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Title: Using Receiver Operating Characteristic Curves to Optimize Discovery-Based Software with Comprehensive Two-Dimensional Gas Chromatography with Time-of-Flight Mass Spectrometry

Journal Article · · Analytical Chemistry

We report a quantitative approach to optimize implementation of discovery-based software for comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC × GC – TOFMS). The software performs a tile-based Fisher ratio (F-ratio) analysis, and facilitates a supervised non-targeted analysis based upon the experimental design to aid in the discovery of analytes whose variances are statistically different between sample classes. The quantitative approach for software optimization uses receiver operating characteristic (ROC) curves. The area under the curve (AUC) of each ROC curve serves as a quantitative metric to optimize two key algorithm parameters: the signal-to-noise ratio (S/N) threshold of the baseline corrected and normalized data prior to calculating F-ratios at each m/z mass channel, and the number of these F-ratios per m/z to include in the calculation of the average F-ratio of a tile. A total of 25 combinations of S/N threshold by number of m/z were studied. Fifty analytes were spiked into a diesel fuel at two concentration spike levels to produce two sample classes that should in principle produce 50 positive instances in the ROC curves (30 native/20 non-native compounds, at spike levels of 200/20 and100/10 ppm native/non-native, respectively). The “sweet spot” for F-ratio analysis was determined to be a S/N threshold of 10 coupled with a maximum of the 10 most chemically selective m/z (requiring a minimum of 3 m/z), corresponding to a ~ 21% improvement in the discovery rate of true positives relative to prior studies. Furthermore, it was observed that optimization of these software parameters did not depend upon a priori determination of the statistically correct number of positive instances in the sample classes. The AUC metric appears to be suitable for the evaluation of all data analysis methods that utilize the proper experimental design.

Research Organization:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Organization:
USDOE
DOE Contract Number:
AC05-76RL01830
OSTI ID:
1770377
Report Number(s):
PNNL-SA-123039
Journal Information:
Analytical Chemistry, Vol. 89, Issue 6; ISSN 0003--2700
Country of Publication:
United States
Language:
English