10x Xenium
Human spleen
GSM9638046
silver Interactive viewer No linked publication
print(sdata)
SpatialData object
├── Images
│ └── 'morphology_mip': DataTree[cyx] (1, 23887, 25638), (1, 11943, 12819), (1, 5971, 6409), (1, 2985, 3204), (1, 1492, 1602)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (23787, 25454), (11893, 12727), (5946, 6363), (2973, 3181), (1486, 1590)
│ └── 'nucleus_labels': DataTree[yx] (23763, 25423), (11881, 12711), (5940, 6355), (2970, 3177), (1485, 1588)
├── Points
│ └── 'transcripts': DataFrame with shape: (67588024, 13) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (314413, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (314413, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (322788, 2) (2D shapes)
└── Tables
└── 'table': AnnData (314413, 5093)
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("HDN05y9v01dLJ3rN") # 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/HDN05y9v01dLJ3rN
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid HDN05y9v01dLJ3rN Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["HDN05y9v01dLJ3rN0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- 10x Xenium
- Organism
- human
- Tissue
- spleen
- Modality
- RNA
- Observations
- 314,413
- Transcripts
- 67,588,024
- Tier
- silver
- Size
- 2.7 GB
- Sample ID
- GSM9638046
- License
- unknown
- Published
- Apr 30, 2026
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB