10x Xenium
Human coronary artery
GSM9423583
bronze Interactive viewer atherosclerosis Provisional
print(sdata)
SpatialData object
├── Images
│ └── 'morphology_mip': DataTree[cyx] (1, 20543, 22806), (1, 10271, 11403), (1, 5135, 5701), (1, 2567, 2850), (1, 1283, 1425)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (20386, 22125), (10193, 11062), (5096, 5531), (2548, 2765), (1274, 1382)
│ └── 'nucleus_labels': DataTree[yx] (20125, 22043), (10062, 11021), (5031, 5510), (2515, 2755), (1257, 1377)
├── Points
│ └── 'transcripts': DataFrame with shape: (984088, 13) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (14277, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (14277, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (14220, 2) (2D shapes)
└── Tables
└── 'table': AnnData (14277, 477)
with coordinate systems:
▸ 'global', with elements:
morphology_mip (Images), cell_labels (Labels), nucleus_labels (Labels), transcripts (Points), cell_boundaries (Shapes), cell_circles (Shapes), nucleus_boundaries (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("84uRRe2sR6MNbw9k") # 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/84uRRe2sR6MNbw9k
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid 84uRRe2sR6MNbw9k Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["84uRRe2sR6MNbw9k0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- 10x Xenium
- Organism
- human
- Tissue
- coronary artery
- Condition
- atherosclerosis
- Modality
- RNA
- Observations
- 14,277
- Transcripts
- 984,088
- Tier
- bronze
- Size
- 389 MB
- Sample ID
- GSM9423583
- License
- unknown
- Published
- Feb 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