ArticleMetabolites2021
Separation of Chromatographic Co-Eluted Compounds by Clustering and by Functional Data Analysis.
Article in Metabolites, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Development and Validation of RP-HPLC Method forACS omega · 2025Article
- Metabolomic profile and bioactivity of fungal endophytes isolated from Crinum macowanii.BMC complementary medicine and therapies · 2025Article
- Volatile Distribution in Flowers ofPlants (Basel, Switzerland) · 2024Article
- Analysis of Azathioprine Metabolites in Autoimmune Hepatitis Patient Blood-Method Development and Validation.International journal of molecular sciences · 2024Article
- Identification of Xanthine Oxidase Inhibitors from Celery Seeds Using Affinity Ultrafiltration-Liquid Chromatography-Mass Spectrometry.Molecules (Basel, Switzerland) · 2023Article
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Authors and funding
4 authors.
Funding
Abstract
Peak overlapping is a common problem in chromatography, mainly in the case of complex biological mixtures, i.e., metabolites. Due to the existence of the phenomenon of co-elution of different compounds with similar chromatographic properties, peak separation becomes challenging. In this paper, two computational methods of separating peaks, applied, for the first time, to large chromatographic datasets, are described, compared, and experimentally validated. The methods lead from raw observations to data that can form inputs for statistical analysis. First, in both methods, data are normalized by the mass of sample, the baseline is removed, retention time alignment is conducted, and detection of peaks is performed. Then, in the first method, clustering is used to separate overlapping peaks, whereas in the second method, functional principal component analysis (FPCA) is applied for the same purpose. Simulated data and experimental results are used as examples to present both methods and to compare them. Real data were obtained in a study of metabolomic changes in barley (
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