The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index.
A Guideline to Univariate Statistical Analysis for LC/MS-Based Untargeted Metabolomics-Derived Data
Open accessAbstract
Several metabolomic software programs provide methods for peak picking, retention time alignment and quantification of metabolite features in LC/MS-based metabolomics. Statistical analysis, however, is needed in order to discover those features significantly altered between samples. By comparing the retention time and MS/MS data of a model compound to that from the altered feature of interest in the research sample, metabolites can be then unequivocally identified. This paper reports on a comprehensive overview of a workflow for statistical analysis to rank relevant metabolite features that will be selected for further MS/MS experiments. We focus on univariate data analysis applied in parallel on all detected features. Characteristics and challenges of this analysis are discussed and illustrated using four different real LC/MS untargeted metabolomic datasets. We demonstrate the influence of considering or violating mathematical assumptions on which univariate statistical test rely, using high-dimensional LC/MS datasets. Issues in data analysis such as determination of sample size, analytical variation, assumption of normality and homocedasticity, or correction for multiple testing are discussed and illustrated in the context of our four untargeted LC/MS working examples.
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Cited by
Thévenot, E. A., Roux, A., Xu, Y., Ezan, E., & Junot, C. (2015) · Journal of Proteome Research · doi:10.1021/acs.jproteome.5b00354 · Cited by 1,735
Identification of bioactive metabolites using activity metabolomics
Rinschen, M. M., Ivanisevic, J., Giera, M., & Siuzdak, G. (2019) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-019-0108-4 · Cited by 1,008
High-resolution metabolomics of occupational exposure to trichloroethylene
Walker, D. I., Uppal, K., Zhang, L., Vermeulen, R., Smith, M., Hu, W., Purdue, M. P., Tang, X., Reiss, B., Kim, S., et al. (2016) · International Journal of Epidemiology · doi:10.1093/ije/dyw218 · Cited by 107
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Low-dose rapamycin extends lifespan in a mouse model of mtDNA depletion syndrome
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Metadata
- Authors
- Vinaixa, M., Samino, S., Saez, I., Duran, J., Guinovart, J. J., & Yanes, O.
- Venue
- Metabolites
- Publisher
- MDPI AG
- Published
- 2012-10-18
- Volume
- 2
- Issue
- 4
- Pages
- 775-795
- ISSN
- 2218-1989 (ISSN-L)
- OpenAlex
- W2104787245
- Cited by
- 329
- References
- 31
- FWCI
- 3.02
- Type
- journal article
- Language
- en
- Open access
- gold
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- Vinaixa, M., Samino, S., Saez, I., Duran, J., Guinovart, J. J., & Yanes, O. (2012). A Guideline to Univariate Statistical Analysis for LC/MS-Based Untargeted Metabolomics-Derived Data. Metabolites. https://doi.org/10.3390/metabo2040775
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