10x Xenium
Mouse brain
GSM9304332
silver Interactive viewer No linked publication
print(sdata)
SpatialData object
├── Images
│ └── 'morphology_mip': DataTree[cyx] (1, 23868, 17114), (1, 11934, 8557), (1, 5967, 4278), (1, 2983, 2139), (1, 1491, 1069)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (23479, 17023), (11739, 8511), (5869, 4255), (2934, 2127), (1467, 1063)
│ └── 'nucleus_labels': DataTree[yx] (23219, 16089), (11609, 8044), (5804, 4022), (2902, 2011), (1451, 1005)
├── Points
│ └── 'transcripts': DataFrame with shape: (26170467, 11) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (124103, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (124103, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (126041, 2) (2D shapes)
└── Tables
└── 'table': AnnData (124103, 347)
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("HCqdLcWlHP9HDkZ3") # 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/HCqdLcWlHP9HDkZ3
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid HCqdLcWlHP9HDkZ3 Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["HCqdLcWlHP9HDkZ30000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- 10x Xenium
- Organism
- mouse
- Tissue
- brain
- Modality
- RNA
- Observations
- 124,103
- Transcripts
- 26,170,467
- Tier
- silver
- Size
- 1.5 GB
- Sample ID
- GSM9304332
- License
- unknown
- Published
- Aug 12, 2026
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB