Stereopy: modeling comparative and spatiotemporal cellular heterogeneity via multi-sample spatial transcriptomics
Understanding complex biological systems requires tracing cellular dynamic changes across conditions, time, and space. However, integrating multi-sample data in a unified way to explore cellular heterogeneity remains challenging. Here, we present Stereopy, a flexible framework for modeling and dissecting comparative and spatiotemporal patterns in multi-sample spatial transcriptomics with interactive data visualization. To optimize this framework, we devise a universal container, a scope controller, and an integrative transformer tailored for multi-sample multimodal data storage, management, and processing. Stereopy showcases three representative applications: investigating specific cell communities and genes responsible for pathological changes, detecting spatiotemporal gene patterns by considering spatial and temporal features, and inferring three-dimensional niche-based cell-gene interaction network that bridges intercellular communications and intracellular regulations. Stereopy serves as both a comprehensive bioinformatics toolbox and an extensible framework that empowers researchers with enhanced data interpretation abilities and new perspectives for mining multi-sample spatial transcriptomics data.
Authors
- Lei Cao (ORCID: https://orcid.org/0000-0002-7170-9602)
- Yi Zhao (ORCID: https://orcid.org/0000-0001-6046-8420)
- Fengzhen Chen (ORCID: https://orcid.org/0009-0009-3673-5395)
- Ping Qiu (ORCID: https://orcid.org/0000-0003-4090-5704)
- Nikola Milićević (ORCID: https://orcid.org/0000-0003-4834-6994)
- Longyu Guo
- Lü Qin (ORCID: https://orcid.org/0000-0002-9315-8004)
- Tianyi Xia (ORCID: https://orcid.org/0000-0001-9341-7742)
- Mengyang Xu (ORCID: https://orcid.org/0000-0002-4487-7088)
- Mei Li (ORCID: https://orcid.org/0000-0003-3310-2911)
- Shuangsang Fang (ORCID: https://orcid.org/0000-0002-4126-0074)
- Junhou Hui
- Qiang Kang (ORCID: https://orcid.org/0000-0001-6579-7944)
- Ziqing Deng (ORCID: https://orcid.org/0000-0001-8726-0160)
- Guangyi Fan (ORCID: https://orcid.org/0000-0001-7365-1590)
- Zhiyuan Yuan (ORCID: https://orcid.org/0000-0002-9367-4236)
- Luni Hu
- Leying Wang (ORCID: https://orcid.org/0000-0001-9112-1219)
- Liang Lin (ORCID: https://orcid.org/0000-0001-7374-7234)
- Bojana Josic
- Marija Bezulj
- Ao Chen (ORCID: https://orcid.org/0000-0002-9699-8340)
- Junhua Li (ORCID: https://orcid.org/0000-0001-6784-1873)
- Yuxiang Li (ORCID: https://orcid.org/0000-0002-1575-3692)
- Yao Li (ORCID: https://orcid.org/0000-0002-5248-3249)
- Yong Zhang (ORCID: https://orcid.org/0000-0001-9950-1793)
- Xun Xu (ORCID: https://orcid.org/0000-0002-5338-5173)
- Chao Zhang (ORCID: https://orcid.org/0000-0002-5162-9568)
- Xiaobin Liu (ORCID: https://orcid.org/0000-0001-7091-2660)
- Liwei Tan
- Lidong Guo (ORCID: https://orcid.org/0000-0003-2520-4416)
- Shengkang Li (ORCID: https://orcid.org/0000-0002-6864-5644)
- Vladimir Kovačević (ORCID: https://orcid.org/0000-0002-9843-6261)
- Mengnan Cheng
- Chao Liu
- Zhenbin Wen
- Yumei Li (ORCID: https://orcid.org/0009-0005-0602-9079)
Institutions
- BGI Group (China) (CN)
- Latvian Biomedical Research and Study Centre (LV)
- Fudan University (CN)
- Institute of Computing Technology (CN)
- Beijing Graphene Institute (CN)
- Shanghai Center for Brain Science and Brain-Inspired Technology (CN)
- University of Chinese Academy of Sciences (CN)
- BGI Research (CN)
Publication Details
- Journal
- Nature Communications
- Published
- 2025-04-21
- DOI
- https://doi.org/10.1038/s41467-025-58079-9
- Citations
- 26
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 20.96
Funders
- National Natural Science Foundation of China
- Major Research Plan
- National Key Research and Development Program of China