R: s-Plot of Spectra Data (Post PCA)

sPlotSpectra {ChemoSpec} | R Documentation

## s-Plot of Spectra Data (Post PCA)

### Description

Produces a scatter plot of the correlation of the variables against their covariance for a chosen principal component. It allows visual identification of variables driving the separation and thus is a useful adjunct to traditional loading plots.

### Usage

    sPlotSpectra(spectra, pca, pc = 1, tol = 0.05, ...)

### Arguments

`spectra` | An object of S3 class `Spectra`.
`pca` | The result of a pca calculation on `Spectra` (i.e. the output from `c_pcaSpectra` or `r_pcaSpectra`).
`pc` | An integer specifying the desired pc plot.
`tol` | A number describing the fraction of points to be labeled. `tol = 1.0` labels all the points; `tol = 0.05` labels the most extreme 5 percent.
`...` | Additional parameters to be passed to plotting functions.

### Value

A data frame containing the frequency, covariance and correlation of the selected pc for the `Spectra` object. A plot of the correlation vs. covariance is created.

### Author(s)

Matthew J. Keinsley and Bryan A. Hanson, DePauw University.

### References

Wiklund, Johansson, Sjostrom, Mellerowicz, Edlund, Shockcor, Gottfries, Moritz, and Trygg. "Visualization of GC/TOF-MS-Based Metabololomics Data for Identification of Biochemically Interesting Compounds Usings OPLS Class Models" Analytical Chemistry Vol.80 no.1 pgs. 115-122 (2008).

https://github.com/bryanhanson/ChemoSpec

### Examples

    data(SrE.IR)
    IR.pca <- c_pcaSpectra(SrE.IR)
    myt <- expression(bolditalic(Serenoa)~bolditalic(repens)~bold(IR~Spectra))
    splot <- sPlotSpectra(spectra = SrE.IR, pca = IR.pca, pc = 1, tol = 0.001,
      main = myt)

[Package ChemoSpec version 4.4.97 Index]