10x Xenium
Mouse brain
GSM9304335
silver Interactive viewer No linked publication
print(sdata)
SpatialData object
├── Images
│ └── 'morphology_mip': DataTree[cyx] (1, 27264, 19956), (1, 13632, 9978), (1, 6816, 4989), (1, 3408, 2494), (1, 1704, 1247)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (27068, 19145), (13534, 9572), (6767, 4786), (3383, 2393), (1691, 1196)
│ └── 'nucleus_labels': DataTree[yx] (26992, 18000), (13496, 9000), (6748, 4500), (3374, 2250), (1687, 1125)
├── Points
│ └── 'transcripts': DataFrame with shape: (32388408, 11) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (123258, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (123258, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (123215, 2) (2D shapes)
└── Tables
└── 'table': AnnData (123258, 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("0kW2IQVX09FeJ4Bl") # 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/0kW2IQVX09FeJ4Bl
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid 0kW2IQVX09FeJ4Bl Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["0kW2IQVX09FeJ4Bl0000"])[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
- 123,258
- Transcripts
- 32,388,408
- Tier
- silver
- Size
- 1.9 GB
- Sample ID
- GSM9304335
- 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