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Figure 1

From: Elucidating Microglial Heterogeneity and Functions in Alzheimer’s Disease Using Single-cell Analysis and Convolutional Neural Network Disease Model Construction

Figure 1

AD-associated subclusters of microglia from scRNA-seq data. (A) Workflow of the experiment. (B–D) UMAP plot illustrates cell clusters identified from the entire dataset. (E, F), Identification of microglia subclusters in AD and HC. (G–I), Plot of pseudotime analysis of microglia. (J), Plot of cell communication between microglia and other cells. AD, Alzheimer's Disease; scRNA-seq, single-cell RNA sequencing; HC, healthy control; WGCNA, Weighted Gene Co-expression Network Analysis; LASSO, the least absolute shrinkage and selection operator; NMF, Non-negative Matrix Factorization; CNN, Convolutional Neural Network; UMAP, Uniform Manifold Approximation and Projection.

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