Spatial organization plays a fundamental role in shaping cellular function, differentiation, and tissue development, and its disruption is frequently associated with pathological conditions, including cancer. Gaining insight into how cells are arranged within tissues can therefore provide important insights into the biological mechanisms driving disease. Although single-cell sequencing technologies have significantly improved our ability to characterize cellular molecular states, they generally lack spatial context, limiting the study of cell–cell interactions and tissue architecture. Spatial omics technologies address this limitation by preserving positional information, and recent advances in spatial multi-omics now enable the simultaneous profiling of multiple molecular layers, such as transcriptomics, proteomics, and epigenomics, within the same tissue section. This multimodal perspective offers complementary aspects of cellular functions, regulatory mechanisms, and spatial heterogeneity. Despite their transformative potential for improved characterization of tissue biology, disease mechanisms, and cellular microenvironments, important challenges remain in the analysis and integration of spatial omics data. This special session aims to bring together researchers developing computational and methodological solutions for spatial omics analysis and integration, encouraging discussion on novel approaches and frameworks, analysis strategies, and promising future research directions.