plotSNPs {crlmm} | R Documentation

## Make M vs S plot for SNPs or samples.

### Description

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.

### Usage

    	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")

### Arguments

`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')

### Details

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

### Value

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`.

### Author(s)

Matt Ritchie and Cynthia Liu

### See Also

`genotype.Illumina`

### Examples

    ## 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)

[Package crlmm version 1.40.0 Index]