Welcome to the official GitHub organization for the Spatial Atlas of Human Anatomy (SAHA), a multimodal reference of human tissues at subcellular resolution. We develop and release high-resolution spatial omics datasets, computational tools, and benchmarks to enable tissue-scale systems biology and clinical translation.
The SAHA project brings together spatial transcriptomics, proteomics, histology, and AI-based computational methods to chart the healthy and diseased human body in unprecedented detail.
- Subcellular-resolution spatial profiling across gastrointestinal and immune tissues
- Multi-modal datasets: CosMx SMI, MERFISH, spatial proteomics, histology, and clinical metadata
- Applications in cancer, inflammation, and tissue microenvironment modeling
- Open science collaboration across institutions
** currently waiting for a manuscript acceptance for a full release, but want you can access today: **
For project overviews, interactive figures, and publications, visit our site: https://saha-project.org.
All datasets are available through our website or directly via Zenodo
Here are some of our primary repositories:
saha– manuscript figures, data loaders, and core workflowssaha-maxfuse– multimodal integration of CosMx and histologysaha-scimap– spatial data analysis and visualization tools
For a full list, browse the organization repositories.
Our work is available as a preprint:
The Spatial Atlas of Human Anatomy (SAHA)
bioRxiv, 2025. In peer review.
Stay tuned for updates when the manuscript is accepted.
We welcome collaborators in spatial biology, machine learning, clinical research, and bioinformatics. If you're interested in contributing or proposing a collaboration:
Contact us via the website
File issues or pull requests in relevant repositories
Code in SAHA repositories is generally licensed under the MIT License, and data under CC BY 4.0. Controlled-tier data require a signed Data Use Agreement. Check individual repositories for specifics.
Maintained by the SAHA Consortium.