Visium
Human aortic valve leaflet
GSM9196849
bronze Interactive viewer H&E aortic valve stenosis Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM9196849_patient_6B_hires_image': DataArray[cyx] (3, 1876, 2000)
│ └── 'GSM9196849_patient_6B_lowres_image': DataArray[cyx] (3, 563, 600)
├── Shapes
│ └── 'GSM9196849_patient_6B': GeoDataFrame shape: (1693, 2) (2D shapes)
└── Tables
└── 'table': AnnData (1693, 36601)
with coordinate systems:
▸ 'GSM9196849_patient_6B', with elements:
GSM9196849_patient_6B_hires_image (Images), GSM9196849_patient_6B_lowres_image (Images), GSM9196849_patient_6B (Shapes)
▸ 'GSM9196849_patient_6B_downscaled_hires', with elements:
GSM9196849_patient_6B_hires_image (Images), GSM9196849_patient_6B (Shapes)
▸ 'GSM9196849_patient_6B_downscaled_lowres', with elements:
GSM9196849_patient_6B_lowres_image (Images), GSM9196849_patient_6B (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("aljDkNJr1njeBJGE") # 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/aljDkNJr1njeBJGE
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid aljDkNJr1njeBJGE Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["aljDkNJr1njeBJGE0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
Spatial transcriptomic profiling of the human aortic valve reveals cellular sex differences near sites of calcification→ 8 datasets · other
Metadata
- Technology
- Visium
- Organism
- human
- Tissue
- aortic valve leaflet
- Condition
- aortic valve stenosis
- Modality
- RNA
- Observations
- 1,693
- Tier
- bronze
- Chemistry
- Visium v1
- Magnification
- other
- Resolution
- 2,000 × 1,876 px
- mpp
- 3.595 µm/px
- Size
- 8.7 MB
- Sample ID
- GSM9196849
- License
- unknown
- Published
- Jun 3, 2026
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB