The paper introduces a novel approach called structure-based analysis for processing spatial omics data, focusing on multicellular anatomical arrangements rather than just single cells. This methodology is implemented in sosta, an open-source Bioconductor package designed for the reconstruction, characterization, and comparison of these anatomical structures. The authors demonstrate sosta's utility through two case studies: quantifying structural changes during colorectal malignancy transformation and recovering anatomically relevant gene expression gradients in human tonsil germinal centers. The overall goal is to bridge the gap between classic histopathology and modern spatial transcriptomics by analyzing biologically meaningful, multicellular patterns.
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