Statistical Methods and Resources for Biomarker Discovery Using Metabolomics

Overview

Journal BMC Bioinformatics

Publisher Biomed Central

Specialty Biology

Date 2023 Jun 15

PMID 37322419

Authors

Najeha R Anwardeen

Ilhame Diboun

Younes Mokrab

Asma A Althani

Mohamed A Elrayess

Affiliations

Soon will be listed here.

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.

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