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Wavelet-based method for noise characterization and rejection in high-performance liquid chromatography coupled to mass spectrometry

Cappadona, Salvatore LU ; Levander, Fredrik LU ; Bentz, Maria LU ; James, Peter LU ; Cerutti, Sergio and Pattini, Linda (2008) In Analytical Chemistry 80(13). p.4960-4968
Abstract
We present a new method for rejecting noise from HPLC-MS data sets. The algorithm reveals peptides at low concentrations by minimizing both the chemical and the random noise. The goal is reached through a systematic approach to characterize and remove the background. The data are represented as two-dimensional maps, in order to optimally exploit the complementary dimensions of separation of the peptides offered by the LC-MS technique. The virtual chromatograms, reconstructed from the spectrographic data, have proved to be more suitable to characterize the noise than the raw mass spectra. By means of wavelet analysis, it was possible to access both the chemical and the random noise, at different scales of the decomposition. The novel... (More)
We present a new method for rejecting noise from HPLC-MS data sets. The algorithm reveals peptides at low concentrations by minimizing both the chemical and the random noise. The goal is reached through a systematic approach to characterize and remove the background. The data are represented as two-dimensional maps, in order to optimally exploit the complementary dimensions of separation of the peptides offered by the LC-MS technique. The virtual chromatograms, reconstructed from the spectrographic data, have proved to be more suitable to characterize the noise than the raw mass spectra. By means of wavelet analysis, it was possible to access both the chemical and the random noise, at different scales of the decomposition. The novel approach has proved to efficiently distinguish signal from noise and to selectively reject the background while preserving low-abundance peptides. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Analytical Chemistry
volume
80
issue
13
pages
4960 - 4968
publisher
The American Chemical Society
external identifiers
  • wos:000257270600027
  • scopus:46849101222
ISSN
1520-6882
DOI
10.1021/ac800166w
language
English
LU publication?
yes
id
54a5499d-e65b-4702-9a45-9b595c30842e (old id 1187181)
date added to LUP
2008-09-05 09:31:50
date last changed
2017-04-16 03:40:18
@article{54a5499d-e65b-4702-9a45-9b595c30842e,
  abstract     = {We present a new method for rejecting noise from HPLC-MS data sets. The algorithm reveals peptides at low concentrations by minimizing both the chemical and the random noise. The goal is reached through a systematic approach to characterize and remove the background. The data are represented as two-dimensional maps, in order to optimally exploit the complementary dimensions of separation of the peptides offered by the LC-MS technique. The virtual chromatograms, reconstructed from the spectrographic data, have proved to be more suitable to characterize the noise than the raw mass spectra. By means of wavelet analysis, it was possible to access both the chemical and the random noise, at different scales of the decomposition. The novel approach has proved to efficiently distinguish signal from noise and to selectively reject the background while preserving low-abundance peptides.},
  author       = {Cappadona, Salvatore and Levander, Fredrik and Bentz, Maria and James, Peter and Cerutti, Sergio and Pattini, Linda},
  issn         = {1520-6882},
  language     = {eng},
  number       = {13},
  pages        = {4960--4968},
  publisher    = {The American Chemical Society},
  series       = {Analytical Chemistry},
  title        = {Wavelet-based method for noise characterization and rejection in high-performance liquid chromatography coupled to mass spectrometry},
  url          = {http://dx.doi.org/10.1021/ac800166w},
  volume       = {80},
  year         = {2008},
}