How to Screen Differential Metabolites for Experimental Validation in Untargeted Metabolomics
Differential metabolites in untargeted metabolomics can be screened through the following approaches:
1. Statistical Analysis
(1) The t-test and analysis of variance (ANOVA) are applied for comparisons between two groups and among multiple groups, respectively.
(2) Multivariate analyses, such as Principal Component Analysis (PCA) and Partial Least Squares Discriminant Analysis (PLS-DA), are used to identify key metabolites that contribute to the separation between groups.
2. Threshold Setting
(1) A threshold for the fold change (e.g., >1.5 or >2) is established based on the observed effect size or biological relevance.
(2) A significance threshold for the P-value is set, commonly <0.05 or more stringent, such as <0.01.
3. Correction for Multiple Hypothesis Testing
Given the issue of multiple comparisons, statistical corrections such as the Bonferroni adjustment or control of the False Discovery Rate (FDR) are applied to adjust P-values accordingly.
4. Metabolic Pathway Enrichment Analysis
Tools such as MetaboAnalyst are employed to identify significantly enriched metabolic pathways, facilitating the selection of differential metabolites with greater biological relevance.
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