SRTsim: spatial pattern preserving simulations for spatially resolved transcriptomics

Jiaqiang Zhu

doi:10.1186/s13059-023-02879-z

2023-03-03

Jiaqiang Zhu

Lulu Shang

Xiang Zhou (Xiang Zhou) *

DOI：10.1186/s13059-023-02879-z

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摘要

En 中文

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.

Keyword:

GENE-EXPRESSION

RNA

IDENTIFICATION

TISSUE

CELLS

SEQ

AI总结

对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。

期刊

Genome Biology

IF:

9.4

论文数:

6.4K

被引数:

7.3W

机构

university of michigan system

学者数:

9.1W

论文数: 8.6W

被引数: 133

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