| Literature DB >> 30562035 |
Mark D Chaffin, Liu Cao1, Amy A Deik2, Clary B Clish2, Frank B Hu, Miguel A Martínez-González3,4, Cristina Razquin3,4, Monica Bullo4,5, Dolores Corella4,6, Enrique Gómez-Gracia4,7, Miquel Fiol4,8, Ramon Estruch4, José Lapetra4,9, Montserrat Fitó4,10, Fernando Arós4,11, Lluís Serra-Majem4,12, Emilio Ros3, Liming Liang.
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 (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.Entities:
Keywords: measurement artifact; missing pattern; pooled QC sample; untargeted metabolomics
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Year: 2018 PMID： 30562035 PMCID： PMC9018011 DOI： 10.1021/acs.jproteome.8b00893
Source DB: PubMed Journal: J Proteome Res ISSN： 1535-3893 Impact factor: 5.370