10x Xenium
Human spleen
GSM9638041
silver Interactive viewer No linked publication
print(sdata)
SpatialData object
├── Images
│ └── 'morphology_mip': DataTree[cyx] (1, 23891, 31295), (1, 11945, 15647), (1, 5972, 7823), (1, 2986, 3911), (1, 1493, 1955)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (23755, 29425), (11877, 14712), (5938, 7356), (2969, 3678), (1484, 1839)
│ └── 'nucleus_labels': DataTree[yx] (23710, 29402), (11855, 14701), (5927, 7350), (2963, 3675), (1481, 1837)
├── Points
│ └── 'transcripts': DataFrame with shape: (24173006, 13) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (329371, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (329371, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (335576, 2) (2D shapes)
└── Tables
└── 'table': AnnData (329371, 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("dtHwgSUA9iD0rSOm") # 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/dtHwgSUA9iD0rSOm
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid dtHwgSUA9iD0rSOm Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["dtHwgSUA9iD0rSOm0000"])[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
- 329,371
- Transcripts
- 24,173,006
- Tier
- silver
- Size
- 1.9 GB
- Sample ID
- GSM9638041
- 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