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spatialdata-io: convenient readers for loading common formats into SpatialData

Tests Documentation DOI

This package contains reader functions to load common spatial omics formats into SpatialData. Currently, we provide support for:

  • 10x Genomics Visium®
  • 10x Genomics Visium HD®
  • 10x Genomics Xenium®
  • Akoya PhenoCycler® (formerly CODEX®)
  • Curio Seeker®
  • DBiT-seq
  • MCMICRO (output data)
  • NanoString CosMx®
  • Spatial Genomics GenePS® (seqFISH)
  • Steinbock (output data)
  • STOmics Stereo-seq®
  • Vizgen MERSCOPE® (MERFISH)
  • MACSima® (MACS® iQ View output)

Note: all mentioned technologies are registered trademarks of their respective companies.

Known limitations

Contributions for addressing the below limitations are very welcomed.

  • Only Stereo-seq 7.x is supported, 8.x is not currently supported. #161

How to Contribute

  1. Open a GitHub Issue: Start by opening a new issue or commenting on an existing one in the repository. Clearly describe the problem and your proposed changes to avoid overlapping efforts with others.

  2. Submit a Pull Request (PR): Once the issue is discussed, submit a PR to the spatialdata-io repository. Ensure your PR includes information about a suitable dataset for testing the reader, ideally no larger than 10 GB. Include clear instructions for accessing the data, preferably with a curl or wget command for easy downloading.

  3. Optional Enhancements: To facilitate reproducibility and ease of data access, consider adding a folder in the spatialdata-sandbox repository. Include a download.py and to_zarr.py script (refer to examples in the repository) to enable others to reproduce your reader by simply running these scripts sequentially.

Getting started

Please refer to the documentation. In particular, the

Installation

You need to have Python 3.8 or newer installed on your system. If you don't have Python installed, we recommend installing Miniconda.

There are several alternative options to install spatialdata-io:

  1. Install the latest release of spatialdata-io from PyPI:
pip install spatialdata-io
  1. Install the latest development version:
pip install git+https://github.com/scverse/spatialdata-io.git@main

Contact

For questions and help requests, you can reach out in the scverse discourse. If you found a bug, please use the issue tracker.

Readers from third-party libraries

Technologies that can be read into SpatialData objects using third-party libraries:

Disclaimer

This library is community maintained and is not officially endorsed by the aforementioned spatial technology companies. As such, we cannot offer any warranty of the correctness of the representation. Furthermore, we cannot ensure the correctness of the readers for every data version as the technologies evolve and update their formats. If you find a bug or notice a misrepresentation of the data please report it via our Bug Tracking System so that it can be addressed either by the maintainers of this library or by the community.

Citation

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