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Visium

Human intestine

ZEN39

silver Interactive viewer H&E colon adenocarcinoma ✓ Verified publication
Human intestine preview
print(sdata)
SpatialData object
├── Images
│     └── 'ZEN39_full_image': DataTree[cyx] (3, 16804, 16954), (3, 8402, 8477), (3, 4201, 4238), (3, 2100, 2119)
├── Shapes
│     └── 'ZEN39_spots': GeoDataFrame shape: (1219, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (1219, 36601)
with coordinate systems:
    ▸ 'global', with elements:
        ZEN39_full_image (Images), ZEN39_spots (Shapes)
Python · sddb client
from sddb import Catalog

ds = Catalog().dataset("rqd9ugxrqTZRDZEi0000")
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("rqd9ugxrqTZRDZEi")   # 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 rqd9ugxrqTZRDZEi0000 --dest data/

# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/rqd9ugxrqTZRDZEi

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid rqd9ugxrqTZRDZEi

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

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Metadata

Technology
Visium
Organism
human
Tissue
intestine
Condition
colon adenocarcinoma
Modality
RNA
Observations (spots)
1,219
Tier
silver
Chemistry
Visium v1
Magnification
20x
Resolution
16,954 × 16,804 px
mpp
0.460 µm/px
Size
535 MB
Sample ID
ZEN39
License
CC BY-NC-SA 4.0 NonCommercial
Published
Jan 19, 2023

Cite this dataset

doi.org/10.1101/2023.01.23.525135 ↗
BibTeX
@article{Valdeolivas_2023,
  title = {Charting the Heterogeneity of Colorectal Cancer Consensus Molecular Subtypes using Spatial Transcriptomics},
  url = {http://dx.doi.org/10.1101/2023.01.23.525135},
  DOI = {10.1101/2023.01.23.525135},
  publisher = {openRxiv},
  author = {Valdeolivas, Alberto and Amberg, Bettina and Giroud, Nicolas and Richardson, Marion and Gálvez, Eric J.C. and Badillo, Solveig and Julien-Laferrière, Alice and Turos, Demeter and von Voithenberg, Lena Voith and Wells, Isabelle and Lo, Amy A. and Yángüez, Emilio and Das Thakur, Meghna and Bscheider, Michael and Sultan, Marc and Kumpesa, Nadine and Jacobsen, Björn and Bergauer, Tobias and Saez-Rodriguez, Julio and Rottenberg, Sven and Schwalie, Petra C. and Hahn, Kerstin},
  year = {2023},
  month = Jan
}

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