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Automated annotation and quantification of metabolites in (1)H NMR data of biological origin
Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.ORCID-id: 0000-0003-2013-8093
Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för analytisk kemi.
Vise andre og tillknytning
2012 (engelsk)Inngår i: Analytical and Bioanalytical Chemistry, ISSN 1618-2642, E-ISSN 1618-2650, Vol. 403, nr 2, s. 443-455Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

In 1H NMR metabolomic datasets, there are often over a thousand peaks per spectrum, many of which change position drastically between samples. Automatic alignment, annotation, and quantification of all the metabolites of interest in such datasets have not been feasible. In this work we propose a fully automated annotation and quantification procedure which requires annotation of metabolites only in a single spectrum. The reference database built from that single spectrum can be used for any number of 1H NMR datasets with a similar matrix. The procedure is based on the generalized fuzzy Hough transform (GFHT) for alignment and on Principal-components analysis (PCA) for peak selection and quantification. We show that we can establish quantities of 21 metabolites in several 1H NMR datasets and that the procedure is extendable to include any number of metabolites that can be identified in a single spectrum. The procedure speeds up the quantification of previously known metabolites and also returns a table containing the intensities and locations of all the peaks that were found and aligned but not assigned to a known metabolite. This enables both biopattern analysis of known metabolites and data mining for new potential biomarkers among the unknowns.

sted, utgiver, år, opplag, sider
2012. Vol. 403, nr 2, s. 443-455
Emneord [en]
1H NMR, Alignment, Multivariate, Metabolomics, Hough transform, Urine, Quantification, Spectral profiling
HSV kategori
Forskningsprogram
analytisk kemi
Identifikatorer
URN: urn:nbn:se:su:diva-74546DOI: 10.1007/s00216-012-5789-xISI: 000302256800012OAI: oai:DiVA.org:su-74546DiVA, id: diva2:510534
Tilgjengelig fra: 2012-03-16 Laget: 2012-03-16 Sist oppdatert: 2020-02-20bibliografisk kontrollert
Inngår i avhandling
1. Solving the correspondence problem in analytical chemistry: Automated methods for alignment and quantification of multiple signals
Åpne denne publikasjonen i ny fane eller vindu >>Solving the correspondence problem in analytical chemistry: Automated methods for alignment and quantification of multiple signals
2012 (engelsk)Doktoravhandling, med artikler (Annet vitenskapelig)
Abstract [en]

When applying statistical data analysis techniques to analytical chemical data, all variables must have correspondence over the samples dimension in order for the analysis to generate meaningful results. Peak shifts in NMR and chromatography destroys that correspondence and creates data matrices that have to be aligned before analysis. In this thesis, new methods are introduced that allow for automated transformation from unaligned raw data to aligned data matrices where each column corresponds to a unique signal. These methods are based around linear multivariate models for the peak shifts and Hough transform for establishing the parameters of these linear models. Methods for quantification under difficult conditions, such as crowded spectral regions, noisy data and unknown peak identities are also introduced. These methods include automated peak selection and a robust method for background subtraction. This thesis focuses on the processing of the data; the experimental work is secondary and is not discussed in great detail.

All the developed methods are put together in a full procedure that takes us from raw data to a table of concentrations in a matter of minutes.

The procedure is applied to 1H-NMR data from biological samples, which is one of the toughest alignment tasks available in the field of analytical chemistry. It is shown that the procedure performs consistently on the same level as much more labor intensive manual techniques such as Chenomx NMRSuite spectral profiling.

Several kinds of datasets are evaluated using the procedure. Most of the data is from the field of Metabolomics, where the goal is to establish concentrations of as many small molecules as possible in biological samples.

sted, utgiver, år, opplag, sider
Stockholm: Department of Analytical Chemistry, Stockholm University, 2012. s. 74
HSV kategori
Forskningsprogram
analytisk kemi
Identifikatorer
urn:nbn:se:su:diva-74556 (URN)978-91-7447-485-5 (ISBN)
Disputas
2012-05-25, Magnélisalen, Kemiska övningslaboratoriet, Svante Arrhenius väg 16 B, Stockholm, 13:00 (engelsk)
Opponent
Veileder
Tilgjengelig fra: 2012-05-03 Laget: 2012-03-16 Sist oppdatert: 2012-05-02bibliografisk kontrollert

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