specload1: Overlay PCA or OPLS loadings with spectra - experimental

In kimsche/MetaboMate: All you need for NMR-based metabolic profiling with R!

Description

Plotting overlayed NMR spectra. This function is based on ggplot2, a high-level plotting R package. For high ppm ranges computation time is relatively, so the range of input argument shift should be as small as possible. List argument an must have the first element define, even if it is only a single value. If colour and line width is specified, then at least one list elements of an must have the same length as X.

Usage

specload1(model, X, ppm, shift = c(0, 10), an, alp = 0.3, size = 0.5,
  pc = 1, type = c("Statistical reconstruction", "Backscaled"),
  title = "")

Arguments

model	PCA or OPLS model generated via MetaboMate package functions.
X	Input matrix with rows representing spectra
ppm	ppm variable
shift	ppm region to visualise.
an	List with one to three elements specifying facetting, colour and linetype (see Details).
alp	Alpha value for spectral lines.
size	plot line width.
pc	index of principal component to visualise, set to 1 if input model is OPLS
type	Type of loadings visualisation, either 'Statistical reconstruction' or 'Backscaled' (see Details).
title	Plot title.
...	Additional paramters passe on to ggplot's facet function.

Details

OPLS: If type='Statistical reconstruction' the function calculates the covariance (y axis) and Pearson's correlation (colouring) of the predictive OPLS scores with each X variable (x axis is ppm variable). If type='Backscaled' the OPLS loadings are backscaled with X feature standard deviations. Results are plotted over ppm, coloured according to OPLS model weights. Often, the latter method visualises model importance more robust due to the presence of false positive correlations. PCA: Function always calculates the statistical reconstruction.

Author(s)

Torben Kimhofer [e-mail]

See Also

plotload specOverlay OPLS_MetaboMate opls PCA_MetaboMate pca

kimsche/MetaboMate documentation built on Aug. 8, 2020, 1:14 a.m.