title: Application of parallel computing to speed up chemometrics for GC×GC-TOFMS based metabolic fingerprinting.
abstract: Parallel computing was tested regarding its ability to speed up chemometric operations for data analysis. A set of metabolic samples from a second hand smoke (SHS) experiment was analyzed with comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC-TOFMS). Data was further preprocessed and analyzed. The preprocessing step comprises background correction, smoothing and alignment of the chromatographic signal. Data analysis was performed by applying t-test and partial least squares projection to latent structures discriminant analysis (PLS-DA). The optimization of the algorithm for parallel computing led to a substantial increase in performance. Metabolic fingerprinting showed a discrimination of the samples and indicates a metabolic effect of SHS.
authors.affiliation: Institute of Ecological Chemistry, Cooperation Group Analysis of complex molecular systems, Helmholtz Zentrum München, 85764 Neuherberg, Germany.
authors.forename: Thomas
authors.initials: T
authors.lastname: Gröger
authors.forename: Ralf
authors.initials: R
authors.lastname: Zimmermann
mesh_terms: D003201:Computers; D008401:Gas Chromatography-Mass Spectrometry / Q000379:methods*; D048088:Informatics / Q000379:methods*; D055442:Metabolome; D055432:Metabolomics / Q000379:methods*; D012984:Software; D013997:Time Factors