A package to visualize single cell proteomics (and more to come!) data
Project description
scpviz
CI Matrix Status:
| Python | Ubuntu | macOS | Windows |
|---|---|---|---|
| 3.11 | |||
| 3.10 |
Overview
scpviz is a Python package for single-cell and spatial proteomics data analysis, built around a custom pAnnData object.
It extends the AnnData ecosystem with proteomics-specific functionality, enabling seamless integration of proteins, peptides, and relational data.
- Documentation: https://gnaprs.github.io/scpviz/
- Python Package Index (PyPI): https://pypi.org/project/scpviz/
Getting started
Installation
scpviz requires Python 3.10 or later. It is distributed as a Python package and can be installed with pip.
pip install scpviz
This will install all required dependencies, including scanpy, anndata, pandas, and common plotting libraries.
For single-cell proteomics workflows (directLFQ normalization, Leiden clustering, Harmony batch correction, PIMMS imputation), install the sc extras:
pip install scpviz[sc]
For the most up-to-date development version, clone the repository and install with pip:
git clone https://github.com/gnaprs/scpviz.git
cd scpviz
pip install -e .
Quickstart
Check out the quickstart guide for a run through import, basic preprocessing and quick visualization.
In-depth Tutorials
For more in-depth guides on importing, filtering, plotting, and running enrichment, see the tutorials.
API Reference
Full function documentation for the pAnnData class and utility modules can be found on our documentation page.
Contributing
If you'd like to contribute to scpviz, please see the contributing guidelines and code of conduct. We welcome contributions from the community to help improve, expand, and document the functionality of scpviz.
License
scpviz was created by Marion Pang and contributors. It is licensed under the terms of the MIT license.
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