Abstract
This case study describes data analysis of a chromatogram distributed for the 2019 GC×GC Data Challenge for the Tenth Multidimensional Chromatography Workshop (Liege, Belgium). The chromatogram resulted from chemical analysis of a terpene-standards sample by comprehensive two-dimensional chromatography with mass spectrometry (GC×GC-MS). First, several aspects of the data quality are assessed, including detector saturation and oscillation, and operations to prepare the data for analyte detection and identification are described, including phase roll for modulation-cycle alignment and baseline correction to account for the non-zero detector baseline. Then, the case study presents operations for analyte detection with filtering, a new method to flag false detections, interactive review to confirm detected peaks, and ion-peaks detection to reveal peaks that are obscured by noise or coelution. Finally, the case study describes analyte identification including mass-spectral library search with a new method for optimizing spectra extraction, retention-index calibration from preliminary identifications, and expression-based identification checks. Processing of the first 40 min of data detected 144 analytes, 21 of which have at least one percent response, plus an additional 20 trace and/or coeluted analytes.
Highlights
The difficulty of detecting and identifying analytes in data from comprehensive two-dimensional gas chromatography with mass spectrometry (GC×GC-MS) ranges from simple, for resolved analytes that have clear spectral signals matched in mass-spectral libraries, to challenging, for coeluted and trace analytes that have obscure or faint signals and ambiguous matching with mass-spectral libraries [1,2,3,4,5]
The data for the case study is a GC×GC-MS chromatogram of a terpene-standards sample released for the Data Challenge at the 10th Multidimensional Chromatography Workshop
A series of experiments aimed to maximize performance of MS library search with respect to several methods and settings for extracting mass spectra from the chromatogram and several options for the MS library presearch. The results of these experiments are of interest for this case study, but the ultimate goal is to develop a new method for automating the determination of settings for MS library search for a given chromatogram without a priori identifications
Summary
The difficulty of detecting and identifying analytes in data from comprehensive two-dimensional gas chromatography with mass spectrometry (GC×GC-MS) ranges from simple, for resolved analytes that have clear spectral signals matched in mass-spectral libraries, to challenging, for coeluted and trace analytes that have obscure or faint signals and ambiguous matching with mass-spectral libraries [1,2,3,4,5]. This case study examines a combination of time-tested and new peak detection techniques, beginning with the 2D drain algorithm that is highly effective for resolved peaks, filtering of those peaks, followed by a new method for predicting true and false peak detections, and combined with a new tool that detects collections of coincident ion-peaks It considers analyte identification with mass-spectral library search, using a new method for parameterizing extraction of mass spectra in order to maximize search performance; retention-index calibration, using library retention indices from preliminary identifications; and expression-based identification checks. The data for the case study is a GC×GC-MS chromatogram of a terpene-standards sample released for the Data Challenge at the 10th Multidimensional Chromatography Workshop (Liege,Belgium, 2019).
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