sCCIgen: a high-fidelity spatially resolved transcriptomics data simulator for cell–cell interaction studies
Xiaoyu Song, Joselyn C. Chavez-Fuentes, Weiping Ma, Weijia Fu, Sujung Crystal Shin, Pei Wang, Guo-Cheng Yuan
TL;DR
sCCIgen is a tool that creates realistic synthetic data for studying how cells interact in tissues using spatial transcriptomics.
Contribution
sCCIgen introduces a high-fidelity simulator for generating spatially resolved transcriptomics data with known cell–cell interaction features.
Findings
sCCIgen preserves transcriptomic and spatial characteristics of real data.
The tool supports various input types, including unpaired expression and spatial data.
It enables reproducible and interactive studies of cell interactions and spatial biology.
Abstract
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.
Genes, proteins, chemicals, diseases, species, mutations and cell lines named across the full text — each resolved to its canonical identifier and authoritative record.
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Taxonomy
TopicsSingle-cell and spatial transcriptomics · Gene Regulatory Network Analysis · Bioinformatics and Genomic Networks