Computational Approaches for Spatial Omics

Mapping the spatial organization of cells and their communication within tissues is crucial for gaining insights into the processes of development and disease formation. Recent advent of spatial omics technologies has empowered researchers to detect biological molecules in their native location within a tissue. Spatial transcriptomics (ST), for example, measure genome-wide mRNA expression across thousands of spots (containing up to 10 cells) on a tissue slice while preserving information about the location of spots and allowing characterization of the microenvironment. Emerging multi-omic spatial technologies further integrate transcriptome-wide gene expression and multiplexed surface protein expression with histology images from the same formalin-fixed, paraffin-embedded tissue section. Given the nascency of such high-throughput spatially omics technologies, new computational methods for analyzing the resulting data are still actively being developed.