sCCIgen: A high-fidelity spatially resolved transcriptomics data simulator for cell-cell interaction studies.

1. Introduction

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.

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.

2. Reference

• Song, X., et al. sCCIgen: A high-fidelity spatially resolved transcriptomics data simulator for cell-cell interaction studies. bioRxiv (2025)

3. Software Instruction

The installation instruction, documentation, tutorials, and examples are accessible at https://songxiaoyu.github.io/sCCIgen/.

4. Brief overview of simulation options

Users have two options to perform SRT simulations using sCCIgen. Depending on preference, Users can choose to use:

• An interactive interface. The interface helps users to choose tasks, data, and parameters, and lets sCCIgen run simulations to provide simulated data, together with parameters and documentations, saved in the working directory. As simulations usually involve many parameters, this option is highly recommended for the first time user or researchers with limited programming expertise.
  • Tutorials for using the interface to simulate SRT.
• R package. A direct use of sCCIgen package offers greater flexibility, allowing users to adjust more parameters that would otherwise be fixed at default values. It also enables the output of simulation byproducts, such as spatial windows. This approach is recommended for users with goode programming experience who wish to perform customized simulations.
  • Tutorials for using the R package to simulate SRT based on snRNAseq data.
  • Tutorials for using the R package to simulate SRT based on single-cell SRT data (single region).
  • Tutorials for using the R package to simulate SRT based on single-cell SRT data (multiple regions).
  • Tutorials for using the R package to simulate SRT based on single-cell expression and unpaired spatial data.