Please use this identifier to cite or link to this item: https://doi.org/10.3390/metabo9070145
Title: Metabolomics analytics workflow for epidemiological research: Perspectives from the consortium of metabolomics studies (COMETS)
Authors: Playdon, M.C.
Joshi, A.D.
Tabung, F.K.
Cheng, S.
Henglin, M.
Kim, A.
Lin, T.
van Roekel, E.H.
Huang, J.
Krumsiek, J.
Wang, Y.
Mathé, E.
Temprosa, M.
Moore, S.
Chawes, B.
Eliassen, A.H.
Gsur, A.
Gunter, M.J.
Harada, S.
Langenberg, C.
Oresic, M.
Perng, W.
Seow, W.J. 
Zeleznik, O.A.
Keywords: Analytical methods
Data analysis
Epidemiology
Metabolomics
Pre-processing
Reporting
Statistical analysis
Issue Date: 2019
Publisher: MDPI AG
Citation: Playdon, M.C., Joshi, A.D., Tabung, F.K., Cheng, S., Henglin, M., Kim, A., Lin, T., van Roekel, E.H., Huang, J., Krumsiek, J., Wang, Y., Mathé, E., Temprosa, M., Moore, S., Chawes, B., Eliassen, A.H., Gsur, A., Gunter, M.J., Harada, S., Langenberg, C., Oresic, M., Perng, W., Seow, W.J., Zeleznik, O.A. (2019). Metabolomics analytics workflow for epidemiological research: Perspectives from the consortium of metabolomics studies (COMETS). Metabolites 9 (7) : 145. ScholarBank@NUS Repository. https://doi.org/10.3390/metabo9070145
Rights: Attribution 4.0 International
Abstract: The application of metabolomics technology to epidemiological studies is emerging as a new approach to elucidate disease etiology and for biomarker discovery. However, analysis of metabolomics data is complex and there is an urgent need for the standardization of analysis workflow and reporting of study findings. To inform the development of such guidelines, we conducted a survey of 47 cohort representatives from the Consortium of Metabolomics Studies (COMETS) to gain insights into the current strategies and procedures used for analyzing metabolomics data in epidemiological studies worldwide. The results indicated a variety of applied analytical strategies, from biospecimen and data pre-processing and quality control to statistical analysis and reporting of study findings. These strategies included methods commonly used within the metabolomics community and applied in epidemiological research, as well as novel approaches to pre-processing pipelines and data analysis. To help with these discrepancies, we propose use of open-source initiatives such as the online web-based tool COMETS Analytics, which includes helpful tools to guide analytical workflow and the standardized reporting of findings from metabolomics analyses within epidemiological studies. Ultimately, this will improve the quality of statistical analyses, research findings, and study reproducibility. © 2019 by the authors. Licensee MDPI, Basel, Switzerland.
Source Title: Metabolites
URI: https://scholarbank.nus.edu.sg/handle/10635/212294
ISSN: 22181989
DOI: 10.3390/metabo9070145
Rights: Attribution 4.0 International
Appears in Collections:Staff Publications
Elements

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
10_3390_metabo9070145.pdf2.56 MBAdobe PDF

OPEN

NoneView/Download

SCOPUSTM   
Citations

19
checked on Sep 22, 2022

Page view(s)

57
checked on Sep 22, 2022

Google ScholarTM

Check

Altmetric


This item is licensed under a Creative Commons License Creative Commons