期刊
JOURNAL OF PROTEOME RESEARCH
卷 18, 期 3, 页码 1446-1450出版社
AMER CHEMICAL SOC
DOI: 10.1021/acs.jproteome.8b00893
关键词
untargeted metabolomics; measurement artifact; missing pattern; pooled QC sample
资金
- NIH [HL118264]
- official funding agency for biomedical research of the Spanish government, Instituto de Salud Carlos III (ISCIII) [RTIC G03/140, RTIC RD 06/0045]
- Centro de Investigation Biomedica en Red de Fisiopatologia de la Obesidad y Nutricion [CIBEROBN])
- Centro Nacional de Investigaciones Cardiovasculares [CNIC 06/2007]
- Fondo de Investigacion Sanitaria-Fondo Europeo de Desarrollo Regional [PI04-2239, PI 05/2584, CP06/00100, PI07/0240, PI07/1138, PI07/0954, PI 07/0473, P110/01407, PI10/02658, PI11/01647, P11/02505, PI13/00462, PI13/01090]
- Ministerio de Ciencia e Innovacion [AGL-2009-13906-C02, AGL2010-22319-C03]
- Fundacion Mapfre 2010
- Consejeria de Salud de la Junta de Andalucia [PI0105/2007]
- Public Health Division of the Department of Health of the Autonomous Government of Catalonia
- Generalitat Valenciana [ACOMP06109, GVA-COMP2010-181, GVACOMP2011-151, CS2010-AP-111, CS2011-AP-042]
- Regional Government of Navarra [P27/2011]
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.
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