Fig. 3

Example subcellular spatial omics data and analysis. A Subcellular spatial omics analysis starts with calling transcripts (or other molecular entities of interest) at their 3D locations from z-stacked images. B Using boundaries drawn by cell segmentation algorithms, the counts are aggregated into single-cell expression profiles, from which cell labels and neighborhood traits are inferred. C Both information can then be used for analyses commonly used for single cell and bulk image and sequencing methods, such as differential expression, clustering, cellular interaction analyses. The tissue sample images in all panels were provided by NanoString Technologies (CosMx platform) [65]