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Statistical methods and resources for biomarker discovery using metabolomics

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submitted on 2024-02-21, 07:59 and posted on 2024-02-21, 07:59 authored by Najeha R. Anwardeen, Ilhame Diboun, Younes Mokrab, Asma A. Althani, Mohamed A. Elrayess

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.

Other Information

Published in: BMC Bioinformatics
License: https://creativecommons.org/licenses/by/4.0
See article on publisher's website: https://dx.doi.org/10.1186/s12859-023-05383-0

Funding

Open Access funding provided by the Qatar National Library.

History

Language

  • English

Publisher

Springer Nature

Publication Year

  • 2023

License statement

This Item is licensed under the Creative Commons Attribution 4.0 International License.

Institution affiliated with

  • Qatar University
  • Biomedical Research Center - QU
  • Qatar University Health - QU
  • Sidra Medicine

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