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Squidpy - Spatial Single Cell Analysis in Python

Squidpy is a tool for the analysis and visualization of spatial molecular data. It builds on top of scanpy and anndata, from which it inherits modularity and scalability. It provides analysis tools that leverages the spatial coordinates of the data, as well as tissue images if available.

Visit our documentation_ for installation, tutorials, examples and more.

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.

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Manuscript

Please see our manuscript Palla, Spitzer et al. (2022)_ in Nature Methods to learn more.

Squidpy's key applications

• Build and analyze the neighborhood graph from spatial coordinates.
• Compute spatial statistics for cell-types and genes.
• Efficiently store, analyze and visualize large tissue images, leveraging skimage_.
• Interactively explore anndata and large tissue images in napari.

Installation

Install Squidpy via PyPI by running::

pip install squidpy
# or with napari included
pip install 'squidpy[interactive]'

or via Conda as::

conda install -c conda-forge squidpy

Contributing to Squidpy

We are happy about any contributions! Before you start, check out our contributing guide <CONTRIBUTING.rst>_.

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.. _Palla, Spitzer et al. (2022): https://doi.org/10.1038/s41592-021-01358-2 .. _scanpy: https://scanpy.readthedocs.io/en/stable/ .. _anndata: https://anndata.readthedocs.io/en/stable/ .. _napari: https://napari.org/ .. _skimage: https://scikit-image.org/ .. _documentation: https://squidpy.readthedocs.io/en/stable/ .. _website: https://scverse.org/ .. _governance: https://scverse.org/about/roles/ .. _NumFOCUS: https://numfocus.org/ .. _donation: https://numfocus.org/donate-to-scverse/