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Urine Diabetic Vs Non-Diabetic Statstical Compare

Using the Statistical Compare and Fisher Ratio ChromaTOF Features to Define Variance Prior to Multivariate Analysis in the Small Metabolite Profile of Diabetic Versus Non-Diabetic Urine by GCxGC-TOFMS


The "Statistical Compare" option available in ChromaTOF software allows the user to view statistical comparisons as a data processing step for groups of samples. The groups of samples are divided into different subsets or classes. ChromaTOF software aligns the data for the specified group of samples from the data processed peak tables. Upon completion of peak alignment, statistical information (such as minimum, maximum, average, relative standard deviation, etc.) on various peak properties (such as peak height, peak area, retention time, etc.) can be viewed in the Compound Table generated by Statistical Compare. The software will also compare statistical information from each class and between classes. Additionally, "Fisher Ratios" can be calculated from the Compound Table for each analyte. The Fisher ratio is a statistical calculation that can be used to discover the unknown chemical differences among known classes of complex samples. Statistical Compare results can also be exported as a .csv file and applied to third party software programs for supplemental data reduction such asmultivariate analysis.

In this paper, Statistical Compare is utilized to define the small metabolite profile with potentially significant class differences between trimethylsilyl (TMS) derivatized urine from diabetic and non-diabetic subjects analyzed by GCxGC-TOFMS. This research was designed to analyze TMS-derivatized urine samples for the small molecule metabolite profile with the intent to detect possible chemical variations between diabetic diseased state and normal control non-diabetic subjects. It is important to note that this research was conducted solely as a proof of concept study to test the validity of the Statistical Compare, Fisher Ratios, and .csv file export functions that are available in the ChromaTOF software. The data mining strategy used to distinguish analyte differences between diabetic and non-diabetic sample classes begins by aligning the analytes from the processed data files using the Statistical Compare feature. Following the Statistical Compare operation, Fisher Ratios are calculated to identify the compounds showing the highest variance. The resulting Compound Table is then exported as a .csv file to a third party multivariate analysis software package where PCA and clustering analysis was executed.

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