10x Xenium
Mouse liver
GSM9256797
bronze Interactive viewer Provisional
print(sdata)
SpatialData object
├── Images
│ └── 'morphology_mip': DataTree[cyx] (1, 23910, 51124), (1, 11955, 25562), (1, 5977, 12781), (1, 2988, 6390), (1, 1494, 3195)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (23882, 50763), (11941, 25381), (5970, 12690), (2985, 6345), (1492, 3172)
│ └── 'nucleus_labels': DataTree[yx] (23859, 50726), (11929, 25363), (5964, 12681), (2982, 6340), (1491, 3170)
├── Points
│ └── 'transcripts': DataFrame with shape: (193453037, 13) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (156456, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (156456, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (163451, 2) (2D shapes)
└── Tables
└── 'table': AnnData (156456, 440)
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("1hyGjLC5AGneBKLD") # 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/1hyGjLC5AGneBKLD
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid 1hyGjLC5AGneBKLD Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["1hyGjLC5AGneBKLD0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- 10x Xenium
- Organism
- mouse
- Tissue
- liver
- Modality
- RNA
- Observations
- 156,456
- Transcripts
- 193,453,037
- Tier
- bronze
- Size
- 5.3 GB
- Sample ID
- GSM9256797
- License
- unknown
- Published
- Nov 10, 2025
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB