napari spatialdata
0.5.3
This repository contains a napari plugin for interactively exploring and annotating SpatialData objects. Here you can find the napari-spatialdata documentation. napari-spatialdata is part of the SpatialData ecosystem. To learn more about SpatialData, please see the spatialdata documentation.
You can install napari-spatialdata via pip:
pip install napari-spatialdata[all]
The all command will install the qt bindings PyQt5.
You can find more details on this in the installation instructions.
If you would like to use the plugin as the default zarr reader, in napari please go to File -> Preferences-> Plugins and follow the instructions under File extension readers.
You can install napari-spatialdata from Github with:
pip install git+https://github.com/scverse/napari-spatialdata
Or, you can also install in editable mode after cloning the repo by:
git clone https://github.com/scverse/napari-spatialdatacd napari-spatialdatapip install -e .
Note: when performing an editable install of napari-spatialdata, spatialdata will be reinstalled from pip. So, if you previously also made an editable install of spatialdata, you need to re-run pip install -e . on the spatialdata repository. Please find more details on this in the installation instructions.
To learn how to use the napari-spatialdata plugin, please see the documentation. To learn how to integrate napari-spatialdata into your analysis workflows, please see the SpatialData tutorials. In particular:
Annotating regions of interest with napari
Use landmark annotations to align multiple -omics layers
Contributions are very welcome. Tests can be run with tox, please ensurethe coverage at least stays the same before you submit a pull request.
Distributed under the terms of the BSD-3 license,"napari-spatialdata" is free and open source software
If you encounter any problems, please file an issue along with a detailed description.
Marconato, L., Palla, G., Yamauchi, K.A. et al. SpatialData: an open and universal data framework for spatial omics. Nat Methods (2024). https://doi.org/10.1038/s41592-024-02212-x
