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. Author manuscript; available in PMC: 2023 Oct 1.
Published in final edited form as: Neuropharmacology. 2023 Jun 15;237:109635. doi: 10.1016/j.neuropharm.2023.109635

Figure 5.

Figure 5.

Principal Component Analysis (PCA) of the behavioral and metabolism data. The cumulative proportion of variance is represented as a bar chart. Proportion of variance explained by each principal component (PC) indicated by the line plot (panel A). Loadings plot showing the contribution of each variable to PC1 and PC2. Each variable is represented by a point and labeled accordingly. The closer a variable’s point is to the axes, the stronger its association with the corresponding PC (panel B). Scatter plot of PC scores for individual rats, with each point representing a rat and colored by strain (panel C). The x-axis corresponds to PC1 scores, and the y-axis corresponds to PC2 scores. The plot illustrates the separation between strains in the two-dimensional space defined by PC1 and PC2.