Annotation of APCs in skin from patients with AD or PSO. (a) Left: Gating strategy starting from CD45⁺HLA-DR⁺CD3⁻CD19⁻ defining all skin subsets of nonlesional and lesional skin of AD (n = 2) and PSO (n = 2) patients. Right: Annotation from indexed data were overlaid on RNA-based UMAP dimensional reduction. (b) Surface protein expression from indexed data were overlaid on RNA-based UMAP dimensional reduction. (c) GSEA of pairwise comparisons of CD1c⁺CD14⁺ cells with CD1c⁺ cells or CD14⁺ cells from skin. Gene signatures of blood DC3s compared with DC2s (DC3 > DC2) or CD14⁺ monocytes (DC3 > Mono) and, vice versa, of blood DC2s (DC2 > DC3) or CD14⁺ monocytes (Mono > DC3) compared with DC3s were used (Villani et al., 2017). NES, normalized enrichment score. (d) The heat map showing relative expression of the DEGs from each KNN cluster. (e) UMAP dimensionality reduction and KNN clustering of human skin APCs based on RNA expression data. Cell subsets were delineated using the 10 KNN clusters that were regrouped into major previously defined cell subsets based on the expression of surface proteins. (f) Heat map of the mean fluorescence intensity (MFI) of the surface proteins in each cluster. (g) Differentially active regulons among RNA-based KNN clusters. (h) Regulon activities of top regulons were projected on the RNA-based UMAP space and shown as violin plots across the KNN clusters. MAC, macrophage.