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A package to visualize single cell proteomics (and more to come!) data

Project description

scpviz

DOI

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CI Matrix Status:

Python Ubuntu macOS Windows
3.11 Ubuntu-3.11 macOS-3.11 Windows-3.11
3.10 Ubuntu-3.10 macOS-3.10 Windows-3.10

Documentation:
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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.

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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