PreprocessingChain: Proprocessing workflow for 1H-NMR data
In yclement/PepsNMR: Pre-process 1H-NMR FID signals

Description Usage Arguments Value Author(s) References Examples

The function is a wrapper for all the preprocessing steps available in PepsNMR.

PreprocessingChain(Fid_data = NULL, Fid_info = NULL, data.path = NULL, readFids = TRUE, 
    groupDelayCorr = TRUE, solventSuppression = TRUE, apodization = TRUE, 
    zerofilling = TRUE,fourierTransform = TRUE, zeroOrderPhaseCorr = TRUE, 
    internalReferencing = TRUE, baselineCorrection = TRUE, negativeValues0 = TRUE, 
    warping = TRUE, windowSelection = TRUE, bucketing = TRUE, regionRemoval = TRUE, 
    zoneAggregation = TRUE,normalization = TRUE, ...,  export = FALSE, 
    format = c("Rdata", "csv", "txt"), out.path = ".",  filename = "filename", 
    writeArg = c("none", "return", "txt"), verbose = FALSE)

`Fid_data`	If non `NULL`, matrix containing the complex FIDs, one row per FID.
`Fid_info`	If non `NULL`, matrix containing the information for each spectrum, one row per spectrum, as returned by `ReadFids`.
`data.path`	A character string specifying the directory where the FIDs are searched.
`readFids`	If `TRUE`, applies the `ReadFids` function to the data.
`groupDelayCorr`	If `TRUE`, applies the `GroupDelayCorrection` function to the data.
`solventSuppression`	If `TRUE`, applies the `SolventSuppression` function to the data.
`apodization`	If `TRUE`, applies the `Apodization` function to the data.
`zerofilling`	If `TRUE`, applies the `ZeroFilling` function to the data.
`fourierTransform`	If `TRUE`, applies the `FourierTransform` function to the data.
`zeroOrderPhaseCorr`	If `TRUE`, applies the `ZeroOrderPhaseCorrection` function to the data.
`internalReferencing`	If `TRUE`, applies the `InternalReferencing` function to the data.
`baselineCorrection`	If `TRUE`, applies the `BaselineCorrection` function to the data.
`negativeValues0`	If `TRUE`, applies the `NegativeValuesZeroing` function to the data.
`warping`	If `TRUE`, applies the `Warping` function to the data.
`windowSelection`	If `TRUE`, applies the `WindowSelection` function to the data.
`bucketing`	If `TRUE`, applies the `Bucketing` function to the data.
`regionRemoval`	If `TRUE`, applies the `RegionRemoval` function to the data.
`zoneAggregation`	If `TRUE`, applies the `ZoneAggregation` function to the data.
`normalization`	If `TRUE`, applies the `Normalization` function to the data.
`...`	Other optionnal arguments of the above pre-processing functions.
`export`	If `TRUE`, will export the spectral intensities and the aquisition parameters matrices.
`format`	Format chosen to export the spectral intensities and the aquisition parameters matrices.
`out.path`	Path used to export the spectral intensities and the aquisition parameters matrices if `export == TRUE` and the function argument if `writeArg == "txt"`.
`filename`	Name given to exported files.
`writeArg`	If not `"none"`, will export the function arguments, either in the return of the function (`"return"`) or as a text file (`"txt"`).
`verbose`	If `"TRUE"`, will print processing information.

The function will return a list with the spectral intensities and the aquisition parameters matrices. If writeArg == "return", an additionnal list element is returned (arguments).

`Spectrum_data`	The pre-processed spectra.
`Fid_info`	The acquisition parameters.
`arguments`	The function arguments.

Manon Martin

Martin, M., Legat, B., Leenders, J., Vanwinsberghe, J., Rousseau, R., Boulanger, B., & Govaerts, B. (2018). PepsNMR for 1H NMR metabolomic data pre-processing. Analytica chimica acta, 1019, 1-13.

Rousseau, R. (2011). Statistical contribution to the analysis of metabonomics data in 1H NMR spectroscopy (Doctoral dissertation, PhD thesis. Institut de statistique, biostatistique et sciences actuarielles, Université catholique de Louvain, Belgium).

path <-  system.file("extdata", package = "PepsNMRData")
data.path <-  file.path(path, "HumanSerum")
res <-  PreprocessingChain(Fid_data = NULL, Fid_info = NULL, data.path = data.path, 
      ReadFids = TRUE, type.norm = "mean", export = FALSE, writeArg = "return")