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Visium

Human kidney

NCBI565

silver Interactive viewer H&E nephrolithiasis ✓ Verified publication
Human kidney preview
print(sdata)
SpatialData object
├── Images
│     └── 'NCBI565_full_image': DataTree[cyx] (3, 11299, 10473), (3, 5649, 5236), (3, 2824, 2618), (3, 1412, 1309)
├── Shapes
│     └── 'NCBI565_spots': GeoDataFrame shape: (1085, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (1085, 36601)
with coordinate systems:
    ▸ 'global', with elements:
        NCBI565_full_image (Images), NCBI565_spots (Shapes)
Python · sddb client
from sddb import Catalog

ds = Catalog().dataset("uPnF4kwEcckN5w100000")
ds.elements()          # inspect without downloading
sdata = ds.to_sdata()  # cached locally, reused
print(sdata)
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("uPnF4kwEcckN5w10")   # 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
Shell
# sddb client: download the .zarr into data/
sddb-cli download uPnF4kwEcckN5w100000 --dest data/

# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/uPnF4kwEcckN5w10

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid uPnF4kwEcckN5w10

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

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

Metadata

Technology
Visium
Organism
human
Tissue
kidney
Condition
nephrolithiasis
Modality
RNA
Observations (spots)
1,085
Tier
silver
Chemistry
Visium v1
Resolution
10,473 × 11,299 px
mpp
0.758 µm/px
Size
209 MB
Sample ID
NCBI565
License
CC BY-NC-SA 4.0 NonCommercial
Published
May 4, 2023

Cite this dataset

doi.org/10.1038/s41467-023-38975-8 ↗
BibTeX
@article{Canela_2023,
  title = {A spatially anchored transcriptomic atlas of the human kidney papilla identifies significant immune injury in patients with stone disease},
  volume = {14},
  ISSN = {2041-1723},
  url = {http://dx.doi.org/10.1038/s41467-023-38975-8},
  DOI = {10.1038/s41467-023-38975-8},
  number = {1},
  journal = {Nature Communications},
  publisher = {Springer Science and Business Media LLC},
  author = {Canela, Victor Hugo and Bowen, William S. and Ferreira, Ricardo Melo and Syed, Farooq and Lingeman, James E. and Sabo, Angela R. and Barwinska, Daria and Winfree, Seth and Lake, Blue B. and Cheng, Ying-Hua and Gaut, Joseph P. and Ferkowicz, Michael and LaFavers, Kaice A. and Zhang, Kun and Coe, Fredric L. and Worcester, Elaine and Jain, Sanjay and Eadon, Michael T. and Williams, James C. and El-Achkar, Tarek M.},
  year = {2023},
  month = July
}

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