sPlotSpectra | R Documentation |
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.
sPlotSpectra(spectra, pca, pc = 1, tol = 0.05, ...)
spectra |
An object of S3 class |
pca |
The result of a pca calculation on |
pc |
An integer specifying the desired pc plot. |
tol |
A number describing the fraction of points to be labeled. |
... |
Parameters to be passed to the plotting routines. Applies to base graphics only. |
The returned value depends on the graphics option selected (see ChemoSpecUtils::GraphicsOptions()
).
base
: None. Side effect is a plot.
ggplot2
: The plot is displayed, and a ggplot2
object is returned if the value is assigned. The plot can be modified in the usual ggplot2
manner.
Bryan A. Hanson (DePauw University), Tejasvi Gupta, Matthew J. Keinsley.
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).
Additional documentation at https://bryanhanson.github.io/ChemoSpec/
# This example assumes the graphics output is set to ggplot2 (see ?GraphicsOptions).
library("ggplot2")
data(SrE.IR)
pca <- c_pcaSpectra(SrE.IR)
myt <- expression(bolditalic(Serenoa) ~ bolditalic(repens) ~ bold(IR ~ Spectra))
p <- sPlotSpectra(spectra = SrE.IR, pca = pca, pc = 1, tol = 0.001)
p <- p + ggtitle(myt)
p
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