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. 2024 May 30;16:1352681. doi: 10.3389/fnagi.2024.1352681

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Copyright © 2024 Zhang, Wang, Su, Yang, Wang and Li.

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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Mining of network modules using WGCNA. The main method involved was Pearson correlation analysis. (A) Heatmap of the network for all genes; (B) Heatmap showing the correlation between module eigengenes and risk traits; (C) Correlation and significance of the red module with the low-risk group of Glioma patients; (D,E) GO and KEGG analysis of genes in the red module; (F) Correlation and significance of the magenta module with the high-risk group of Glioma patients; (G,H) GO and KEGG analysis of genes in the magenta module.