Spatial data format.
Project description
SpatialData: an open and universal framework for processing spatial omics data.
SpatialData is a data framework that comprises a FAIR storage format and a collection of python libraries for performant access, alignment, and processing of uni- and multi-modal spatial omics datasets. This repository contains the core spatialdata library. See the links below to learn more about other packages in the SpatialData ecosystem.
- spatialdata-io: load data from common spatial omics technologies into spatialdata.
- spatialdata-plot: Static plotting library for spatialdata.
- napari-spatialdata: napari plugin for interactive exploration and annotation of spatial data.
The spatialdata project uses a consensus based governance model and is fiscally sponsored by NumFOCUS. Consider making a tax-deductible donation to help the project pay for developer time, professional services, travel, workshops, and a variety of other needs.
The spatialdata project also received support by the Chan Zuckerberg Initiative.
- The library is currently under review. We expect there to be changes as the community provides feedback.
- The SpatialData storage format is built on top of the OME-NGFF specification.
Getting started
Please refer to the documentation. In particular:
Another useful resource to get started is the source code of the spatialdata-io package, which shows example of how to read data from common technologies.
Installation
Check out the docs for more complete installation instructions. To get started with the "batteries included" installation, you can install via pip:
pip install "spatialdata[extra]"
Note: if you are using a Mac with an M1/M2 chip, please follow the installation instructions.
Contact
- To get involved in the discussion, or if you need help to get started, you are welcome to join our
scverseZulip chat and our scverse discourse forum. If you found a bug, please use the issue tracker.
Citation
L Marconato*, G Palla*, KA Yamauchi*, I Virshup*, E Heidari, T Treis, M Toth, R Shrestha, H Vöhringer, W Huber, M Gerstung, J Moore, FJ Theis, O Stegle, bioRxiv, 2023. * = equal contribution
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