Unsupervised clustering identifies seven major cell types in the human retina. a Clustering of 5873 human retina single-nuclei expression profiles into seven populations (right) and representation of the alignment of six datasets from three donors (left). b Profiles of known markers (PDE6A, NETO1, SLC1A3, GAD1, SEPT4, ARR3, RBPMS) in each cluster. c The proportion of the seven cell types (rod, BC, MG, AC, HC, cone, RGC) in the macular and peripheral samples (bar graph shows the mean of the proportion; single data points are visualized in dots, N = 3). d Heatmap of DEGs in each cell type and the gene ontology term enrichment by each set of DEGs. For visualization, top 50 DEGs with least FDR q-value and top five terms under the biological process category with least p-value were used. Each column represents a cell while each row represents a gene. Gene expression values are scaled across all the cells.