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.

Development of gas chromatographic pattern recognition and classification tools for compliance and forensic analyses of fuels: A review.

Gas chromatography (GC) is undoubtedly the analytical technique of choice for compositional analysis of petroleum-based fuels. Over the past twenty years, as comprehensive two-dimensional gas chromatography (GC × GC) has evolved, fuel analysis has often been highlighted in scientific reports, since the complexity of fuel analysis allows for illustration of the impressive peak capacity gains afforded by GC × GC. Indeed, several research groups in recent years have applied GC × GC and chemometric data analysis to demonstrate the potential of these analytical tools to address important compliance (tax evasion, tax credits, physical quality standards) and forensic (arson investigations, oil spills) applications involving fuels.

Statistical inference of mass channel purity from Fisher ratio analysis using comprehensive two-dimensional gas chromatography with time of flight mass spectrometry data.

Tile-based Fisher ratio (F-ratio) analysis has recently been developed and validated for discovery-based studies of highly complex data collected using comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC×GC-TOFMS). In previous studies, interpretation and utilization of F-ratio hit lists has relied upon manual decomposition and quantification performed by chemometric methods such as parallel factor analysis (PARAFAC), or via manual translation of the F-ratio hit list information to peak table quantitative information provided by the instrument software (ChromaTOF). Both of these quantification approaches are bottlenecks in the overall workflow.

Discovery-based analysis and quantification for comprehensive three-dimensional gas chromatography flame ionization detection data.

Basic principles are introduced for implementing discovery-based analysis with automated quantification of data obtained using comprehensive three-dimensional gas chromatography with flame ionization detection (GC-FID). The GC-FID instrument employs dynamic pressure gradient modulation, providing full modulation (100% duty cycle) with a fast modulation period (P) of 100 ms. Specifically, tile-based Fisher-ratio analysis, previously developed for comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry (GC×GC-TOFMS), is adapted and applied for GC-FID where the third chromatographic dimension (D) is treated as the "spectral" dimension.

Impact of data bin size on the classification of diesel fuels using comprehensive two-dimensional gas chromatography with principal component analysis.

Principal component analysis (PCA) is a widely applied chemometric tool for classifying samples using comprehensive two-dimensional (2D) gas chromatography (GC × GC) separation data. Classification via PCA can be improved by 2D binning of the data. A "standard operating procedure (SOP) bin size" is often applied to improve the S/N and to mitigate potential retention time misalignment issues.

Impact of comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry experimental design on data trilinearity and parallel factor analysis deconvolution.

Comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC × GC-TOFMS) is a powerful instrument for the analysis of complex samples. Deconvolution of overlapped analytes using a suitable chemometric data analysis method such as Parallel Factor Analysis (PARAFAC) is often required. However, PARAFAC is designed to require a strict data trilinearity requirement.

Development of Ultrafast Separations Using Negative Pulse Partial Modulation To Enable New Directions in Gas Chromatography.

Partial modulation via a pulse flow valve operated in the negative pulse mode is developed for high-speed one-dimensional gas chromatography (1D-GC), comprehensive two-dimensional (2D) gas chromatography (GC × GC), and comprehensive three-dimensional gas chromatography (GC). The pulse flow valve readily provides very short modulation periods, P, demonstrated herein at 100, 200, and 300 ms, and holds significant promise to increase the scope and applicability of GC instrumentation. The negative pulse mode creates an extremely narrow, local analyte concentration pulse.

Targeted analyte deconvolution and identification by four-way parallel factor analysis using three-dimensional gas chromatography with mass spectrometry data.

Comprehensive three-dimensional gas chromatography with time-of-flight mass spectrometry (GC-TOFMS) creates an opportunity to explore a new paradigm in chemometric analysis. Using this newly described instrument and the well understood Parallel Factor Analysis (PARAFAC) model we present one option for utilization of the novel GC-TOFMS data structure. We present a method which builds upon previous work in both GC and targeted analysis using PARAFAC to simplify some of the implementation challenges previously discovered.