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Squidpy - Spatial Single Cell Analysis in Python

Squidpy is the scverse toolkit for scalable analysis and visualization of spatial molecular data. It builds on scanpy and anndata, providing streamlined APIs for feature extraction, spatial statistics, and interactive exploration of tissue sections together with microscopy images.

Squidpy overview

Documentation

Head over to the documentation for installation instructions, tutorials, how-to guides, and reference material.

Installation

We recommend running Squidpy on a recent Linux or macOS system with Python ≥3.11, but it also works on Windows via WSL.

Install from PyPI with:

pip install squidpy

or from conda-forge:

conda install -c conda-forge squidpy

Interactive visualization

To get optional dependencies required for the napari-based interactive plotting APIs, install the interactive extra:

pip install 'squidpy[interactive]'

Key capabilities

  • Build and analyze spatial neighbor graphs directly from Visium, Slide-seq, Xenium, and other spatial omics assays.
  • Compute spatial statistics for cell types and genes, including neighborhood enrichment, co-occurrence, and Moran's I.
  • Efficiently store, featurize, and visualize high-resolution tissue microscopy images via scikit-image.
  • Explore annotated datasets interactively with napari and scverse visualization tooling.

Contributing

Contributions are welcome! Please read the contributing guide for instructions on setting up your environment, running tests, and submitting pull requests.

Citation

If you use Squidpy in your research, cite the original publication:

@article{palla:22,
    author = {Palla, Giovanni and Spitzer, Hannah and Klein, Michal and Fischer, David and Schaar, Anna Christina
              and Kuemmerle, Louis Benedikt and Rybakov, Sergei and Ibarra, Ignacio L. and Holmberg, Olle
              and Virshup, Isaac and Lotfollahi, Mohammad and Richter, Sabrina and Theis, Fabian J.},
    title = {Squidpy: a scalable framework for spatial omics analysis},
    journal = {Nature Methods},
    year = {2022},
    month = {Feb},
    volume = {19},
    number = {2},
    pages = {171--178},
    issn = {1548-7105},
    doi = {10.1038/s41592-021-01358-2},
}

Squidpy is part of the scverse® project (website, governance) and is fiscally sponsored by NumFOCUS. Please consider making a tax-deductible donation to help the project pay for developer time, professional services, travel, workshops, and a variety of other needs.

Project links

Data verified by PyPI on Dec 6, 2025
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Key dates

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  • Released:
Newer release available (1.8.3)

Owner

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1 maintainer

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Credits

Author: scverse

Maintainer: Tim Treis

GitHub Statistics

Data verified by PyPI on Dec 6, 2025
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License expression

BSD-3-Clause
View SPDX License List

Requires

Python >=3.11

Provides Extra

dev docs test

Tags

bio-informatics image analysis single-cell spatial data analysis spatial transcriptomics

Classifiers

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