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.

Manuscript¶

Please see our preprint on bioRxiv to learn more.

Latest additions¶

1.1.0 2021-07-01¶

This release includes:

Additions

Add many new tutorials and examples
Add squidpy.gr.sepal() [Anderson and Lundeberg, 2021] PR 313.
Replace squidpy.gr.moran with squidpy.gr.spatial_autocorr(), which implements both Moran’s I and Geary’s C PR 317.
Add option to compute graph from Delaunay triangulation in squidpy.gr.spatial_neighbors() PR 322.
Add lazy computation using dask for squidpy.im PR 324.
Allow Z-dimension shared across all layers in squidpy.im.ImageContainer PR 329.
Replace squidpy.gr.ripley_k with squidpy.gr.ripley() PR 331
Generalize graph building in squidpy.gr.spatial_neighbors() PR 340.
Add 3 new example datasets PR 348:
Enable additional layer specification in squidpy.im.calculate_image_features() PR 354.
Expose canvas_only in squidpy.pl.Interactive.screenshot() PR 363.
Various minor improvements to the documentation PR 356, PR 358, PR 359.

Bugfixes

Fix squidpy.im.ImageContainer to work with different scaled PR 320
Fix handling of anndata.AnnData.obsm in squidpy.im.ImageContainer.interactive() PR 335.
Fix Z-dimension in squidpy.im.ImageContainer.interactive() PR 351.
Fix plotting bug in squidpy.pl.ripley() PR 352.
Fix handling of NaNs in squidpy.gr.ligrec() PR 362.

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.
Explore anndata and the large tissue image in napari.

Contributing to Squidpy¶

We are happy about any contributions! Before you start, check out our contributing guide.