Change search
ReferencesLink to record
Permanent link

Direct link
Validated and predictive processing of gas chromatography-mass spectra screening studies, diagnostics and metabolite pattern verification
Umeå University, Faculty of Science and Technology, Department of Chemistry.
Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
Umeå University, Faculty of Medicine, Department of Surgical and Perioperative Sciences, Sports Medicine.
Umeå University, Faculty of Science and Technology, Department of Chemistry.
Show others and affiliations
2012 (English)In: Metabolites, ISSN 2218-1989, Vol. 2, no 4, 796-817 p.Article in journal (Refereed) Published
Abstract [en]

The suggested approach makes it feasible to screen large metabolomics data, sample sets with retained data quality or to retrieve significant metabolic information from small sample sets that can be verified over multiple studies. Hierarchical multivariate curve resolution (H-MCR), followed by orthogonal partial least squares discriminant analysis (OPLS-DA) was used for processing and classification of gas chromatography/time of flight mass spectrometry (GC/TOFMS) data characterizing human serum samples collected in a study of strenuous physical exercise. The efficiency of predictive H-MCR processing of representative sample subsets, selected by chemometric approaches, for generating high quality data was proven. Extensive model validation by means of cross-validation and external predictions verified the robustness of the extracted metabolite patterns in the data. Comparisons of extracted metabolite patterns between models emphasized the reliability of the methodology in a biological information context. Furthermore, the high predictive power in longitudinal data provided proof for the potential use in clinical diagnosis. Finally, the predictive metabolite pattern was interpreted physiologically, highlighting the biological relevance of the diagnostic pattern.

Place, publisher, year, edition, pages
M D P I AG , 2012. Vol. 2, no 4, 796-817 p.
Keyword [en]
metabolomics, chemometrics, information, large data, GC/MS, curve resolution, diagnosis
National Category
Biochemistry and Molecular Biology
URN: urn:nbn:se:umu:diva-62181DOI: 10.3390/metabo2040796OAI: diva2:575544
Available from: 2012-12-10 Created: 2012-12-10 Last updated: 2015-08-26Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full text

Search in DiVA

By author/editor
Thysell, ElinChorell, ElinSvensson, MichaelJonsson, PärAntti, Henrik
By organisation
Department of ChemistryMedicineSports Medicine
In the same journal
Biochemistry and Molecular Biology

Search outside of DiVA

GoogleGoogle Scholar

Altmetric score

Total: 93 hits
ReferencesLink to record
Permanent link

Direct link