How does spatial transcriptomics provide insights beyond single-cell RNA-seq?

Spatial transcriptomics retains spatial context lost in dissociated single-cell approaches. Technologies include: imaging-based methods (MERFISH, seqFISH+, FISH-based with multiplexed probes for ~1000 genes) and sequencing-based methods (10x Visium with 55um resolution, Slide-seq, HDST approaching single-cell resolution). Analysis involves image registration, spot/cell deconvolution for multi-cell spots, spatial clustering, identifying spatially variable genes, ligand-receptor interaction inference, and integration with scRNA-seq for cell-type annotation. Insights include tissue architecture, cell-cell communication in native context, and disease-specific microenvironments. Challenges include resolution-throughput tradeoff, depth of detection, and computational methods for spatial statistics. Applications span development, cancer microenvironment, and neuroanatomy.