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Spatial omics datasets

Here you can find all datasets necessary to run the example notebooks already converted to the ZARR file format.

If you want to convert additional datasets check out the scripts available in the spatialdata sandbox.

:::{note} S3 URLs cannot be opened directly in a web browser. They should be treated as Zarr stores. For example, appending .zgroup to any of the URLs will allow you to see that file. :::

Technology Sample File Size Filename (spatialdata-sandbox) download data work with data remotely (see note below) license
Visium HD Mouse intestin 1 1 GB visium_hd_3.0.0_id .zarr.zip S3 CCA
Visium Breast cancer 2 1.5 GB visium_associated_xenium_io .zarr.zip S3 CCA
Xenium Breast cancer 2 2.8 GB xenium_rep1_io .zarr.zip S3 CCA
Xenium Breast cancer 2 3.7 GB xenium_rep2_io .zarr.zip S3 CCA
CyCIF (MCMICRO output) Small lung adenocarcinoma 3 250 MB mcmicro_io .zarr.zip S3 CC BY-NC 4.0 DEED
MERFISH Mouse brain 4 50 MB merfish .zarr.zip S3 CC0 1.0 DEED
MIBI-TOF Colorectal carcinoma 5 25 MB mibitof .zarr.zip S3 CC BY 4.0 DEED
Imaging Mass Cytometry (Steinbock output) 4 different cancers (SCCHN, BCC, NSCLC, CRC) 678 820 MB steinbock_io .zarr.zip S3 CC BY 4.0 DEED
Molecular Cartography (SPArrOW output) Mouse Liver 910 70 MB MouseLiver .zarr.zip S3 CC BY 4.0 DEED
SpaceM T cells 11 116 MB spacem_scseahorse1 .zarr.zip NA CC BY 4.0 DEED
SpaceM Hepa and NIH3T3 cells 12 59 MB spacem_hepanih3t3 .zarr.zip .zarr.zip CC BY 4.0 DEED

For the first 3 datasets, we also provide a version of them in which they are all aligned in a common coordinate system, and where we added the cell-type information, as described in our paper, to annotate the Xenium cells.

Technology Sample File Size Filename (spatialdata-sandbox) download data work with data remotely (see note below) license
Visium Breast Cancer 2 1.5 GB visium_associated_xenium_io .zarr.zip S3 CCA
Xenium Breast Cancer 2 2.8 GB xenium_rep1_io .zarr.zip S3 CCA
Xenium Breast Cancer 2 3.7 GB xenium_rep2_io .zarr.zip S3 CCA

Licenses abbreviations

  • CCA: Creative Common Attribution
  • CC0 1.0 DEED: CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
  • CC BY 4.0 DEED: Creative Common Attribution 4.0 International
  • CC BY-NC 4.0 DEED: Creative Common Attribution-NonCommercial 4.0 International

The data retains the license of the original published data.

Artificial datasets

Also, here you can find additional datasets and resources for methods developers.

References

If you use the datasets please cite the original sources and double-check their license.

Footnotes

  1. From https://www.10xgenomics.com/datasets/visium-hd-cytassist-gene-expression-libraries-of-mouse-intestine ↩

  2. Janesick, A. et al. High resolution mapping of the breast cancer tumor microenvironment using integrated single cell, spatial and in situ analysis of FFPE tissue. bioRxiv 2022.10.06.510405 (2022) doi:10.1101/2022.10.06.510405. ↩ ↩2 ↩3 ↩4 ↩5 ↩6

  3. Schapiro, D. et al. MCMICRO: A scalable, modular image-processing pipeline for multiplexed tissue imaging. Cold Spring Harbor Laboratory 2021.03.15.435473 (2021) doi:10.1101/2021.03.15.435473. ↩

  4. Moffitt, J. R. et al. Molecular, spatial, and functional single-cell profiling of the hypothalamic preoptic region. Science 362, (2018). ↩

  5. Hartmann, F. J. et al. Single-cell metabolic profiling of human cytotoxic T cells. Nat. Biotechnol. (2020) doi:10.1038/s41587-020-0651-8. ↩

  6. Windhager, J., Bodenmiller, B. & Eling, N. An end-to-end workflow for multiplexed image processing and analysis. bioRxiv 2021.11.12.468357 (2021) doi:10.1101/2021.11.12.468357. ↩

  7. Eling, N. & Windhager, J. Example imaging mass cytometry raw data. (2022). doi:10.5281/zenodo.5949116. ↩

  8. Eling, N. & Windhager, J. steinbock results of IMC example data. (2022). doi:10.5281/zenodo.7412972. ↩

  9. Guilliams, Martin, et al. "Spatial proteogenomics reveals distinct and evolutionarily conserved hepatic macrophage niches." Cell 185.2 (2022) doi:10.1016/j.cell2021.12.018 ↩

  10. Pollaris, Lotte, et al. "SPArrOW: a flexible, interactive and scalable pipeline for spatial transcriptomics analysis." bioRxiv (2024) doi:10.1101/2024.07.04.601829 ↩

  11. See https://github.com/giovp/spatialdata-sandbox/blob/main/spacem_scseahorse1/README.md ↩

  12. See https://github.com/giovp/spatialdata-sandbox/blob/main/spacem_helanih3t3/README.md ↩