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Proof of principle of a generalized fuzzy Hough transform approach to peak alignment of one-dimensional 1H NMR data
Stockholm University, Faculty of Science, Department of Analytical Chemistry.
Stockholm University, Faculty of Science, Department of Analytical Chemistry.
Stockholm University, Faculty of Science, Department of Analytical Chemistry.
Stockholm University, Faculty of Science, Department of Analytical Chemistry.
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2007 (English)In: Analytical and Bioanalytical Chemistry, ISSN 1618-2642, E-ISSN 1618-2650, Vol. 389, no 3, 875-885 p.Article in journal (Refereed) Published
Abstract [en]

In metabolic profiling, multivariate data analysis techniques are used to interpret one-dimensional (1D) 1H NMR data. Multivariate data analysis techniques require that peaks are characterised by the same variables in every spectrum. This location constraint is essential for correct comparison of the intensities of several NMR spectra. However, variations in physicochemical factors can cause the locations of the peaks to shift. The location prerequisite may thus not be met, and so, to solve this problem, alignment methods have been developed. However, current state-of-the-art algorithms for data alignment cannot resolve the inherent problems encountered when analysing NMR data of biological origin, because they are unable to align peaks when the spatial order of the peaks changes—a commonly occurring phenomenon. In this paper a new algorithm is proposed, based on the Hough transform operating on an image representation of the NMR dataset that is capable of correctly aligning peaks when existing methods fail. The proposed algorithm was compared with current state-of-the-art algorithms operating on a selected plasma dataset to demonstrate its potential. A urine dataset was also processed using the algorithm as a further demonstration. The method is capable of successfully aligning the plasma data but further development is needed to address more challenging applications, for example urine data.

Place, publisher, year, edition, pages
2007. Vol. 389, no 3, 875-885 p.
Keyword [en]
NMR, Peak detection, Hough transform, Alignment, Metabolic profiling
National Category
Analytical Chemistry
Research subject
Analytical Chemistry
Identifiers
URN: urn:nbn:se:su:diva-10783DOI: 10.1007/s00216-007-1475-9ISI: 000249645800024OAI: oai:DiVA.org:su-10783DiVA: diva2:177302
Available from: 2008-01-07 Created: 2008-01-07 Last updated: 2017-12-13Bibliographically approved
In thesis
1. Solving the correspondence problem in analytical chemistry: Automated methods for alignment and quantification of multiple signals
Open this publication in new window or tab >>Solving the correspondence problem in analytical chemistry: Automated methods for alignment and quantification of multiple signals
2012 (English)Doctoral thesis, comprehensive summary (Other academic)
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.

Place, publisher, year, edition, pages
Stockholm: Department of Analytical Chemistry, Stockholm University, 2012. 74 p.
National Category
Chemical Sciences
Research subject
Analytical Chemistry
Identifiers
urn:nbn:se:su:diva-74556 (URN)978-91-7447-485-5 (ISBN)
Public defence
2012-05-25, Magnélisalen, Kemiska övningslaboratoriet, Svante Arrhenius väg 16 B, Stockholm, 13:00 (English)
Opponent
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Available from: 2012-05-03 Created: 2012-03-16 Last updated: 2012-05-02Bibliographically approved

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