OmicVerse is the fundamental package for multi omics included bulk ,single cell and spatial RNA-seq analysis with Python. For more information, please read our paper: OmicVerse: a framework for bridging and deepening insights across bulk and single-cell sequencing
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OmicVerse v2 is a unified Python project for modern transcriptomics and multi-omics analysis. It brings together bulk RNA-seq, single-cell, spatial transcriptomics, downstream visualization, model-based analysis, and AI-assisted workflows in one package and documentation system.
Note
OmicVerse v2 is organized as a broader analysis platform rather than a single-method package. In addition to core analysis modules, it now includes agent-style workflows through J.A.R.V.I.S., MCP-based tool serving for AI clients, and a growing documentation/tutorial system under omicverse_guide.
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βββ omicverse # Main Python package
βββ omicverse_guide # Documentation files
βββ omicverse_web # Web Analysis Platform
βββ sample # Some test data
βββ LICENSE
βββ README.mdOmicVerse can be installed via conda or pypi and you need to install pytorch at first. Please refer to the installation tutorial for more detailed installation steps and adaptations for different platforms (Windows, Linux or Mac OS).
You can use conda install omicverse -c conda-forge or pip install -U omicverse for installation.
Please checkout the documentations and tutorials at omicverse page or omicverse.readthedocs.io.
OmicVerse provide an directly interact analysis with OpenClaw project. You can use
omicverse claw 'help me annotate the lung scrna-seq'This module supported by ov.Agent function. And i think that will be convinent for you to analysis the anndata using OpenClaw.
The full tutorial could be found at here
OmicVerse provide an MCP server that exposes registered analysis tools to AI assistants (Claude Code, etc.) via the standard Model Context Protocol.
# Install with MCP dependencies
pip install -e "omicverse[mcp]"
# Start the server (stdio transport)
python -m omicverse.mcp # or: omicverse-mcp
python -m omicverse.mcp --phase P0 # core pipeline tools onlyThe full tutorial could be found at here
If you want to analysis the AnnData using Mobile Phone, maybe you can try
# Install with jarvis dependencies
pip install "omicverse[jarvis]"
# Start to chat with JARVIS using telegram
omicverse jarvis --channel telegram --token "$TELEGRAM_BOT_TOKEN"The full tutorial could be found at here
The omicverse is implemented as an infrastructure based on the following four data structures.
The table contains the tools have been published
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Included Package not published or preprint
- [1] Cellula is to provide a toolkit for the exploration of scRNA-seq. These tools perform common single-cell analysis tasks
- [2] pegasus is a tool for analyzing transcriptomes of millions of single cells. It is a command line tool, a python package and a base for Cloud-based analysis workflows.
- [3] cNMF is an analysis pipeline for inferring gene expression programs from single-cell RNA-Seq (scRNA-Seq) data.
5 Contact
- Zehua Zeng (starlitnightly@gmail.com or zehuazeng@xs.ustb.edu.cn)
- Lei Hu (hulei@westlake.edu.cn)
If you would like to contribute to omicverse, please refer to our developer documentation.
Install the test dependencies and execute the suite with pytest:
pip install -e .[tests]
# or install the pinned latest requirements
pip install -r requirements-latest.txt
pytestThe optional tests extra and the requirements-latest.txt file now include pytest-asyncio>=0.23, which is required for the asynchronous streaming tests under tests/utils/.
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Important
We would like to thank the following WeChat Official Accounts for promoting Omicverse.
7 Citation
If you use omicverse in your work, please cite the omicverse publication as follows:
OmicVerse: a framework for bridging and deepening insights across bulk and single-cell sequencing
Zeng, Z., Ma, Y., Hu, L. et al.
Nature Communication 2024 Jul 16. doi: 10.1038/s41467-024-50194-3.
Here are some other related packages, feel free to reference them if you use them!
CellOntologyMapper: Consensus mapping of cell type annotation
Zeng, Z., Wang, X., Du, H. et al.
imetaomics 2025 Nov 06. doi: 10.1002/imo2.70064.
8 Other
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