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beadarraySNP (version 1.38.0)

GenomicReports: 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
numerical, relative width of the LOH part of the sample
segment
integer.
orientation
["V","H"], vertical or horizontal orientation of plot.
proportion
numerical, proportion of the plot to use for idiogram annotation
subsample
character, or factor of length of features
smoothing
Type of smoothing per chromosome.
dot.col
color.
smooth.col
color.
ideo.bleach
numeric [0,1]
...
arguments are forwarded to plot or getChangedRegions.

Value

These functions are executed for their side effects

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.

See Also

quantsmooth,prepareGenomePlot, pdfChromosomesSmoothCopyNumber, pdfSamplesSmoothCopyNumber

Examples

Run this code
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)

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