normalizeAffine.MAData: Affine normalization based on non-logged data
In HenrikBengtsson/aroma: An R Object-oriented Microarray Analysis package

Description Usage Arguments Author(s) See Also Examples

Affine normalization based on non-logged data. For details, see normalizeAffine.RGData().

1 2	## S3 method for class 'MAData' normalizeAffine(this, ...)

...

Arguments passed to normalizeAffine.RGData().

Henrik Bengtsson (http://www.braju.com/R/).

For more information see MAData.

  # The option 'dataset' is used to annotate plots.
  options(dataset="sma:MouseArray")

  SMA$loadData("mouse.data")
  layout <- Layout$read("MouseArray.Layout.dat", path=system.file("data-ex", package="aroma"))
  raw <- RawData(mouse.data, layout=layout)
  ma <- getSignal(raw)

  # Clone the data to get one non-normalized and one normalized data set.
  maCurveFit <- clone(ma)
  maAffine <- clone(ma)

  # Normalize the data within slides using scaled print-tip normalization.
  normalizeCurveFit(maCurveFit, groupBy="printtip", method="lowess")
  normalizeAffine(maAffine, groupBy="printtip")

  # Plot data before and after normalization.
  subplots(9, nrow=3)
  for (obj in list(ma, maCurveFit, maAffine)) {
    # Plot M vs A and M spatially for array 1.
    plot(obj)
    plotSpatial(obj)
    # Plot the densities of A for *all* arrays.
    plotDensity(obj, what="A", xlim=c(4,16))
  }