Development of variance rank initiated-unsupervised sample indexing for gas chromatography-mass spectrometry analysis.

Traditional non-targeted chemometric workflows for gas chromatography-mass spectrometry (GC-MS) data rely on using supervised methods, which requires a priori knowledge of sample class membership. Herein, we propose a simple, unsupervised chemometric workflow known as variance rank initiated-unsupervised sample indexing (VRI-USI). VRI-USI discovers analyte peaks exhibiting high relative variance across all samples, followed by k-means clustering on the individual peaks.

Control-Normalized Fisher Ratio Analysis of Comprehensive Two-Dimensional Gas Chromatography Time-of-Flight Mass Spectrometry Data for Enhanced Biomarker Discovery in a Metabolomic Study of Orthopedic Knee-Ligament Injury.

An innovative form of Fisher ratio (F-ratio) analysis (FRA) is developed for use with comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry (GC × GC-TOFMS) data and applied to the investigation of the changes in the metabolome in human plasma for patients with injury to their anterior cruciate ligament (ACL). Specifically, FRA provides a supervised discovery of metabolites that express a statistically significant variance in a two-sample class comparison: patients and healthy controls. The standard F-ratio utilizes the between-class variance relative to the pooled within-class variance.

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.

Determining the Probability of Achieving a Successful Quantitative Analysis for Gas Chromatography-Mass Spectrometry.

A new approach is presented to determine the probability of achieving a successful quantitative analysis for gas chromatography coupled with mass spectrometry (GC-MS). The proposed theory is based upon a probabilistic description of peak overlap in GC-MS separations to determine the probability of obtaining a successful quantitative analysis, which has its lower limit of chromatographic resolution R at some minimum chemometric resolution, R*; that is to say, successful quantitative analysis can be achieved when R ≥ R*. The value of R* must be experimentally determined and is dependent on the chemometric method to be applied.