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StePSIM – a method for stepwise peak selection and identification of metabolites in 1 H NMR spectra

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A method for stepwise selection of peaks in NMR spectra from multiple groups is described. This method is based on initial peak-finding among the spectra and uses jacknife classification performance as the basis for selection of peaks. The selection process is followed by the construction of correlation maps to identify sets of multiplets that are related to each of the selected peaks, aiding in the identification of metabolites that are responsible for differences among the groups. For illustrative purposes, this methodology is applied to a data set that contains 52 spectra from renal cell carcinoma and normal renal tissue samples. The new method is denoted as StePSIM, Stepwise Peak Selection and Identification of Metabolites.

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References

  • Ammann, L., Merritt, M., Sagalowsky, A. and Nurenberg, P. (2006). Peak-finding partial least squares for the analysis of 1 H NMR spectra. J. Chemometrics. 20

  • Antti, H., Ebbels, T., Keun, H., et al. (2004) Statistical experimental design and partial least squares regression analysis of biofluid metabonomic NMR and clinical chemistry data for screening of adverse drug effects. Chemom. Intell. Lab. Syst. 73:139–149

    Article  CAS  Google Scholar 

  • Broadhurst, D., Goodacre, R., Jones, A., Rowland, J.J., Kell, D.B. (1997) Genetic algorithms as a method for variable selection in multiple linear regression and partial least squares regression, with applications to pyrolysis mass spectrometry. Analytica Chimica Acta. 348:71–86

    Article  CAS  Google Scholar 

  • de Jong, S. (1993) SIMPLS: an alternative approach to partial least squares regression. Chemom. Intell. Lab. Syst. 18:251–263

    Article  Google Scholar 

  • Efron, B. (1982). The Jacknife, the Bootstrap and Other Resampling Plans. SIAM, Philadelphia

    Google Scholar 

  • Huber, P. (1981). Robust Statistics. Wiley, New York

    Book  Google Scholar 

  • Nurenberg, P., Sartoni-D’Ambrosia, G. and Szczepaniak, L.S. (2002). Magnetic resonance spectroscopy of renal and other retroperitoneal tumors. Curr. Opin. Urol. 12(5):375–380

    Article  Google Scholar 

  • Ramadan, Z., Jacobs, D., Grigorov, M., Kochhar, S. (2006) Metabolic profiling using principal component analysis, discriminant partial least squares, and genetic algorithms. Talanta. 68:1683–1691

    Article  CAS  Google Scholar 

  • R Development Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, URL http://www.R-project.org. 2004

  • Trbovic, N., Smirnov, S., Zhang, F., Brüschweiler, R. (2004) Covariance NMR spectroscopy by singular value decomposition. J. Magn. Reson. 171:277–283

    Article  PubMed  CAS  Google Scholar 

  • Wang, Y., Holmes, E., Nicholson, J.K., et al. (2004) Metabonomic investigations in mice infected with Schistosoma mansoni: an approach for biomarker identification. Proc. Nat. Acad. Sci. 101:12676–12681

    Article  PubMed  CAS  Google Scholar 

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Correspondence to L. P. Ammann.

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Research partially supported by NCI 1 R21 CA89671-01A1 and NIH NCRR 02584

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Ammann, L.P., Merritt, M. StePSIM – a method for stepwise peak selection and identification of metabolites in 1 H NMR spectra. Metabolomics 3, 1–11 (2007). https://doi.org/10.1007/s11306-006-0041-3

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  • DOI: https://doi.org/10.1007/s11306-006-0041-3

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