Prognostic Biomarkers Identification in Esophageal Cancer Based on WGCNA and Single-Cell Analysis

Figure 3

The WGCNA. (a) The clustering dendrogram of tumor and normal samples to detect outliers. (b) Cluster tree of 15 tumor and 30 normal samples in the GSE75241 dataset. The color band underneath the tree indicates the numeric values of the clinical features. (c) The scale-free fit index for soft-thresholding powers (). The soft-thresholding power in the WGCNA was determined based on a scale-free (). (d) Clustering of module eigengenes. (e) The module-trait relationships between modules and phenotypes. (f) Scatter plot of module eigengenes related to tumor in the black module. (g) Scatter plot of module eigengenes related to tumor in the green module. (h) Scatter plot of module eigengenes related to differentiation in the green module. (i) Scatter plot of module eigengenes related to tumor in the green module.

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