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AuthorAnwardeen, Najeha R
AuthorDiboun, Ilhame
AuthorMokrab, Younes
AuthorAlthani, Asma A
AuthorElrayess, Mohamed A
Available date2023-06-25T05:08:22Z
Publication Date2023-06-15
Publication NameBMC Bioinformatics
Identifierhttp://dx.doi.org/10.1186/s12859-023-05383-0
CitationAnwardeen, 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
URIhttp://hdl.handle.net/10576/44691
AbstractMetabolomics 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.
SponsorOpen Access funding provided by the Qatar National Library. This research was funded by the Qatar National Research Fund (QNRF), grant number NPRP13S-1230-190008.
Languageen
PublisherBMC
SubjectAnalytical workflow
Metabolomics
Metabolomics tools
Multivariate
Statistical methods
Univariate
TitleStatistical methods and resources for biomarker discovery using metabolomics.
TypeArticle Review
Issue Number1
Volume Number24
ESSN1471-2105
dc.accessType Open Access


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