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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.

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.

Project links

Key dates

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Data sourced directly from PyPI's database.
  • Released:
Newer release available (1.8.3)

Owner

PyPI data
Data sourced directly from PyPI's database.

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for wmv1992 from gravatar.com wmv1992

Credits

Author: Giovanni Palla, Michal Klein, Hannah Spitzer

Maintainer: Giovanni Palla

License

BSD License (BSD 3-Clause License Copyright (c) 2021, Theis Lab All rights reserved. Redistribution and use in ...)

Requires

Python >=3.9

Tags

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

Classifiers

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