plotSNPs: Make M vs S plot for SNPs or samples.
In benilton/crlmm: Genotype Calling (CRLMM) and Copy Number Analysis tool for Affymetrix SNP 5.0 and 6.0 and Illumina arrays

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

These functions plot the M-values (log-ratios) versus S-values (average intensities) for given SNP/(s) or sample/(s) or beanplots for M-values from different samples.

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	plotSNPs(cnSet, row=1, offset=0, xlim=c(9,16), ylim=c(-5,5), verbose=FALSE)
	plotSamples(cnSet, col=1, offset=0, xlim=c(9,16), ylim=c(-5,5), verbose=FALSE, sample=100000, seed=1, type="smoothScatter")

`cnSet`	An object of class `CNSet`
`row`	scalar/vector of SNP indexes to plot
`col`	scalar/vector of sample indexes to plot
`offset`	numeric, offset to add to intensities in `cnSet` before log2-transforming to make log-ratios or average log-intensities
`xlim`	the x limits of the plot
`ylim`	the y limits of the plot
`verbose`	'logical.' Whether to print descriptive messages during processing
`sample`	integer indicating the number of SNPs to sample for the plot
`seed`	integer seed for the random number generator to sample the SNPs
`type`	character vector specifying the type of sample plot (either 'smoothScatter' or 'beanplot')

The plotSNPs and plotSamples functions plot the M and S values derived from the cnSet object.

One or more M vs S plot for plotSNPs for a given SNP(/s) or either a smoothed scatter plot of M vs S or a beanplot of the M-values for a selected sample(/s) for plotSamples.

Matt Ritchie and Cynthia Liu

genotype.Illumina

## Not run: 
   crlmmResult <- genotype.Illumina(sampleSheet=samples[1:10,], path=path,
                                        arrayInfoColNames=list(barcode=NULL,
                                        position="SentrixPosition"),
                                        saveDate=TRUE, cdfName="human370v1c")
   par(mfrow=c(2,2))
   plotSamples(crlmmResult, col=1:4)
   plotSNPs(crlmmResult, row=1:4)

## End(Not run)