Fig. 3 | Scientific Reports

Fig. 3

From: Identifying propionate metabolism-related genes as biomarkers of sepsis development and therapeutic targets

Fig. 3

Establishing the machine learning prediction model. (A) and (B) The distribution of the training set and the testing set before and after batch effect elimination. (C) LASSO coefficient path diagram for risk factors. (D) Cross-validation curves. (E) 13 hub genes identified after LASSO regression analysis. (F) Immune infiltration analysis of propionate metabolism PCs. The AUC of the CatBoost model in the testing (G) and validation set (H). (I) The top 6 hub genes selected according to the CatBoost model. P < 0.05; **, P < 0.01; ***, P < 0.001. P < 0.05 was considered statistically significant. area under the curve, AUC.

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