plotGenotypes: Plotting of genotyped markers
In beadarrayMSV: Analysis of Illumina BeadArray SNP data including MSV markers

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

Produces plots of “intensity” vs. “theta” with clusters coloured according to genotype call. Optional highlighting of specified samples or of pedigree-errors

plotGenotypes(BSRed, markers = 1:min(nrow(BSRed), 64),
    indHighlight = NULL, ploidy = "tetra", indicate.SE = FALSE,
    retFrames = FALSE, nC = NULL, mai = NULL, mNoise = NULL,
    main = NULL)

`BSRed`	`"AlleleSetIllumina"` object
`markers`	Index to markers to plot
`indHighlight`	Index to samples to highlight with yellow
`ploidy`	Character string reflecting the ploidy (copy-number) of the markers, defining the appearance of the clusters. Currently, only “tetra” is implemented
`indicate.SE`	If `TRUE`, size of points will reflect their precision (1/SE)
`retFrames`	If `TRUE`, a list of data-frames containing the coordinates for each marker is returned
`nC`	Number of columns of plots in the figure
`mai`	Size of margins. See `par`
`mNoise`	The “intensity”-limit below which no samples are called. If `NULL`, the mean `pData(BSRed)$noiseIntensity` (across arrays) is used
`main`	Vector of plot-titles. If `NULL`, the `featureNames` are used

All specified markers are plotted in subplots on a single device, and no more than 50-100 markers should be plotted at the time. The classified samples are coloured according to their allele-ratio, and non-called samples are represented as black dots. A red line indicates the estimated noise-level.

There are several ways samples may be highlighted. If indicate.SE is TRUE, the size of the dots reflects the precision of the intensity-estimates. Else, the samples indicated with indHighlight are represented as yellow dots. If neither of these are given, pedigree-errors will be highlighted if such information is found in BSRed. Both assayData entries “ped.check.parents” (see validateSingleCall) and “ped.check” (see validateCallsPedigree) are recognised. Yellow circles and crosses indicate parent and offspring errors, respectively.

The function plotGenotypes is called mainly for its side effects, however if retFrames is TRUE a list of data-frames containing the coordinates for each marker is returned

Lars Gidskehaug

validateCallsPedigree, callGenotypes

## Not run: 
#Read pre-processed data directly into AlleleSetIllumina object
rPath <- system.file("extdata", package="beadarrayMSV")
normOpts <- setNormOptions()
dataFiles <- makeFilenames('testdata',normOpts,rPath)
beadFile <- paste(rPath,'beadData_testdata.txt',sep='/')
beadInfo <- read.table(beadFile,sep='\t',header=TRUE,as.is=TRUE)
BSRed <- createAlleleSetFromFiles(dataFiles[1:4],beadInfo=beadInfo)

#Genotype calling and plotting
BSRed <- callGenotypes(BSRed)
plotGenotypes(BSRed,1:25)

#Pedigree validation and plotting
BSRed <- validateCallsPedigree(BSRed)
plotGenotypes(BSRed,1:25)

## End(Not run)