Examination of the two-dimensional mass channel cluster plot method for gas chromatography - mass spectrometry in the context of the statistical model of overlap.

Evaluation of a recently developed data reduction method for gas chromatography time-of-flight mass spectrometry (GC-TOFMS) is presented in the context of the statistical model of overlap (SMO) using simulated chromatographic data. The two-dimensional mass cluster plot method (2D m/z cluster plot method) significantly improves separation visualization by measuring the retention time, t, and peak width-at-base, w, of each analyte peak on a per mass channel, m/z, basis and plotting w versus t as a single point for each peak. Additional selectivity is provided by the peak width dimension, allowing for the differentiation of "pure" or selective m/z and shared or overlapped m/z. Analyte clusters in the 2D mass cluster plot are defined based on clustering of individual points, representing the selective m/z for those analytes, and encompassed by a box of user-specified size. The method is applied to simulated chromatographic data with a random, independent distribution of analyte peaks and constant peak w. Two levels of chromatographic saturation factor, α, and two sets of analyte mass spectra with varying spectral similarity are studied to assess method performance. The percentage of analyte clusters found relative to the number of analytes simulated in the chromatogram increases as the box size (analogous to chromatographic resolution, R) is decreased, resulting in an R limit of 0.05 for the method. Additionally, the percentage of analyte clusters discovered also increases with lower α and greater dissimilarity between analyte mass spectra, demonstrating the immense benefit of improving the chromatographic separation and chemical selectivity in analyte discovery, identification, and quantification.