Figure 2.

Identification of the key module by WGCNA. (a) Clustering dendrogram of ccRCC samples and heatmap of clinical traits. The clustering was based on the expression data of robust DEGs. The color intensity in heatmap increased with age, pathological stage and grade. In terms of survival status, white means alive and red means dead. (b) Analysis of the scale-free fit index (left) and the mean connectivity (right) for various soft-thresholding power value. (c) Clustering of module eigengenes. The red line indicates cut height = 0.20. (d) Dendrogram of all DEGs clustered based on a dissimilarity measure (1-TOM) together with assigned module colors. (e) Heatmap of the correlation between module eigengenes and clinical traits of ccRCC. Each cell contains the Pearson correlation coefficient and P value. (f) Distribution of average gene significance and errors in the modules associated with survival status of ccRCC

ccRCC, clear cell renal cell carcinoma; DEGs, differentially expressed genes; TOM, topological overlap matrix; WGCNA, Weighted Gene Co-expression Network Analysis.