Visium
Human coronary artery
GSM9989020
silver Interactive viewer H&E coronary artery disorder No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM9989020_6552-A2486-9_hires_image': DataArray[cyx] (3, 2000, 1873)
│ └── 'GSM9989020_6552-A2486-9_lowres_image': DataArray[cyx] (3, 600, 562)
├── Shapes
│ └── 'GSM9989020_6552-A2486-9': GeoDataFrame shape: (3112, 2) (2D shapes)
└── Tables
└── 'table': AnnData (3112, 18085)
with coordinate systems:
▸ 'GSM9989020_6552-A2486-9', with elements:
GSM9989020_6552-A2486-9_hires_image (Images), GSM9989020_6552-A2486-9_lowres_image (Images), GSM9989020_6552-A2486-9 (Shapes)
▸ 'GSM9989020_6552-A2486-9_downscaled_hires', with elements:
GSM9989020_6552-A2486-9_hires_image (Images), GSM9989020_6552-A2486-9 (Shapes)
▸ 'GSM9989020_6552-A2486-9_downscaled_lowres', with elements:
GSM9989020_6552-A2486-9_lowres_image (Images), GSM9989020_6552-A2486-9 (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("mxDcOrxCPJ0IjJmy") # 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/mxDcOrxCPJ0IjJmy
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid mxDcOrxCPJ0IjJmy Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["mxDcOrxCPJ0IjJmy0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- Visium
- Organism
- human
- Tissue
- coronary artery
- Condition
- coronary artery disorder
- Modality
- RNA
- Observations
- 3,112
- Tier
- silver
- Chemistry
- Visium v1
- Resolution
- 1,873 × 2,000 px
- mpp
- 4.007 µm/px
- Size
- 14 MB
- Sample ID
- GSM9989020
- License
- unknown
- Published
- Sep 1, 2026
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB