title: The discriminant pixel approach: a new tool for the rational interpretation of GCxGC-MS chromatograms.
abstract: GCxGC is now recognized as the most suited analytical technique for the characterization of complex mixtures of volatile compounds; it is implemented worldwide in academic and industrial laboratories. However, in the frame of comprehensive analysis of non-target analytes, going beyond the visual examination of the color plots remains challenging for most users. We propose a strategy that aims at classifying chromatograms according to the chemical composition of the samples while determining the origin of the discrimination between different classes of samples: the discriminant pixel approach. After data pre-processing and time-alignment, the discriminatory power of each chromatogram pixel for a given class was defined as its correlation with the membership to this class. Using a peak finding algorithm, the most discriminant pixels were then linked to chromatographic peaks. Finally, crosschecking with mass spectrometry data enabled to establish relationships with compounds that could consequently be considered as candidate class markers. This strategy was applied to a large experimental data set of 145 GCxGC-MS chromatograms of tobacco extracts corresponding to three distinct classes of tobacco.
authors.affiliation: Laboratoire des Sciences Analytiques, Bioanalytiques et Miniaturisation (LSABM), UMR CNRS UPMC PECSA, ESPCI ParisTech, 10 rue Vauquelin, 75005 Paris, France. jerome.vial@espci.fr
authors.forename: Jérôme
authors.initials: J
authors.lastname: Vial
authors.forename: Benoît
authors.initials: B
authors.lastname: Pezous
authors.forename: Didier
authors.initials: D
authors.lastname: Thiébaut
authors.forename: Patrick
authors.initials: P
authors.lastname: Sassiat
authors.forename: Béatrice
authors.initials: B
authors.lastname: Teillet
authors.forename: Xavier
authors.initials: X
authors.lastname: Cahours
authors.forename: Isabelle
authors.initials: I
authors.lastname: Rivals
mesh_terms: D005591:Chemical Fractionation; D016002:Discriminant Analysis; D008401:Gas Chromatography-Mass Spectrometry / Q000379:methods*; D010936:Plant Extracts / Q000737:chemistry; D013223:Statistics as Topic / Q000379:methods*; D013997:Time Factors; D014026:Nicotiana / Q000737:chemistry
chemical_list: D010936:Plant Extracts