Skip to contents

Preprocess time/wavelength data

Source: R/preprocess.R
preprocess.Rd

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 = NULL,
  interpolate_rows = TRUE,
  interpolate_cols = TRUE,
  cl = 2,
  show_progress = NULL,
  ...
)

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 exceed the range of the original time points.

dim2

A new, usually shorter, set of wavelengths (numerical). The range of these should not exceed the range of the original wavelengths.

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.

interpolate_rows

Logical. Whether to interpolate along the time axis (dim1). Defaults to TRUE.

interpolate_cols

Logical. Whether to interpolate along the spectral axis (dim2). Defaults to TRUE.

cl

Argument to pblapply or mclapply. Either an integer specifying the number of clusters to use for parallel processing or a cluster object created by makeCluster. Defaults to 2. On Windows integer values will be ignored.

show_progress

Logical. Whether to show progress bar. Defaults to TRUE if pbapply is installed.

...

Further optional arguments to baseline.corr.

Value

The function returns the preprocessed data matrix (or list of matrices), with row names and column names indicating the time points and wavelengths, respectively.

Note

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

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 .

Author

Ethan Bass

Examples

if (FALSE) { # interactive()
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)
}