Spatial transcriptomics data provide detailed gene expression profile while maintaining spatial resolution.Developing computational methods to integrate the multimodal data to identify intricate hierarchical structures within tissues and elucidate the dynamics and mechanisms of related biological processes is a crucial task in this field.This review comprehensively outlines the computa-tional principles of relevant algorithms,surveys commonly used datasets,and establishes evaluation criteria,emphasizing the strengths,limitations,and applicability of different algorithms.These insights provide a thorough methodological framework for the development of new algorithms,while also highlighting potential avenues for future improvements.
维普
万方数据