Bayesian statistics improves biological interpretability of metabolomics data from human cohorts
Christopher R. Brydges, Xiaoyu Che, Walter Ian Lipkin, Oliver Fiehn
The paper applies Bayesian statistics to metabolomics data from human ME/CFS cohorts, revealing more consistent and biologically meaningful metabolic differences compared to frequentist methods.
Metabolites · Aug 31, 2023Peer-reviewedBioinformatics