6533b7d0fe1ef96bd125b7d4
RESEARCH PRODUCT
MetProc: Separating Measurement Artifacts from True Metabolites in an Untargeted Metabolomics Experiment
Dolores CorellaDolores CorellaLluis Serra-majemLluis Serra-majemRamon EstruchLiu CaoMiguel ÁNgel Martínez-gonzálezMiguel ÁNgel Martínez-gonzálezMiquel FiolJosé LapetraClary B. ClishMònica BullóLiming LiangCristina RazquinCristina RazquinAmy DeikMontserrat FitóFernando ArósMark ChaffinEmilio RosFrank B. HuEnrique Gómez-graciaEnrique Gómez-graciasubject
0301 basic medicinePooled QC sampleComputer scienceComputational biology01 natural sciencesBiochemistryArticle03 medical and health sciencesMetabolomicsTandem Mass SpectrometryMetabolomicsUntargeted metabolomics010401 analytical chemistryGeneral ChemistryPotential measurementMeasurement artifactLipidsPredimed0104 chemical sciencesR package030104 developmental biologyUntargeted metabolomicsMetabolomeArtifactsMETABOLIC FEATURESBiomarkersMissing patternChromatography Liquiddescription
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.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2019-01-01 | Journal of Proteome Research |