R: Plot CGH data

PlotCGH {PMA} | R Documentation

## Plot CGH data

### Description

Given a vector of gains/losses at CGH spots, this makes a plot of gain/loss on each chromosome.

### Usage

    PlotCGH(array, chrom = NULL, nuc = NULL, main = "", scaleEachChrom = TRUE)

### Arguments

`array` | A vector containing the chromosomal location of each CGH spot.
`chrom` | A numeric vector of the same length as "array"; its values should indicate the chromosome that each CGH spot is on (for instance, for human genomic data, values of chrom should range from 1 to 24). If NULL, then it is assumed that all elements of 'array' are on the same chromosome.
`nuc` | A numeric vector of same length as "array", indicating the nucleotide position of each CGH spot. If NULL, then the function assumes that each CGH spot corresponds to a consecutive position. E.g. if there are 200 CGH spots on chromosome 1, then they are located at positions 1,2,...,199,200.
`main` | Give your plot a title.
`scaleEachChrom` | Default is TRUE. This means that each chromosomes CGH spots are divided by 1.1 times the max of the CGH spots on that chromosome. This way, the CGH spots on each chromosome of the plot are as big as possible (i.e. easy to see). If FALSE, then all of the CGH spots are divided by 1.1 times the max of ALL the CGH spots. This means that on some chromosomes CGH spots might be hard to see, but has the advantage that now relative magnitudes of CGH spots on different chromosomes can be seen from figure.

### Details

This function makes a plot of regions of genomic gain/loss.

### References

Witten D. M., Tibshirani R., and Hastie, T. (2009) A penalized matrix decomposition, with applications to sparse principal components and canonical correlation analysis, Biostatistics, Gol 10 (3), 515-534, Jul 2009

### See Also

PMD, PMD.cv, CCA, CCA.permute

### Examples

    ## Not run:
    # Use breast data
    data(breastdata)
    attach(breastdata)

    # dna contains CGH data and chrom contains chromosome of each CGH spot;
    # nuc contains position of each CGH spot.
    dna <- t(dna)
    PlotCGH(dna[1,],chrom=chrom,nuc=nuc,main="Sample 1: All Chromosomes")
    PlotCGH(dna[1,chrom==1], chrom=chrom[chrom==1], nuc=nuc[chrom==1],
    main= "Sample 1: Chrom 1")
    PlotCGH(dna[1,chrom<=3], chrom=chrom[chrom<=3], nuc=nuc[chrom<=3],
     main="Sample 1: Chroms 1, 2, and 3")
    detach(breastdata)

    ## End(Not run)

[Package PMA version 1.2.1 Index]