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Welcome to scpviz

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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.

Features

  • Set up in 5 minutes

    Install scpviz with pip and get up and running in minutes

    Getting started

  • Quickstart

    Check out the quickstart guide for a run through import, basic preprocessing and quick visualization

    Quickstart

  • In-depth Tutorials

    Step-by-step guides for importing, filtering, plotting, and running enrichment.

    Tutorials

  • API Reference

    Full function documentation for pAnnData and helper utilities.

    API Reference

  • Single-cell proteomics support: Store protein and peptide quantifications in AnnData-compatible structures.
  • Relational mapping: Track protein–peptide connectivity using a dedicated RS matrix.
  • Analysis tools: Filtering, normalization, imputation, and differential expression (DE) tailored for proteomics.
  • Functional enrichment: Integrated STRING queries for GSEA and PPI networks.
  • Custom plotting: Publication-ready plots (abundance, PCA/UMAP, clustermaps, rank-quant plots, etc.).
  • API utilities: Retrieve annotations from UniProt, cache mappings, and manage large datasets efficiently.

Getting Started

Check out the quickstart guide. For more detailed examples, check out the Tutorials.

  • Developer Notes – Guidelines for contributing, testing, and extending scpviz.

Citation

If you use scpviz in your research, please cite:

Pang et al., (2026). scpviz: A Python bioinformatics toolkit for Single-cell Proteomics and multi-omics analysis. Journal of Open Source Software, 11(122), 10303. https://doi.org/10.21105/joss.10303

@article{Pang2026,
  author  = {Pang, Marion and Quan, Baiyi and Wang, Ting-Yu and Chou, Tsui-Fen},
  title   = {scpviz: A Python bioinformatics toolkit for Single-cell Proteomics and multi-omics analysis},
  journal = {Journal of Open Source Software},
  year = {2026},
  month = jun,
  journal = {Journal of Open Source Software},
  volume = {11},
  number = {122},
  pages = {10303},
  issn = {2475-9066},
  doi = {10.21105/joss.10303},

}

scpviz is developed for research in single-cell and spatial proteomics, supporting reproducible and scalable analysis.