Systematic evaluation with practical guidelines for single-cell and spatially resolved transcriptomics data simulation under multiple scenarios

Data simulation is crucial for developing and benchmarking bioinformatics tools for single-cell RNA sequencing (scRNA-seq) and spatially resolved transcriptomics (SRT). However, choosing a suitable simulation method is challenging without comprehensive assessments. We systematically evaluated 49 simulation methods across 152 reference datasets from 24 platforms, focusing on accuracy, functionality, scalability, and usability. Our findings indicate that SRTsim, scDesign3, ZINB-WaVE, and scDesign2 show the best accuracy. We also found that some scRNA-seq simulators can be adapted for SRT data. This comprehensive benchmark offers practical guidelines for researchers to select the most appropriate simulation tools for their specific needs.

Recommended citation: Duo, H., Li, Y., Lan, Y. et al. (2024). "Systematic evaluation with practical guidelines for single-cell and spatially resolved transcriptomics data simulation under multiple scenarios." Genome Biology. 25:145.
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