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Uncovering hidden compositional changes in breath profiles using untargeted chemometric workflows

This study describes the use of thermal desorption (TD) and GC×GC–TOF MS for exploratory profiling of biomarkers in breath, coupled with innovative data mining tools to uncover hidden compositional changes using automated untargeted workflows.

TD–GC×GC–TOF MS was used to capture nine comprehensive breath profiles from two groups of participants, with the goal of identifying compositional differences between the two groups. ChromCompare+, a powerful data mining and chemometrics platform, was used to automatically find significant differences between sample classes in the resulting complex datasets.

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