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MetProc: Separating Measurement Artifacts from True Metabolites in an Untargeted Metabolomics Experiment

AuthorsChaffin, Mark D.; Cao, Liu; Seik, Amy A.; Clish, Clary B.; Hu, Frank B.; Martínez-García, Miguel Ángel; Razquin, Cristina; Bulló, Mònica; Corella, Dolores; Gómez-Gracia, Enrique; Fiol, Miquel; Estruch, Ramón; Lapetra, Jose; Fitó, Montserrat; Arós, Fernando; Serra-Majem, Lluis; Ros, Emilio; Liang, Liming
KeywordsUntargeted metabolomics
Measurement artifact
Missing pattern
Pooled QC sample
Issue Date2019
PublisherAmerican Chemical Society
CitationJournal of Proteome Research 18(3): 1446-1450 (2019)
AbstractHigh-throughput metabolomics using liquid chromatography and mass spectrometry (LC/MS) provides a useful method to identify biomarkers of disease and explore biological systems. However, the majority of metabolic features detected from untargeted metabolomics experiments have unknown ion signatures, making it critical that data should be thoroughly quality controlled to avoid analyzing false signals. Here, we present a postalignment method relying on intermittent pooled study samples to separate genuine metabolic features from potential measurement artifacts. We apply the method to lipid metabolite data from the PREDIMED (PREvención con DIeta MEDi-terránea) study to demonstrate clear removal of measurement artifacts. The method is publicly available as the R package MetProc, available on CRAN under the GPL-v2 license.
Publisher version (URL)http://dx.doi.org/10.1021/acs.jproteome.8b00893
Identifiersdoi: 10.1021/acs.jproteome.8b00893
issn: 1535-3893
e-issn: 1535-3907
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