The Value of Immune-Related Genes Signature in Osteosarcoma Based on Weighted Gene Co-expression Network Analysis

Figure 3

The samples clustering dendrogram, immune score, stromal score, and the determination of soft-thresholding power analyzed by WGCNA. (a) Sample clustering was performed to detect outlying samples based on immune score and stromal score. The red line indicates the cut-off point for data filtering in the data preprocessing step. (b) Clustering based on incorporating immune scores and stromal scores of expression data from osteosarcomas with clinical data and color intensity is proportional to immune and stromal scores. (c) Analysis of the scale-free fit index for various soft-thresholding powers (). (d) Analysis of the mean connectivity for various soft-thresholding powers. (e) Clustering dendrogram of genes based on a dissimilarity measure (1-TOM). (f) Pink coexpression modules based on immune scores yielded scatter plots of gene significance (GS) versus module membership (MM). The screening conditions were the correlation between genes, and the pink module was more significant than 0.8, and the correlation coefficient between genes and the immune score was greater than 0.5. (g) The DEG PPI network module analysis via Cytoscape software. (h) Heatmap of the association with MES and immune score and stromal score of OS. OS: osteosarcoma; TOM: topological overlap stromal; MES: module eigengenes; PPI: protein-protein interaction; DEGs: differentially expressed genes.

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