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. 2024 May 29;15:1377817. doi: 10.3389/fimmu.2024.1377817

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Copyright © 2024 Xu, Tao and Zhang

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Hub genes selection based on machine learning algorithms. (A) Heatmap displaying the distribution of 50 DEGs. (B) Volcano plot showing expression of DEGs (|logFC|>1 and adjusted P value<0.05) in cluster 1&2 neutrophils. (C) Box plots displaying the expression of the expression of the top 50 genes. (D) Heatmap for correlations between 50 DEGs. (E) Coefficient profile plots showing the shrinkage of gene number. (F) Penalty plot for the LASSO model. (G) The AUC of seven machine learning althogrims. (H) Mean AUC of fivefold cross-validation for 9 replications of each model. (I) Expression difference of ALPL, ACTB, CD177, GAPDH, SLC25A37, S100A8, S100A9, and STXBP2 in GSE57056 between sepsis group and control group. (J) In GSE57056, ROC curve of predicted risk scores of ALPL, ACTB, CD177, GAPDH, SLC25A37, S100A8, S100A9, and STXBP2 in sepsis diagnosis. *, P<0.05.