preprocess: Preprocess time/wavelength data

In chromatographR: Chromatographic Data Analysis Toolset

Preprocess time/wavelength data

Description

Standard pre-processing of response matrices, consisting of a time axis and a spectral axis (e.g. HPLC-DAD/UV data). For smooth data, like UV-VIS data, the size of the matrix can be reduced by interpolation. By default, the data are baseline-corrected in the time direction (baseline.corr) and smoothed in the spectral dimension using cubic smoothing splines (smooth.spline.

Usage

preprocess(
  X,
  dim1,
  dim2,
  remove.time.baseline = TRUE,
  spec.smooth = TRUE,
  maxI,
  parallel,
  interpolate_rows = TRUE,
  interpolate_cols = TRUE,
  mc.cores = 2,
  ...
)

Arguments

X	A numerical data matrix, or list of data matrices. Missing values are not allowed. If rownames or colnames attributes are used, they should be numerical and signify time points and wavelengths, respectively.
dim1	A new, usually shorter, set of time points (numerical). The range of these should not be outside the range of the original time points, otherwise the function stops with an error message.
dim2	A new, usually shorter, set of wavelengths (numerical). The range of these should not be outside the range of the original wavelengths, otherwise the function stops with an error message.
remove.time.baseline	Logical, indicating whether baseline correction should be done in the time direction, according to baseline.corr. Default is TRUE.
spec.smooth	Logical, indicating whether smoothing should be done in the spectral direction, according to smooth.spline. Default is TRUE.
maxI	if given, the maximum intensity in the matrix is set to this value.
parallel	Logical, indicating whether to use parallel processing. Defaults to TRUE (unless you're on Windows).
interpolate_rows	Logical. Whether to interpolate along dim1. Defaults to TRUE.
interpolate_cols	Logical. Whether to interpolate along dim2. Defaults to TRUE.
mc.cores	How many cores to use for parallel processing. Defaults to 2.
...	Further optional arguments to baseline.corr.

Value

The function returns the preprocessed data matrix, with row names and column names indicating the time points and wavelengths, respectively.

Note

Adapted from preprocess function in the alsace package by Ron Wehrens.

Author(s)

Ethan Bass

References

• Wehrens, R., Bloemberg, T.G., and Eilers P.H.C. 2015. Fast parametric time warping of peak lists. Bioinformatics 31:3063-3065. doi: 10.1093/bioinformatics/btv299.

• Wehrens, R., Carvalho, E., Fraser, P.D. 2015. Metabolite profiling in LC–DAD using multivariate curve resolution: the alsace package for R. Metabolomics 11:1:143-154. doi: 10.1007/s11306-014-0683-5.

Examples

data(Sa)
new.ts <- seq(10,18.66,by=.01) # choose time-points
new.lambdas <- seq(200, 318, by = 2) # choose wavelengths
Sa_pr <- preprocess(Sa[[1]], dim1 = new.ts, dim2 = new.lambdas)

chromatographR documentation built on Aug. 24, 2022, 9:06 a.m.