R/SnpCnvQSet.extractTheta.R

In aroma.affymetrix: Analysis of Large Affymetrix Microarray Data Sets

setMethodS3("extractTheta", "SnpCnvQSet", function(this, ..., transform=function(y, ...) { 2^y }, addNames=TRUE, verbose=FALSE) {
  eSet <- this

  # To please R CMD check
  ns <- loadNamespace("oligo")
  thetaA <- get("thetaA", mode="function", envir=ns)
  thetaB <- get("thetaB", mode="function", envir=ns)


  # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
  # Validate arguments
  # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
  # Argument 'verbose':
  verbose <- Arguments$getVerbose(verbose)
  if (verbose) {
    pushState(verbose)
    on.exit(popState(verbose))
  }


  nbrOfUnits <- nrow(eSet)
  nbrOfSamples <- ncol(eSet)
  nbrOfGroups <- 2L;  # (thetaA, thetaB)

  # Extract sample names
  sampleNames <- .sampleNames(eSet)
  sampleNames <- gsub("[.](cel|CEL)$", "", sampleNames)
  sampleNames <- gsub(",.*$", "", sampleNames)

  # Extract unit names
  snpNames <- .featureNames(eSet)

  # Allocate result object
  naValue <- NA_real_
  theta <- array(naValue, dim=c(nbrOfUnits, nbrOfGroups, nbrOfSamples))
  dimnames(theta)[[3L]] <- sampleNames
  if (addNames)
    dimnames(theta)[[1L]] <- snpNames

  # Populate with estimates
  theta[,1L,] <- transform(thetaA(eSet))
  theta[,2L,] <- transform(thetaB(eSet))

  theta
})