GenomicReports {beadarraySNP}R Documentation

Genomic reports

Description

Create reports for all samples in a dataset.

Usage

reportChromosomesSmoothCopyNumber(snpdata, grouping, normalizedTo=2, 
  smooth.lambda=2, ridge.kappa=0, plotLOH=c("none", "marker", "line", "NorTum"), 
  sample.colors = NULL, ideo.bleach=0.25, ...)
reportSamplesSmoothCopyNumber(snpdata, grouping, normalizedTo=2, 
  smooth.lambda=2, ridge.kappa=0, plotLOH=c("none", "marker", "line", "NorTum"), 
  sample.colors=NULL, ...)
reportGenomeGainLossLOH(snpdata, grouping, plotSampleNames=FALSE, sizeSampleNames=4, 
  distance.min, upcolor="red", downcolor="blue", lohcolor="grey", hetcolor="lightgrey", 
  lohwidth=1, segment=101, orientation=c("V","H"), ...)
reportChromosomeGainLossLOH(snpdata, grouping, plotSampleNames=FALSE, distance.min,
  upcolor="red", downcolor="blue", lohcolor="grey", hetcolor="lightgrey", proportion=0.2, 
  plotLOH=TRUE, segment=101, ...)
reportGenomeIntensityPlot(snpdata, normalizedTo=NULL, subsample=NULL, smoothing=c("mean", "quant"),
  dot.col="black", smooth.col="red", ...)

Arguments

snpdata SnpSetIllumina object.
grouping factor, elements with same value are plotted together. Defaults to groups of 4 in order of the samples in the object.
normalizedTo numeric, a horizontal line is drawn at this position.
smooth.lambda smoothing parameter for quantsmooth.
ridge.kappa smoothing parameter for quantsmooth.
plotLOH indicate regions or probes with LOH, see details.
sample.colors vector of color.
plotSampleNames logical.
sizeSampleNames numeric, margin size for sample names.
distance.min numerical.
upcolor color.
downcolor color.
lohcolor color.
hetcolor color.
lohwidth
segment integer.
orientation ["V","H"], vertical or horizontal orientation of plot.
proportion
subsample
smoothing Type of smoothing per chromosome.
dot.col color.
smooth.col color.
ideo.bleach numeric [0,1]
... arguments are forwarded to plot or getChangedRegions.

Details

The first function creates plots for each group and each chromosome in the dataset. The second function creates full genome plot for each group in the dataset. Beware that a lot of plots can be created, and usually you should prepare for that, by redirecting the plots to pdf or functions that create picture files like jpg, png, bmp.

Value

These functions are executed for their side effects

Author(s)

Jan Oosting

See Also

quantsmooth,prepareGenomeplot, pdfChromosomesSmoothCopyNumber, pdfSamplesSmoothCopyNumber

Examples

data(chr17.260)
chr17nrm <- standardNormalization(chr17.260)
par(mfrow = c(4,2), mar = c(2,4,2,1))
reportChromosomesSmoothCopyNumber(chr17nrm, grouping=pData(chr17.260)$Group,smooth.lambda = 4)

[Package beadarraySNP version 1.6.0 Index]