Visium

Human heart

MISC113

silver Interactive viewer H&E ✓ Verified publication

Preview Download via Python Download via CLI Load via sddb

print(sdata)

SpatialData object
├── Images
│     └── 'MISC113_full_image': DataTree[cyx] (3, 18432, 32832), (3, 9216, 16416), (3, 4608, 8208), (3, 2304, 4104)
├── Shapes
│     └── 'MISC113_spots': GeoDataFrame shape: (2955, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (2955, 33538)
with coordinate systems:
    ▸ 'global', with elements:
        MISC113_full_image (Images), MISC113_spots (Shapes)

Load in Python

import lamindb as ln

db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("QQAznDUvbiIfuOH9")   # 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

Load from the CLI

# one-shot: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/QQAznDUvbiIfuOH9

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid QQAznDUvbiIfuOH9

Load with the Python client

# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog

ds = Catalog().cohort(uids=["QQAznDUvbiIfuOH90000"])[0]
ds.elements()                 # inspect without downloading
sdata = ds.load(lazy=False)   # copy to the local cache and open

Docs: finding & loading data →

View on Lamin ↗ Open in Vitessce ↗ Flag a data issue

Part of collection

Spatially resolved multiomics of human cardiac niches→

41 datasets · publication

Metadata

Technology: Visium
Organism: human
Tissue: heart
Modality: RNA
Observations: 2,955
Tier: silver
Chemistry: Visium v1
Magnification: 20x
Resolution: 32,832 × 18,432 px
mpp: 0.456 µm/px
Size: 592 MB
Sample ID: MISC113
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