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Updated: Jun 16, 2026

An Integrated Workflow of Identification and Quantification on FDR Control-Based Untargeted Metabolome
Published on: September 20, 2022
Knowledge discovery in metabolomics: an overview of MS data handling
Julien Boccard1, Jean-Luc Veuthey, Serge Rudaz
1School of Pharmaceutical Sciences, University of Geneva, University of Lausanne, Geneva, Switzerland.
Abstract:
While metabolomics attempts to comprehensively analyse the small molecules characterising a biological system, MS has been promoted as the gold standard to study the wide chemical diversity and range of concentrations of the metabolome. On the other hand, extracting the relevant information from the overwhelming amount of data generated by modern analytical platforms has become an important issue for knowledge discovery in this research field. The appropriate treatment of such data is therefore of crucial importance in order, for the data, to provide valuable information. The aim of this review is to provide a broad overview of the methodologies developed to handle and process MS metabolomic data, compare the samples and highlight the relevant metabolites, starting from the raw data to the biomarker discovery. As data handling can be further separated into data processing, data pre-treatment and data analysis, recent advances in each of these steps are detailed separately.
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