NaVis: a virtual microscopy framework for interactive, high-resolution navigation of spatial transcriptomics data

Despite the widespread adoption of spatial transcriptomics (ST), revealing the alignment between transcriptional layers and tissue morphology remains technically demanding, typically requiring proficiency across multiple computational frameworks and thereby limiting accessibility for a substantial fraction of the biomedical community. Here, we introduce NaVis ( https://github.com/Izzilab/NaVis ), a point-and-click virtual microscopy framework that redefines ST analysis as an interactive, image-centric experience. NaVis enables rapid high-resolution inference from low-resolution whole-transcriptome platforms, producing microscopy-like visualizations while preserving transcriptome-wide coverage. It further decomposes histological images into quantitative tissue architecture priors – nuclei-rich regions, fibrillar extracellular matrix, and soft tissue – allowing direct integration of gene expression with local morphology. This unified representation supports analyses of compartment enrichment, boundary concordance, spatial cross-correlation, morphological patterning, histology–expression decoupling, and transcriptome-wide spatial similarity. By coupling transcriptomic and image-derived information within an interactive framework, NaVis shifts ST from static computational workflows to an exploratory modality, broadening its accessibility, conceptual reach and potential for biological discoveries.