Song, X.; Chavez-Fuentes, J. C.; Ma, W.; Fu, W.; Wang, P.; Yuan, G.-C.

Spatially resolved transcriptomics (SRT) provides an invaluable avenue for examining cell-cell interactions within native tissue environments. The development and evaluation of analytical tools for SRT data necessitate tools for generating synthetic datasets with known ground truth of cell-cell interaction induced features. To address this gap, we introduce sCCIgen, a novel real-data-based simulator tailored to generate high-fidelity SRT data with a focus on cell-cell interactions. sCCIgen preserves transcriptomic and spatial characteristics in SRT data, while comprehensively models various cell-cell interaction features, including cell colocalization, spatial dependence among gene expressions, and gene-gene interactions between nearby cells. We implemented sCCIgen as an interactive, easy-to-use, realistic, reproducible, and well-documented tool for studying cellular interactions and spatial biology.