Fig. 6: Application to large field mouse brain hemisphere dataset measured by Stereo-seq.

a The workflow of data acquisition, data processing, and cell type annotation. b Cell type annotation of Spatial-ID for the 3 adjacent sections (Bregma −3.56 to −3.66 mm), and UMAP visualization. c A Voronoi treemap shows the composition of excitatory neurons, inhibitory neurons, and non-neuronal cells among the 3 sections. Every tile denotes one cell type and its size represents cell number. d A Voronoi diagram shows cell type organization among distinct brain regions of the 3 sections. Every tile is colored by its populated ABA functional region and its size represents cell number. e Spatial organization of the cortical pyramidal neurons, i.e., TEGLU2, TEGLU3, TEGLU4, TEGLU6, TEGLU7, TEGLU8, TEGLU10, TEGL11, and TEGLU17 in the Section 3. Cells in the VISp and AUD region are individually presented in the middle panel. The right panel shows the kernel density estimate plots for the corresponding cell types along the normalized cortical depth. f The expression dot plots show the gene expression specificity of typical marker genes for identified cell types. Dot size represents the proportion of expressing cells and color indicates average expression level in each identified cell type. g Spatial distributions of selected marker genes show the number of transcripts captured by Stereo-seq. h The spatial gene patterns consist of type-specific genes (Section 3, visualized with pattern scores). The right panel shows the corresponding identified cell types together with the ABA spatial anatomical functional regions. i–k The spatial gene patterns consist of region-specific genes from diverse identified cell types (Section 3). The corresponding identified cell types are illustrated on the right. l Top three highly enriched GO terms for each spatial gene pattern in (h–k).