Research Paper Volume 11, Issue 13 pp 4736—4756

Identification of hub genes in prostate cancer using robust rank aggregation and weighted gene co-expression network analysis

Figure 5. Identification of key modules correlated with clinical traits in the TCGA-PRAD dataset through WGCNA. (A) Clustering dendrograms of genes. The clustering was based on the TCGA-PRAD RNA-seq data of robust DEGs from RRA analysis. Color intensity varies positively with age, Gleason score, and pathological stage. In terms of biochemical recurrence, red means recurrence and white indicates no recurrence. (B) Analysis of the scale-free fit index (left) and the mean connectivity (right) for various soft-thresholding powers. (C) Clustering of module eigengenes. The red line indicates cut height (0.25). (D) Dendrogram of all DEGs clustered based on a dissimilarity measure (1-TOM). (E) Heatmap of the correlation between module eigengenes and clinical traits of PCa. Each cell contains the correlation coefficient and P value. (F) Distribution of average gene significance and errors in the modules associated with Gleason score of PCa.