Statistical methods and resources for biomarker discovery using metabolomics.
Author | Anwardeen, Najeha R |
Author | Diboun, Ilhame |
Author | Mokrab, Younes |
Author | Althani, Asma A |
Author | Elrayess, Mohamed A |
Available date | 2023-06-25T05:08:22Z |
Publication Date | 2023-06-15 |
Publication Name | BMC Bioinformatics |
Identifier | http://dx.doi.org/10.1186/s12859-023-05383-0 |
Citation | Anwardeen, N.R., Diboun, I., Mokrab, Y. et al. Statistical methods and resources for biomarker discovery using metabolomics. BMC Bioinformatics 24, 250 (2023). https://doi.org/10.1186/s12859-023-05383-0 |
Abstract | Metabolomics is a dynamic tool for elucidating biochemical changes in human health and disease. Metabolic profiles provide a close insight into physiological states and are highly volatile to genetic and environmental perturbations. Variation in metabolic profiles can inform mechanisms of pathology, providing potential biomarkers for diagnosis and assessment of the risk of contracting a disease. With the advancement of high-throughput technologies, large-scale metabolomics data sources have become abundant. As such, careful statistical analysis of intricate metabolomics data is essential for deriving relevant and robust results that can be deployed in real-life clinical settings. Multiple tools have been developed for both data analysis and interpretations. In this review, we survey statistical approaches and corresponding statistical tools that are available for discovery of biomarkers using metabolomics. |
Sponsor | Open Access funding provided by the Qatar National Library. This research was funded by the Qatar National Research Fund (QNRF), grant number NPRP13S-1230-190008. |
Language | en |
Publisher | BMC |
Subject | Analytical workflow Metabolomics Metabolomics tools Multivariate Statistical methods Univariate |
Type | Article Review |
Issue Number | 1 |
Volume Number | 24 |
ESSN | 1471-2105 |
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