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Fig. 3 | Genome Biology

Fig. 3

From: Giotto: a toolbox for integrative analysis and visualization of spatial expression data

Fig. 3

Cell-type enrichment analysis on spatial expression data. a Schematic of cell-type enrichment analysis pipeline. The inputs are spatial expression data and cell-type-specific gene signatures. These two sources of information are integrated to infer cell type enrichment scores. Giotto implements three methods for enrichment analysis: PAGE, RANK, and Hypergeometric. b Single-cell resolution seqFISH+ data are used to simulate coarse-resolution spatial transcriptomic data generated from spot-like squares by projecting onto a regular spatial grid (500 × 500 pixels). Colored squares indicate those that contain cells. External scRNAseq data are visualized by UMAP. c Comparison of cell-type enrichment scores (left, inferred by PAGE) and observed frequency of various cell types (right, based on seqFISH+ data). The agreement between the two is quantified by area under curve (AUC) scores (green circles). d Cell type enrichment analysis for the mouse Visium brain dataset (distance unit = 1 pixel, 1 pixel ≈ 1.46 μm). Enrichment scores for selected cell types are displayed (top left) and compared with the expression level of known marker genes (bottom left). For comparison, a snapshot of the anatomic structure image obtained from mouse Allen Brain Atlas is displayed. Known locations for the selected cell types are highlighted

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