Institute of Tropical Medicine Antwerp
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Simple data-reduction method for high-resolution LC-MS data in metabolomics

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dc.contributor.author Scheltema, R. A.
dc.contributor.author Decuypere, S.
dc.contributor.author Dujardin, J. C.
dc.contributor.author Watson, D. G.
dc.contributor.author Jansen, R. C.
dc.contributor.author Breitling, R.
dc.date.accessioned 2010-10-27T12:10:59Z
dc.date.available 2010-10-27T12:10:59Z
dc.date.issued 2009
dc.identifier.issn 1757-6180
dc.identifier.doi http://dx.doi.org/10.4155/bio.09.146
dc.identifier.other ITG-P2B
dc.identifier.other ITG-P3A
dc.identifier.other PARAS
dc.identifier.other U-PROTO
dc.identifier.other DOI
dc.identifier.other Abstract
dc.identifier.other UPD26
dc.identifier.uri http://hdl.handle.net/10390/6325
dc.description.abstract Metabolomics LC-MS experiments yield large numbers of peaks, few of which can be identified by database matching. Many of the remaining peaks correspond to derivatives of identified peaks (e.g., isotope peaks, adducts, fragments and multiply charged molecules). In this article, we present a data-reduction approach that automatically identifies these derivative peaks. Results: Using data-driven clustering based on chromatographic peak shape correlation and intensity patterns across biological replicates, derivative peaks can be reliably identified. Using a test data set obtained from Leishmania donovani extracts, we achieved a 60% reduction of the number of peaks. After quality control filtering, almost 80% of the peaks could putatively be identified by database matching. Conclusion: Automated peak filtering substantially speeds up the data-interpretation process. en
dc.language English en
dc.subject Protozoal diseases en
dc.subject Leishmaniasis en
dc.subject Leishmania donovani en
dc.subject Vectors en
dc.subject Sandflies en
dc.subject Metabolomics en
dc.subject Experimental en
dc.subject Clustering en
dc.subject Chromatography en
dc.subject Data processing en
dc.subject Laboratory techniques and procedures en
dc.title Simple data-reduction method for high-resolution LC-MS data in metabolomics en
dc.type Article en
dc.citation.issue 9 en
dc.citation.jtitle Bioanalysis en
dc.citation.volume 1 en
dc.citation.pages 1551-1557 en
dc.citation.jabbreviation Bioanalysis en


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