Bioinformatic Analysis of Genetic Factors from Human Blood Samples and Postmortem Brains in Parkinson’s Disease

Figure 3

WGCNA analysis of the genes that expressed differentially. (a) The MetaQC software package of R was used to do the PCA analysis for each dataset. (b, c) The Venn diagrams of the four datasets. (d) 1-TOM cluster has been used to create a tree of all gene expressions. (e) Soft Threshold (Power) reflects the weight, while the vertical axis depicts the network’s average connectedness. (f) The weight is represented by Soft Threshold (Power), and the scale-free topology fitting index is shown on the vertical axis. (g) The heat maps of correlations between modules show genes and samples, with correlation coefficients and values in each cell. (h). The heat maps of correlations between modules show genes and samples, grouped into PD and control, with correlation coefficients and values in each cell.

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