| Dokumentenart: | Artikel | ||||||||||||||||||||||||
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| Titel eines Journals oder einer Zeitschrift: | Journal of chromatography A | ||||||||||||||||||||||||
| Verlag: | Elsevier | ||||||||||||||||||||||||
| Band: | 1218 | ||||||||||||||||||||||||
| Nummer des Zeitschriftenheftes oder des Kapitels: | 39 | ||||||||||||||||||||||||
| Seitenbereich: | S. 7031-7038 | ||||||||||||||||||||||||
| Datum: | September 2011 | ||||||||||||||||||||||||
| Institutionen: | Medizin > Lehrstuhl für Anästhesiologie Medizin > Institut für Funktionelle Genomik > Lehrstuhl für Funktionelle Genomik (Prof. Oefner) Medizin > Institut für Funktionelle Genomik > Lehrstuhl für Statistische Bioinformatik (Prof. Spang) Informatik und Data Science > Fachbereich Bioinformatik > Lehrstuhl für Statistische Bioinformatik (Prof. Spang) | ||||||||||||||||||||||||
| Identifikationsnummer: |
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| Klassifikation: |
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| Stichwörter / Keywords: | Alignment; Data mining; GC × GC–TOFMS; Metabolic fingerprinting; Metabolomics; Spike-in experiment | ||||||||||||||||||||||||
| Dewey-Dezimal-Klassifikation: | 500 Naturwissenschaften und Mathematik > 500 Naturwissenschaften 500 Naturwissenschaften und Mathematik > 570 Biowissenschaften, Biologie 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin | ||||||||||||||||||||||||
| Status: | Veröffentlicht | ||||||||||||||||||||||||
| Begutachtet: | Ja, diese Version wurde begutachtet | ||||||||||||||||||||||||
| An der Universität Regensburg entstanden: | Ja | ||||||||||||||||||||||||
| Dokumenten-ID: | 30621 |
Zusammenfassung
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 ...
Zusammenfassung
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 1.1- to 4-fold changes in metabolite concentration was assessed by spiking 20 standard compounds into an aqueous methanol extract of E. coli. To provide the same quality input signals for both alignment routines, the universal m/z 73 trace of the trimethylsilyl (TMS) group was used as a quantitative measure for all features. The performance of data processing and alignment was evaluated and illustrated by ROC curves. Statistical Compare performed marginally better at the lower fold changes, while INCA did so at the higher fold changes. Using SC, quantitative precision could be improved substantially by exploiting the signal intensities of metabolite-specific unique (U) m/z ion traces rather than the universal m/z 73 trace. A list of 56 features that distinguished the two E. coli strains was obtained by the SC alignment using m/z U with an estimated false discovery rate (FDR) of <0.05. Ultimately, 23 metabolites could be identified, one additional and five less than with INCA due to the failure of SC to extract unitized m/z U's across all fingerprints with suitable spectral intensities for the latter metabolites.
Metadaten zuletzt geändert: 29 Sep 2021 07:40
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