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SRTsim: spatial pattern preserving simulations for spatially resolved transcriptomics.

ABSTRACT: Spatially resolved transcriptomics (SRT)-specific computational methods are often developed, tested, validated, and evaluated in silico using simulated data. Unfortunately, existing simulated SRT data are often poorly documented, hard to reproduce, or unrealistic. Single-cell simulators are not directly applicable for SRT simulation as they cannot incorporate spatial information. We present SRTsim, an SRT-specific simulator for scalable, reproducible, and realistic SRT simulations. SRTsim not only maintains various expression characteristics of SRT data but also preserves spatial patterns. We illustrate the benefits of SRTsim in benchmarking methods for spatial clustering, spatial expression pattern detection, and cell-cell communication identification.

SUBMITTER: Zhu J

PROVIDER: S-EPMC9983268 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature

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SRTsim: spatial pattern preserving simulations for spatially resolved transcriptomics.

Zhu Jiaqiang J Shang Lulu L Zhou Xiang X

Genome biology 20230303 1

Spatially resolved transcriptomics (SRT)-specific computational methods are often developed, tested, validated, and evaluated in silico using simulated data. Unfortunately, existing simulated SRT data are often poorly documented, hard to reproduce, or unrealistic. Single-cell simulators are not directly applicable for SRT simulation as they cannot incorporate spatial information. We present SRTsim, an SRT-specific simulator for scalable, reproducible, and realistic SRT simulations. SRTsim not on ...[more]

PMID: 36869394

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