Visium
Human liver
GSM9876361
bronze Interactive viewer H&E biliary atresia Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM9876361_BA1_1_hires_image': DataArray[cyx] (3, 2000, 1976)
│ └── 'GSM9876361_BA1_1_lowres_image': DataArray[cyx] (3, 600, 593)
├── Shapes
│ └── 'GSM9876361_BA1_1': GeoDataFrame shape: (1392, 2) (2D shapes)
└── Tables
└── 'table': AnnData (1392, 37481)
with coordinate systems:
▸ 'GSM9876361_BA1_1', with elements:
GSM9876361_BA1_1_hires_image (Images), GSM9876361_BA1_1_lowres_image (Images), GSM9876361_BA1_1 (Shapes)
▸ 'GSM9876361_BA1_1_downscaled_hires', with elements:
GSM9876361_BA1_1_hires_image (Images), GSM9876361_BA1_1 (Shapes)
▸ 'GSM9876361_BA1_1_downscaled_lowres', with elements:
GSM9876361_BA1_1_lowres_image (Images), GSM9876361_BA1_1 (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("mLszJ9VQkio4e29g") # 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/mLszJ9VQkio4e29g
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid mLszJ9VQkio4e29g Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["mLszJ9VQkio4e29g0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
Spatial transcriptomics supports a role for SOX-4 driven signaling throughout the disease course of biliary atresia→ 16 datasets · comparison
Metadata
- Technology
- Visium
- Organism
- human
- Tissue
- liver
- Condition
- biliary atresia
- Modality
- RNA
- Observations
- 1,392
- Tier
- bronze
- Chemistry
- Visium v1
- Resolution
- 1,976 × 2,000 px
- mpp
- 3.663 µm/px
- Size
- 24 MB
- Sample ID
- GSM9876361
- License
- unknown
- Published
- Jul 20, 2026
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB