Data Analysis Tool for Comprehensive Two-Dimensional Gas Chromatography/Time-of-Flight Mass Spectrometry

摘要

ABSTRACT: Data processing and identification of unknownncompounds in comprehensive two-dimensional gas chromatog-nraphy combined with time-of-flight mass spectrometryn(GCu0001GC/TOFMS) analysis is a major challenge, particularlynwhen large sample sets are analyzed. Herein, we present a methodnfor efficient treatment of large data sets produced by GCu0001GCTOFMS implemented as a freely available open source softwarenpackage, Guineu. To handle large data sets and to efficientlynutilize all the features available in the vendor software (baselinencorrection, mass spectral deconvolution, peak picking, integra-ntion, library search, and signal-to-noise filtering), data prepro-ncessed by instrument software are used as a starting point fornfurther processing. Our software affords alignment of the data,nnormalization, data filtering, and utilization of retention indexesnin the verification of identification as well as a novel tool fornautomated group-type identification of the compounds. Herein, different features of the software are studied in detail and thenperformance of the system is verified by the analysis of a large set of standard samples as well as of a large set of authentic biologicalnsamples, including the control samples. The quantitative features of our GCu0001GC/TOFMSmethodology are also studied to furtherndemonstrate the method performance and the experimental results confirm the reliability of the developed procedure. Thenmethodology has already been successfully used for the analysis of several thousand samples in the field of metabolomics.