Simple data-reduction method for high-resolution LC-MS data in metabolomics

R. A. Scheltema, S. Decuypere, J. C. Dujardin, D. G. Watson, R. C. Jansen, R. Breitling

Research output: Contribution to journalArticle

43 Citations (Scopus)

Abstract

Metabolomics LC-MS experiments yield large numbers of peaks, few of which can be identified by database matching. Many of the remaining peaks correspond to derivatives of identified peaks (e.g., isotope peaks, adducts, fragments and multiply charged molecules). In this article, we present a data-reduction approach that automatically identifies these derivative peaks. Results: Using data-driven clustering based on chromatographic peak shape correlation and intensity patterns across biological replicates, derivative peaks can be reliably identified. Using a test data set obtained from Leishmania donovani extracts, we achieved a 60% reduction of the number of peaks. After quality control filtering, almost 80% of the peaks could putatively be identified by database matching. Automated peak filtering substantially speeds up the data-interpretation process.

LanguageEnglish
Pages1551-1557
Number of pages7
JournalBioanalysis
Volume1
Issue number9
DOIs
Publication statusPublished - Dec 2009

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Metabolomics
Data reduction
Databases
Derivatives
Leishmania donovani
Isotopes
Quality Control
Cluster Analysis
Quality control
Molecules
Experiments
Datasets

Keywords

  • metabolomics
  • peak filtering
  • Leishmania donovani extracts

Cite this

Scheltema, R. A., Decuypere, S., Dujardin, J. C., Watson, D. G., Jansen, R. C., & Breitling, R. (2009). Simple data-reduction method for high-resolution LC-MS data in metabolomics. Bioanalysis, 1(9), 1551-1557. https://doi.org/10.4155/BIO.09.146
Scheltema, R. A. ; Decuypere, S. ; Dujardin, J. C. ; Watson, D. G. ; Jansen, R. C. ; Breitling, R. / Simple data-reduction method for high-resolution LC-MS data in metabolomics. In: Bioanalysis. 2009 ; Vol. 1, No. 9. pp. 1551-1557.
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Scheltema, RA, Decuypere, S, Dujardin, JC, Watson, DG, Jansen, RC & Breitling, R 2009, 'Simple data-reduction method for high-resolution LC-MS data in metabolomics' Bioanalysis, vol. 1, no. 9, pp. 1551-1557. https://doi.org/10.4155/BIO.09.146

Simple data-reduction method for high-resolution LC-MS data in metabolomics. / Scheltema, R. A.; Decuypere, S.; Dujardin, J. C.; Watson, D. G.; Jansen, R. C.; Breitling, R.

In: Bioanalysis, Vol. 1, No. 9, 12.2009, p. 1551-1557.

Research output: Contribution to journalArticle

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AU - Scheltema, R. A.

AU - Decuypere, S.

AU - Dujardin, J. C.

AU - Watson, D. G.

AU - Jansen, R. C.

AU - Breitling, R.

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AB - Metabolomics LC-MS experiments yield large numbers of peaks, few of which can be identified by database matching. Many of the remaining peaks correspond to derivatives of identified peaks (e.g., isotope peaks, adducts, fragments and multiply charged molecules). In this article, we present a data-reduction approach that automatically identifies these derivative peaks. Results: Using data-driven clustering based on chromatographic peak shape correlation and intensity patterns across biological replicates, derivative peaks can be reliably identified. Using a test data set obtained from Leishmania donovani extracts, we achieved a 60% reduction of the number of peaks. After quality control filtering, almost 80% of the peaks could putatively be identified by database matching. Automated peak filtering substantially speeds up the data-interpretation process.

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Scheltema RA, Decuypere S, Dujardin JC, Watson DG, Jansen RC, Breitling R. Simple data-reduction method for high-resolution LC-MS data in metabolomics. Bioanalysis. 2009 Dec;1(9):1551-1557. https://doi.org/10.4155/BIO.09.146