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. 2025 Sep 11;16:1630062. doi: 10.3389/fmicb.2025.1630062

Figure 5.

Chart panel illustrates various statistical analyses comparing REP and NEP groups. A: Volcano plot shows log fold change against negative log p-values. B: Venn diagram details metabolite overlap. C: Box plots compare metabolite levels between groups. D: Bar graph highlights feature importance. E: ROC curve displays AUC of 0.875. F: PR curve demonstrates AUC of 0.943. G and H: Permutation tests show AUC and accuracy distributions with p-values.

Metabolite-level classification model for REP and NEP. (A) Volcano plot showing differential metabolite expression between REP and NEP groups. Red and blue points indicate significantly up- or downregulated metabolites, respectively, based on log2 fold change and -Log10 (p-value). (B) Venn diagram highlighting the overlap between significantly altered metabolites (t-test, p < 0.05, fold change > 1.5 or < 2/3) and those with VIP > 1 from PLS-DA. (C) Box plots of six key metabolites with statistical significance (*p < 0.05, **p < 0.01) between groups. (D) Random forest feature importance ranking of selected metabolites. (E) ROC curve (AUC = 0.875) showing model performance in classifying REP vs. NEP. (F) PR curve (AUC = 0.943) illustrating precision-recall characteristics. (G, H) Permutation test results for AUC and accuracy (1,000 iterations), with empirical p-values indicating statistical robustness. CSF, cerebrospinal fluid; NEP, non-epilepsy; REP, refractory epilepsy; PLS-DA, partial least-squares regression discriminant analysis; ROC, receiver operating characteristic; PR, Precision-recall; AUC, area under the ROC curve.