Fig. 5: ResST works well on various spatial omics data. | Communications Biology

Fig. 5: ResST works well on various spatial omics data.

From: A graph self-supervised residual learning framework for domain identification and data integration of spatial transcriptomics

Fig. 5

a Visualization of subcellular molecular maps using 4i (Iterative Indirect Immunofluorescence Imaging) (top; partial data, coordinates (x1, y1)–(x2, y2): (1100, 950)–(1300, 1150) and spatial domain detection using ResST (bottom). b Visualization of imaging-based molecular MIBI-TOF dataset (3309 pixels and 36 proteins) with annotation (top, the point16 section) and spatial domain detection using ResST (right, ARI = 0.524). c Visualization and annotation of SlideqV2 data in the mouse hippocampus (left); spatial domain detection using ResST (middle); distribution of gene Tmsb4x expression in the data. d Visualization and annotation of MERFISH data in the mouse prefrontal hypothalamus (top) and spatial domain detection using ResST (bottom). e Visualization and annotation of adult Macaque cortex Stereoseq data (leftmost); spatial domain partition using ResST (left middle); expression distribution of the marker genes GFAP, GPR83, and SYT6 in tissue sections of the cortex (right). f Visualization and annotation of seqFISH data in sagittal slices of mouse embryos (left); spatial domain partition using ResST (right).

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