Fig. 1
From: Identification of thyroid cancer biomarkers using WGCNA and machine learning
Integrated genomic analysis revealing key genes and modules in thyroid cancer. A Volcano plot highlighting differentially expressed genes between thyroid cancer and normal tissues. B Sample clustering and outlier detection. C Selection of soft-thresholding power for WGCNA analysis. D Heatmap of module–trait relationships in WGCNA analysis. E Dynamic tree cut for WGCNA module identification. F Correlation of the red module with thyroid cancer traits. G Intersection of differentially expressed genes and genes within the most relevant WGCNA module