SignalProcessing {MSclassifR} | R Documentation |
Function performing post acquisition signal processing
Description
This function performs post acquisition signal processing for list
of MassSpectrum
objects using commonly used methods : transform intensities ("sqrt"), smoothing ("Wavelet"), remove baseline ("SNIP"), calibrate intensities ("TIC") and align spectra. Methods used are selected from the MALDIquant
and MALDIrppa
R packages.
Usage
SignalProcessing(x,
transformIntensity_method = "sqrt",
smoothing_method = "Wavelet",
removeBaseline_method = "SNIP",
removeBaseline_iterations = 25,
calibrateIntensity_method = "TIC",
alignSpectra_NoiseMethod = "MAD",
alignSpectra_method = "lowess",
alignSpectra_halfWs = 11,
alignSpectra_SN = 3,
tolerance_align = 0.002,
referenceSpectra = NULL,
minFrequency= 0.5,
binPeaks_method = "strict",
keepReferenceSpectra = FALSE,
...)
Arguments
x |
a |
transformIntensity_method |
a |
smoothing_method |
a |
removeBaseline_method |
a |
removeBaseline_iterations |
a |
calibrateIntensity_method |
a |
alignSpectra_NoiseMethod |
a |
alignSpectra_method |
a |
alignSpectra_halfWs |
a |
alignSpectra_SN |
a |
tolerance_align |
a |
referenceSpectra |
a |
minFrequency |
a |
binPeaks_method |
a |
keepReferenceSpectra |
a |
... |
other arguments from |
Details
The SignalProcessing
function provides an analysis pipeline for MassSpectrum
objects including intensity transformation, smoothing, removing baseline.
The Wavelet
method relies on the wavShrink
function of the wmtsa
package and its dependencies (now archived by CRAN). The original C code by William Constantine and Keith L. Davidson, in turn including copyrighted routines by Insightful Corp., has been revised and included into MALDIrppa
for the method to work.
All the methods used for SignalProcessing
functions are selected from MALDIquant
and MALDIrppa
packages.
Value
A list of modified MassSpectrum
objects (see MALDIquant
R package) according to chosen arguments. If the argument referenceSpectra
is not completed and the argument keepReferenceSpectra
is TRUE
, a list containing the MassSpectrum
objects modified named "spectra"
and the created reference spectrum named "RefS"
is returned.
References
Gibb S, Strimmer K. MALDIquant: a versatile R package for the analysis of mass spectrometry data. Bioinformatics. 2012 Sep 1;28(17):2270-1. doi: 10.1093/bioinformatics/bts447. Epub 2012 Jul 12. PMID: 22796955.
Javier Palarea-Albaladejo, Kevin Mclean, Frank Wright, David G E Smith, MALDIrppa: quality control and robust analysis for mass spectrometry data, Bioinformatics, Volume 34, Issue 3, 01 February 2018, Pages 522 - 523, doi: 10.1093/bioinformatics/btx628
Examples
library("MALDIquant")
library("MSclassifR")
## Load mass spectra
data("CitrobacterRKIspectra", package = "MSclassifR")
# plot first unprocessed mass spectrum
PlotSpectra(SpectralData=CitrobacterRKIspectra[[1]], col_spec="blue")
## spectral treatment
spectra <- SignalProcessing(CitrobacterRKIspectra,
transformIntensity_method = "sqrt",
smoothing_method = "Wavelet",
removeBaseline_method = "SNIP",
removeBaseline_iterations = 25,
calibrateIntensity_method = "TIC",
alignSpectra_Method = "MAD",
alignSpectra_halfWs = 11,
alignSpectra_SN = 3,
tolerance_align = 0.002)
# plot first processed mass spectrum
PlotSpectra(SpectralData=spectra[[1]], col_spec="blue")