Comparison of two algorithmic data processing strategies for metabolic fingerprinting by comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry.

The alignment algorithm Statistical Compare (SC) developed by LECO Corporation for the processing of comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC×GC-TOFMS) data was validated and compared to the in-house developed retention time correction and data alignment tool INCA (Integrative Normalization and Comparative Analysis) by a spike-in experiment and the comparative metabolic fingerprinting of a wild type versus a double mutant strain of Escherichia coli (E. coli). Starting with the same peak lists generated by LECO's ChromaTOF software, the accuracy of peak alignment and detection of 1.

Estimating classification probabilities in high-dimensional diagnostic studies.

Motivation: Classification algorithms for high-dimensional biological data like gene expression profiles or metabolomic fingerprints are typically evaluated by the number of misclassifications across a test dataset. However, to judge the classification of a single case in the context of clinical diagnosis, we need to assess the uncertainties associated with that individual case rather than the average accuracy across many cases. Reliability of individual classifications can be expressed in terms of class probabilities.

Comparison of serum versus plasma collection in gas chromatography--mass spectrometry-based metabolomics.

Bovine serum, EDTA-plasma and EDTA-plasma fortified with acetylsalicylic acid (ASA) as antioxidant were compared with regard to their suitability for metabolomic studies. Metabolic fingerprints were generated from GC-TOF-MS data using the Leco ChromaTOF software in combination with the in-house retention time correction and data alignment tool INCA. A total of 6, 9 and 21 significant features with a false discovery rate of <0.

Integrative normalization and comparative analysis for metabolic fingerprinting by comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry.

Comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC x GC-TOF-MS) was applied to the comparative metabolic fingerprinting of a wild-type versus a double mutant strain of Escherichia coli lacking the transhydrogenases UdhA and PntAB. Using peak lists generated with the Leco ChromaTOF software as input, we developed retention time correction and data alignment tools (INCA). The accuracy of peak alignment and detection of 1.