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Installation

scpviz 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.

Optional extras

For single-cell proteomics workflows, install the sc extra to enable directLFQ normalization, Leiden clustering, Harmony batch correction, and imputation:

pip install scpviz[sc]

This adds: directlfq, pimms-learn, harmonypy, leidenalg, igraph, scikit-misc.

Note

The sc extras are required for the Single-cell tutorial. The core installation is sufficient for bulk proteomics workflows described in the Quickstart.

Development installation

To install the latest development version directly from GitHub:

git clone https://github.com/gnaprs/scpviz.git
cd scpviz
pip install -e .

This installs scpviz in editable mode, so any changes to the code will be reflected immediately.

If you would like to contribute to scpviz, please see the Contributing Guide

Dependencies

  • Python ≥ 3.10
  • Core scientific stack: numpy, scipy, pandas
  • Data structures: anndata, scanpy
  • Plotting: matplotlib, seaborn, upsetplot
  • Network and enrichment: requests (for UniProt/STRING API access)

Optional (sc extra): directlfq, pimms-learn, harmonypy, leidenalg, igraph, scikit-misc