Novel Software Applications for the Statistical Analysis of 1H NMR-Based Metabolomics Data

Abstract

1H NMR spectroscopy is a powerful tool with which metabolites can be identified and assigned. NMR spectra contain a vast amount of data; careful processing and analysis must be conducted in order to assess the significance of such findings. This study focuses on this specific aspect of NMR spectroscopy, and approaches it through the lenses of statistical analysis. This study has two goals: first, to detect distinctions between the datasets of different types of anti-malarial treatments and horses of different ages, and second, more importantly, to develop a method of analyzing metabolomic data. Building on prior studies on the efficacy of anti-malarial drugs, this study reaffirms the potential of an anti-malarial drug candidate with significantly improved tools of analysis that allows for a more meticulous observation of data. It also performs a careful observation of the changing metabolic profiles of adolescent horses. In the process of doing so, it demonstrates the capabilities of STOCSY analysis and back-calculated coefficient plots as powerful tools in metabolomic analysis.