Visium

Human heart

MISC130

silver Interactive viewer H&E ✓ Verified publication

Preview Client Lamin CLI

print(sdata)

SpatialData object
├── Images
│     └── 'MISC130_full_image': DataTree[cyx] (3, 17629, 17222), (3, 8814, 8611), (3, 4407, 4305), (3, 2203, 2152)
├── Shapes
│     └── 'MISC130_spots': GeoDataFrame shape: (3533, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (3533, 17922)
with coordinate systems:
    ▸ 'global', with elements:
        MISC130_full_image (Images), MISC130_spots (Shapes)

Install (Python 3.12+) Docs →

Python · sddb client

from sddb import Catalog

ds = Catalog().dataset("najTZV9nrWDb6RBm0000")
ds.elements()          # inspect without downloading
sdata = ds.to_sdata()  # cached locally, reused
print(sdata)

Install (Python 3.12+) Docs →

Python · lamindb

Needs pip install lamindb and network access to the Lamin database, which is limited during the alpha. If it fails, use the Client tab.

import lamindb as ln

db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("najTZV9nrWDb6RBm")   # stem uid: Lamin resolves it to the latest version

sdata = artifact.load()   # cache, then load into memory
group = artifact.open()   # stream without downloading
path  = artifact.cache()  # sync into the local cache, returns the path

Install (Python 3.12+) Docs →

Shell

# sddb client: download the .zarr into data/
sddb-cli download najTZV9nrWDb6RBm0000 --dest data/

# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/najTZV9nrWDb6RBm

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid najTZV9nrWDb6RBm

Install (Python 3.12+) Docs →

License: CC BY-NC-SA 4.0 (noncommercial)

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Part of collection

Spatially resolved multiomics of human cardiac niches→

41 datasets · publication

Metadata

Technology: Visium
Organism: human
Tissue: heart
Modality: RNA
Observations (spots): 3,533
Tier: silver
Chemistry: Visium v1
Magnification: 20x
Resolution: 17,222 × 17,629 px
mpp: 0.455 µm/px
Size: 772 MB
Sample ID: MISC130
License: CC BY-NC-SA 4.0 NonCommercial
Published: Jul 12, 2023

Cite this dataset

doi.org/10.1038/s41586-023-06311-1 ↗

BibTeX

@article{Kanemaru_2023,
  title = {Spatially resolved multiomics of human cardiac niches},
  volume = {619},
  ISSN = {1476-4687},
  url = {http://dx.doi.org/10.1038/s41586-023-06311-1},
  DOI = {10.1038/s41586-023-06311-1},
  number = {7971},
  journal = {Nature},
  publisher = {Springer Science and Business Media LLC},
  author = {Kanemaru, Kazumasa and Cranley, James and Muraro, Daniele and Miranda, Antonio M. A. and Ho, Siew Yen and Wilbrey-Clark, Anna and Patrick Pett, Jan and Polanski, Krzysztof and Richardson, Laura and Litvinukova, Monika and Kumasaka, Natsuhiko and Qin, Yue and Jablonska, Zuzanna and Semprich, Claudia I. and Mach, Lukas and Dabrowska, Monika and Richoz, Nathan and Bolt, Liam and Mamanova, Lira and Kapuge, Rakeshlal and Barnett, Sam N. and Perera, Shani and Talavera-López, Carlos and Mulas, Ilaria and Mahbubani, Krishnaa T. and Tuck, Liz and Wang, Lu and Huang, Margaret M. and Prete, Martin and Pritchard, Sophie and Dark, John and Saeb-Parsy, Kourosh and Patel, Minal and Clatworthy, Menna R. and Hübner, Norbert and Chowdhury, Rasheda A. and Noseda, Michela and Teichmann, Sarah A.},
  year = {2023},
  month = July,
  pages = {801–810}
}

Source: nature.com ↗ · License: CC BY-NC-SA 4.0 ↗ · Reprocessed to SpatialData by SpatialData-DB