Spectral Processing Considerations for the Analysis of NMR Based Metabolomics Data

• Author / Creator

  Chang, David Wai Ming

• Employing a combination of biochemistry and chemometrics, the field of metabolomics has the potential to reveal some very significant insights into biological pathways related to drugs and diseases. This thesis explores this field in its depths; specifically focusing on Nuclear Magnetic Resonance (NMR) based methods. The thesis begins with an exploration of the quantum level relationships of molecules, and how these coupling patterns evolve into an NMR spectrum. The thesis will describe the development of a simplified spin simulation algorithm to predict NMR spin coupling patterns that are computed in fractions of a second and to build mathematically relevant basis functions. Later in the thesis, the issue of baseline distortions of real NMR experimental data is addressed by the development of an automated baseline correction algorithm. Data reduction techniques are further analyzed to understand the importance of the quality of the data used in advanced chemometric methods. For analysis of the data, the use of simple univariate techniques applied to NMR spectra of urine is explored to determine statistically significant biomarkers between disease states in asthma. More advanced statistics in the way of multivariate models, namely Partial Least Squares – Discriminant Analysis (PLS-DA), were used to build predictive models of Streptococcus pneumoniae pneumonia from NMR spectra of urine. Potential characteristics of the data that may invalidate assumptions required in our models were accounted for, such as ensuring the statistical normality of the S. pneumoniae pneumonia data by using log transformations. After the analysis, focus was given to the use of unique visualization techniques to further explore the complex relationships that exist between samples and variables, and relationships between variables. As will be made evident, this thesis deals with the basic physics of an NMR signal to building highly sophisticated models to help understand the NMR spectra from complex mixtures. All of these notions are important in the objective to garner the most information provided through an NMR experiment, as such to aid in the discovery of biochemical knowledge.

• Subjects / Keywords

  • Metabolomics, Spectal Processing, Digital Signal Processing

• Graduation date

  Fall 2009

• Type of Item

  Thesis

• Degree

  Doctor of Philosophy

• DOI

  https://doi.org/10.7939/R3DH2H

• License

  This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.