This study describes a new chemometric tool for the analysis of chromatographic data: the Superposing Significant Interaction Rules (SSIR) is a variable selector coming from QSAR field that directly analyses the raw internal data coming from the chromatographic software. This allowed the identification of relevant volatile compounds in cork (treated and not treated samples in the industry) extracted by untargeted HS-SPME in a particular case for which traditional treatments (PCA, Discriminant Analysis) did not produced relevant results. The procedure has revealed the presence of compounds which are increased in the case of treated samples. The obtained classificatory model is robust, as it passed satisfactorily cross-validation tests (96% or more in performance for leave-one-out processes). This is the first time SSIR procedure is applied for the analysis of chromatographic information.
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Analyzing chromatographic data with the Superposing Significant Interaction Rules (SSIR) chemometric tool
Published: 30 March 2020 by MDPI in MOL2NET'20, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 6th ed. congress CHEMBIOINFO-06: Chem-Bioinformatics Congress, München, Germany-Chapel Hill, USA, 2020.
Keywords: Superposing Significant Interaction Rules; Variable Selection; Cork; Volatiles; Gas Chromatography; SPME