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

Xiaoyu Song1, Joselyn C Chavez-Fuentes2, Weiping Ma2

  • 1Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore, Singapore. song.xiaoyu@duke-nus.edu.sg.

Genome Biology
|October 15, 2025
PubMed
Summary
This summary is machine-generated.

We developed sCCIgen, a simulator for creating realistic synthetic spatially resolved transcriptomics data. This tool aids in studying cell-cell interactions and advancing spatial biology research.

Keywords:
Cell–cell interactionData simulatorSpatially resolved transcriptomics

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Area of Science:

  • Spatial biology
  • Genomics
  • Bioinformatics

Background:

  • Spatially resolved transcriptomics (SRT) enables the study of cellular interactions in tissues.
  • Method development and benchmarking are crucial for advancing SRT analysis.

Purpose of the Study:

  • Introduce sCCIgen, a novel simulator for generating synthetic SRT data.
  • Provide a tool for method development and benchmarking in spatial biology.

Main Methods:

  • sCCIgen utilizes real-world data to generate high-fidelity synthetic SRT data.
  • The simulator preserves transcriptomic and spatial characteristics.
  • It incorporates key interaction features like cell colocalization and gene-gene interactions.

Main Results:

  • sCCIgen generates synthetic SRT data with known interaction features.
  • The simulator supports various input data types, including SRT data, single-cell expression data, and unpaired expression/spatial data.
  • It is interactive, user-friendly, reproducible, and well-documented.

Conclusions:

  • sCCIgen is a valuable tool for studying cellular interactions and spatial biology.
  • The simulator facilitates method development and benchmarking for SRT data analysis.
  • It enhances the understanding of cell-cell communication within tissue contexts.