Visium
Mouse liver
GSM9635997
silver Interactive viewer H&E No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM9635997_Liv_N-3_hires_image': DataArray[cyx] (3, 1534, 2000)
│ └── 'GSM9635997_Liv_N-3_lowres_image': DataArray[cyx] (3, 460, 600)
├── Shapes
│ └── 'GSM9635997_Liv_N-3': GeoDataFrame shape: (3062, 2) (2D shapes)
└── Tables
└── 'table': AnnData (3062, 19465)
with coordinate systems:
▸ 'GSM9635997_Liv_N-3', with elements:
GSM9635997_Liv_N-3_hires_image (Images), GSM9635997_Liv_N-3_lowres_image (Images), GSM9635997_Liv_N-3 (Shapes)
▸ 'GSM9635997_Liv_N-3_downscaled_hires', with elements:
GSM9635997_Liv_N-3_hires_image (Images), GSM9635997_Liv_N-3 (Shapes)
▸ 'GSM9635997_Liv_N-3_downscaled_lowres', with elements:
GSM9635997_Liv_N-3_lowres_image (Images), GSM9635997_Liv_N-3 (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("CgGjcq6NHN40kCgb") # 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/CgGjcq6NHN40kCgb
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid CgGjcq6NHN40kCgb Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["CgGjcq6NHN40kCgb0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
Spatial transcriptomic analysis of mouse liver in a high-fat diet model with kimchi supplementation→ 4 datasets · comparison
Metadata
- Technology
- Visium
- Organism
- mouse
- Tissue
- liver
- Modality
- RNA
- Observations
- 3,062
- Tier
- silver
- Chemistry
- Visium v1
- Resolution
- 2,000 × 1,534 px
- mpp
- 5.195 µm/px
- Size
- 44 MB
- Sample ID
- GSM9635997
- License
- unknown
- Published
- Apr 2, 2026
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB