New Investigator Tools for Finding Unique and Common Components in Multiple Samples with Comprehensive Two-Dimensional Chromatography
semanticscholar(2018)
Abstract
Untargeted cross-sample analyses such as sample classification and biomarker discovery require separating, quantifying, and identifying a large number of compounds in chemically rich samples and then relating the complex compositions across samples and sample classes. Advanced chromatography, mass spectrometry, and statistical data analysis methods can be combined to address this challenge [1]. In particular, separations performed with comprehensive two-dimensional chromatography (such as GCxGC and LCxLC) provide much greater separation capacity and signal-to-noise ratio than traditional one-dimensional chromatography [2,3]. Coupled with highresolution accurate mass spectrometry, comprehensive two-dimensional chromatography is a powerful analytical solution. However, the large and complex data sets produced also present challenges for data analysis.
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