10x Xenium
Mouse small intestine
GSM8964408
bronze Interactive viewer Provisional
print(sdata)
SpatialData object
├── Images
│ └── 'morphology_focus': DataTree[cyx] (4, 54451, 48267), (4, 27225, 24133), (4, 13612, 12066), (4, 6806, 6033), (4, 3403, 3016)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (54451, 48267), (27225, 24133), (13612, 12066), (6806, 6033), (3403, 3016)
│ └── 'nucleus_labels': DataTree[yx] (54451, 48267), (27225, 24133), (13612, 12066), (6806, 6033), (3403, 3016)
├── Shapes
│ └── 'cell_circles': GeoDataFrame shape: (722119, 2) (2D shapes)
└── Tables
└── 'table': AnnData (722119, 5006)
with coordinate systems:
▸ 'global', with elements:
morphology_focus (Images), cell_labels (Labels), nucleus_labels (Labels), cell_circles (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("GZdu0iPYQtsrH7g9") # 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/GZdu0iPYQtsrH7g9
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid GZdu0iPYQtsrH7g9 Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["GZdu0iPYQtsrH7g90000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
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Metadata
- Technology
- 10x Xenium
- Organism
- mouse
- Tissue
- small intestine
- Modality
- RNA
- Observations
- 722,119
- Tier
- bronze
- Size
- 14 GB
- Sample ID
- GSM8964408
- License
- NCBI GEO policy
- Published
- Apr 30, 2026
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB