sCCIgen generates synthetic spatially resolved transcriptomics data for studying cell–cell interactions, supporting comprehensive analysis of gene expression.
Spatially resolved transcriptomics (SRT) facilitates the study of cell–cell interactions within native tissue environments. To support method development and benchmarking, we introduce sCCIgen, a real-data-based simulator that generates high-fidelity synthetic SRT data with known interaction features. sCCIgen preserves transcriptomic and spatial characteristics and provides key interaction features, including cell colocalization, spatial dependence of gene expression, and gene–gene interactions between neighboring cells. It supports input from SRT data, single-cell expression data alone, and unpaired expression and spatial data. sCCIgen is interactive, user-friendly, reproducible, and well-documented for studying cellular interactions and spatial biology.
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Song et al. (2025) studied this question.
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