Metabolomics and the Development of Nontarget Discovery Analysis Methods for Two-dimensional Gas Chromatography Time-of-Flight Mass Spectrometry

Abstract

Two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC × GC - TOFMS) is a highly capable instrumental platform that produces complex and information-rich multi-dimensional chemical data. The complex data is computationally overwhelming, especially when many samples are analyzed with multiple injections for each sample. The highly information rich data from GC x GC - TOFMS benefits from elegant and comprehensive target and nontarget algorithmic methods. The development of a novel tile-based Fisher ratio method that greatly decreases the false-positive rate is described thoroughly in this dissertation. Also, the initially application of currently available instrumental and data analysis methods to the optimization of the preparation of mouse heart tissue metabolomics and the investigation of the pathophysiology of pressure overload hypertrophy is described herein. Then, novel algorithmic methods to solve issues seen with the difficult pixel-based analysis are described. Overall, GC x GC - TOFMS and the related data analysis tools investigated here aim to reduce the complex chemical data to glean the most meaningful information from an experiment.