getNoiseDistributions: Estimate median and robust spread of background noise
In beadarrayMSV: Analysis of Illumina BeadArray SNP data including MSV markers

Description Usage Arguments Details Value Warning Note Author(s) See Also Examples

The genotypes of [A/T] and [C/G] markers are measured with Infinium I beads using an arbitrary (red or green) channel, and the alternate channel measures noise only. The median and median absolute deviation (mad) of each noise channel is estimated and returned for each array

getNoiseDistributions(BSData, subBeadPool = NULL, normInd,
    normOpts = setNormOptions(), plot = FALSE, newFigure = plot,
    maxPlots = 72, xlim = NULL, ...)

plotEstimatedNoise(BSData, noiseDist,
    normInd = rep(TRUE, nrow(BSData)), normOpts = setNormOptions(),
    newFigure = TRUE, maxPlots = 72, ...)

`BSData`	`"BeadSetIllumina"` object, previously subjected to rotation and shearing but not to log- or nth-root transformation.
`subBeadPool`	Vector of one or more 1-digit integers (of class character or numeric) denoting sub-bead pool(s) to base estimations upon. For `subBeadPool = "x"`, the red channel noise is estimated based on markers with `featureData` column `Norm.ID = "20x"` and the green channel noise is based on markers with `Norm.ID = "10x"`. For these channels and markers, only noise is detected. If more than one integer is given, the full set of Infinium I markers corresponding to the specified sub-bead pools is used. If `NULL`, all Infinium I markers are used (default).
`normInd`	Matrix with logical indexes to sub-bead pool for each bead-type. See `getNormInd`
`normOpts`	List specifying pre-processing settings. See `setNormOptions`
`plot`	If `TRUE`, a the estimated and parametrized noise for each channel is plotted
`newFigure`	Logical indicating whether or not to clear the current device before plotting. If `FALSE`, an error will be produced if more than one array is specified
`maxPlots`	Numeric indicating the maximum allowed number of arrays to plot. Exceeding this limit will produce an error.
`xlim`	Range of x-axis
`...`	Additional arguments to `plot`
`noiseDist`	Matrix output from `getNoiseDistribution`

Usually called by preprocessBeadSet.

There are three main groups of markers, as identified by the featureData column “Norm.ID” of BSData. Those identified by a single digit “x” are Infinium II beads, and those identified by three digits “10x” and “20x” are Infinium I beads. The difference between the latter is that “10x” beads are measured using the red channel only, whereas “20x” beads are measured with the green channel only. The background noise can thus be estimated based on the alternate channel.

getNoiseDistribution returns a matrix (noiseDist) holding the median and mad for both channels, all arrays

plotEstimatedNoise is used for its side effects

Both these functions take non-transformed BSData as input, however transformations are performed inside the functions as specified in normOpts. It follows that noiseDist holds the median and mad of transformed data. Use plotEstimatedNoise with caution, as one input parameter is transformed and another is not. The function plotPreprocessing may be a good alternative

Sub-bead pools with different 1-digit identifiers “x” are pooled together whenever more than a single sub-bead pool is given

Lars Gidskehaug

preprocessBeadSet, plotPreprocessing

## Not run: 
#Read files into BeadSetIllumina-object
rPath <- system.file("extdata", package="beadarrayMSV")
BSDataRaw <- readBeadSummaryOutput(path=rPath,recursive=TRUE)

#Find indexes to sub-bead pools
beadInfo <- read.table(paste(rPath,'beadData.txt',sep='/'),sep='\t',
    header=TRUE,as.is=TRUE)
rownames(beadInfo) <- make.names(beadInfo$Name)
normInd <- getNormInd(beadInfo,featureNames(BSDataRaw))

#Pre-process
normOpts <- setNormOptions(minSize=50,breaks=200)
BSData <- shearRawSignal(BSDataRaw, normOpts = normOpts,plot=TRUE)
noiseDist <- getNoiseDistributions(BSData[,1:4], normInd = normInd,
    normOpts = normOpts, plot = TRUE)
print(noiseDist)
plotEstimatedNoise(BSData,noiseDist,normOpts=normOpts)

## End(Not run)