Metabolomics Data Analysis Improvement by Use of the Filter Diagonalization Method
The filter diagonalization method (FDM) was implemented and used instead of fast Fourier transform (FFT) to obtain the nuclear magnetic resonance (NMR) spectra from the free induction decay (FID) signals. The areas obtained by the FDM, from selected absorption lines, were used as input for a multidimensional method of data analysis. This procedure was applied in a NMR-based metabolomics investigation. In FDM, instead of spectra, the absorption peaks’ specification, such as central frequency, line width, amplitude and relative phases, are estimated and the spectra are built using this information. Therefore, one can select the lines by width and intensity to exclude the broad lines such as baseline, solvent line and albumin peak. Also lines with small amplitude such as noise can be excluded from the spectra. Moreover, the spectra do not suffer from aliasing or baseline problems. These characteristics are fundamental in the metabolomics investigations. To show the superiority of our method over the standard FFT to obtain the spectra, we reconstructed the spectra from simulated FID by both methods. As an example, this new approach is used to analyze the non-small cell lung cancer A549 exposed to different treatments and principal component analysis is used to compare the performance of both methods.
The author HJC wants to thank Dr. Claudio Jose Magon for the useful discussions about the FDM. The NMR experiments were executed at the Laboratório Nacional de Biociências (LNBIO), part of the Centro Nacional de Pesquisa em Energia e Materiais (CNPEM), project RMN-20606. The authors desire to express gratitude to Sílvia Rocco and Maurício Luís Sforça of the LNBIO for their assistance in NMR measurements. The non-small cell lung cancer, A549 cells line, were cultivated with collaboration of Dr. Roger Chammas group in Cancer Institute of the São Paulo State (ICESP).
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