Toward automated chromatographic fingerprinting: A non-alignment approach to gas chromatography mass spectrometry data

Abstract

In contrast to targeted analysis of volatile compounds, non-targeted approaches take information of known and unknown compounds into account, are inherently more comprehensive and give a more holistic representation of the sample composition. Although several non-targeted approaches have been developed, there's still a demand for automated data processing tools, especially for complex multi-way data such as chromatographic data obtained from multichannel detectors. This work was therefore aimed at developing a data processing procedure for gas chromatography mass spectrometry (GC-MS) data obtained from non-targeted analysis of volatile compounds. The developed approach uses basic matrix manipulation of segmented GC-MS chromatograms and PARAFAC multi-way modelling. The approach takes retention time shifts and peak shape deformations between samples into account and can be done with the freely available N-way toolbox for MATLAB. A demonstration of the new fingerprinting approach is presented using an artificial GC-MS data set and an experimental full-scan GC-MS data set obtained for a set of experimental wines.

Keywords: Fingerprinting; Gas chromatography; Metabolomics; Multi-way analysis; Non-alignment; Non-targeted analysis.