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Updated: Jun 5, 2026

Chromatographic Fingerprinting by Template Matching for Data Collected by Comprehensive Two-Dimensional Gas Chromatography
Published on: September 2, 2020
Application of parallel computing to speed up chemometrics for GC×GC-TOFMS based metabolic fingerprinting
Thomas Gröger1, Ralf Zimmermann
1Institute of Ecological Chemistry, Cooperation Group Analysis of complex molecular systems, Helmholtz Zentrum München, 85764 Neuherberg, Germany.
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.
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