plotGenotypes: Plotting of genotyped markers

Description

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

Usage

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)

Arguments

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

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

Value

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

Details

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.

Examples

Run this code

#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)