MacSGP: Mapping Cell-Type-Specific Spatial Gene Programs Uncovers Tissue Architecture and Microenvironment Organization
Introduction
MacSGP is a scalable statistical and computational approach for MApping Cell-type-specific Spatial Gene Programs (SGPs) in spatial transcriptomic (ST) data.
Real data analysis
The code for reproducing the real data analysis results presented in our paper are available on the tutorial website (https://macsgp-tutorial.readthedocs.io/).
- Multiple adult mouse brain datasets from different sources
- Visium kidney cancer dataset
- Multiple human colorectal cancer datasets generated by different technologies
Reference
If you find MacSGP or any of the source code in this repository useful for your work, please cite:
Mapping Cell-Type-Specific Spatial Gene Programs Uncovers Tissue Architecture and Microenvironment Organization.
Yeqin Zeng, Zhiwei Wang, Yuyao Liu, Yuheng Chen, Jiguang Wang, Hao Chen and Can Yang.
Submitted, 2025.
Development
The software is developed and maintained by Yeqin Zeng.
Contact
Please feel free to contact Yeqin Zeng, Zhiwei Wang, or Prof. Can Yang if any inquiries.
1 maintainer
Metadata
1 maintainer
Release files for MacSGP 0.2.0
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
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| macsgp-0.2.0.tar.gz | 27.8 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| macsgp-0.2.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 57.1 kB
Release files / macsgp-0.2.0.tar.gz
| Download URL | macsgp-0.2.0.tar.gz |
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| Size | 27.8 kB |
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| Download URL | macsgp-0.2.0-py3-none-any.whl |
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| Size | 29.3 kB |
| Tags | Python 3 |
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