis
#'@param clustPar List object that contains the parameters needed to carry out the analysis.
#'@examples
#'\dontrun{
#' clustParsList <- list()
#' for(i in 1:length(compName))
#' {
#'   pvalType <- ifelse(adjMethod[i] == "none", "pvalues", "adj-pvalues")
#'   clustPar <- list(expres = NULL,
#'                    expresFileName = "exprs.filtered.Rda",
#'                    geneListFName = paste("geneList",  compName[i],
#'                                          pvalType, "LT", pValCutOff[i], "Rda", sep = "."),
#'                    genes2cluster = NULL,
#'                    samples2cluster = s2clust,
#'                    sampleNames = as.character(targets$ShortName)[s2clust],
#'                    comparisonName = compName[i],
#'                    anotPackage = "org.Hs.eg",
#'                    my.symbols = symbolsTable,
#'                    outputDir = outputDir,
#'                    fileOfLinks = linksFile,
#'                    numClusters = 2,
#'                    rowDistance = NULL,
#'                    colDistance = NULL,
#'                    RowVals = TRUE,
#'                    ColVals = FALSE,
#'                    escala = "row",
#'                    colorsSet = pal,
#'                    densityInfo = "density",
#'                    colsForGroups = c(rep("pink", 5), rep("blue", 5)),
#'                    cexForColumns = 0.8,
#'                    cexForRows = 0.8,
#'                    Title = paste(compName[i],
#'                                  "with", pvalType,
#'                                  "<", pValCutOff[i],
#'                                  ifelse(minLogFoldChange[i]==0, "",
#'                                         paste0("\n and |logFC|>=", minLogFoldChange[i]))),
#'                    paste("Comparison:", compName[i]),
#'                    csvType = csvType)
#'
#'   clustParsList <- add2parsList(clustParsList, clustPar)
#' }
#'
#' for(ix in 1:length(clustParsList))
#' {
#'  hm.Estudi <- BasicP::doClusterAnalysis(clustParsList[ix])
#' }
#' }
#'@export

doClusterAnalysis <- function(clustPar) {
  p <- clustPar[[1]]

  if(!is.null(p$expresFileName)) {
    expres <- loadFromFile(file.path(p$outputDir, p$expresFileName))
  } else {
    if(!is.null(p$dades)) {
      expres <- eval(parse(text = p$dades)) # Posar-hi un tryCatch per poder sortir si d??na error!!!
    } else {
      stop("Error, Cal definir o les dades o el nom de l'arxiu")
    }
  }

  if(!is.null(p$geneListFName)) {
    genes2cluster <- loadFromFile(file.path(p$outputDir, p$geneListFName))
  } else {
    if(is.null(p$genes2cluster)) {
      stop("Error, Cal definir l'arxiu que conte la llista de gens o passar una variable que la contingui")
    } else {
      genes2cluster <- p$genes2cluster
    }
  }

  clust <- clusterAnalysis(expres = expres,
                           genes = genes2cluster,
                           samples = p$samples2cluster,
                           sampleNames = p$sampleNames,
                           comparisonName = p$comparisonName,
                           anotPackage = p$anotPackage,
                           my.symbols = p$my.symbols,
                           outputDir = p$outputDir,
                           fileOfLinks = p$fileOfLinks,
                           numClusters = p$numClusters,
                           rowDistance = p$rowDistance,
                           colDistance = p$colDistance,
                           RowVals = p$RowVals,
                           ColVals = p$ColVals,
                           escala = p$escala,
                           colorsSet = p$colorsSet,
                           densityInfo = p$densityInfo,
                           colsForGroups = p$colsForGroups,
                           cexForColumns = p$cexForColumns,
                           cexForRows = p$cexForRows,
                           Title = p$Title,
                           csvType = p$csvType)

  return(clust)
}