Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/55042
Title: MetProc: Separating Measurement Artifacts from True Metabolites in an Untargeted Metabolomics Experiment
Authors: Chaffin, Mark D.
Cao, Liu
Deik, Amy A.
Clish, Clary B.
Hu, Frank B.
Martínez-González, Miguel A.
Razquin, Cristina
Bullo, Monica
Corella, Dolores
Gómez-Gracia, Enrique
Fiol, Miquel
Estruch, Ramon
Lapetra, José
Fitó, Montserrat
Arós, Fernando
Serra-Majem, Lluís 
Ros, Emilio
Liang, Liming
UNESCO Clasification: 32 Ciencias médicas
Keywords: Untargeted Metabolomics
Measurement Artifact
Missing Pattern
Pooled Qc Sample
Issue Date: 2019
Publisher: 1535-3893
Journal: Journal of Proteome Research 
Abstract: High-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 (PREvencion con Dleta MEDi-terranea) 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.
URI: http://hdl.handle.net/10553/55042
ISSN: 1535-3893
DOI: 10.1021/acs.jproteome.8b00893
Source: Journal of Proteome Research [ISSN 1535-3893], v. 18(3), p. 1446-1450
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