A categorization of spatial transcriptomics methods for cell-cell communication analysis

Cell-cell communication (CCC) is involved in regulating cellular behavior in tissues. Spatial transcriptomics adds local context to gene expression, enabling more biologically grounded CCC inference than single-cell RNA-seq alone. Rapid method development has yielded diverse CCC methods, each addressing distinct biological questions through varied analytical frameworks. We review 33 recent methods and organize them into three categories: inference of communication networks at cell-type or single-cell resolution, modeling of microenvironment-driven transcriptional variability and regulatory modules, and estimation of spatially informed signaling gene co-associations and higher-order interaction structures. We offer a structured guide for method selection aligned with researchers' analytical goals, highlighting strengths, limitations, and key technical features to support the informed application of CCC inference methods in spatial transcriptomic research.