10x Xenium
Mouse brain
GSM10073652
silver Interactive viewer No linked publication
print(sdata)
SpatialData object
├── Images
│ └── 'morphology_mip': DataTree[cyx] (1, 101923, 34125), (1, 50961, 17062), (1, 25480, 8531), (1, 12740, 4265), (1, 6370, 2132)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (101918, 34120), (50959, 17060), (25479, 8530), (12739, 4265), (6369, 2132)
│ └── 'nucleus_labels': DataTree[yx] (101897, 34106), (50948, 17053), (25474, 8526), (12737, 4263), (6368, 2131)
├── Points
│ └── 'transcripts': DataFrame with shape: (129979312, 13) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (171924, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (171924, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (171437, 2) (2D shapes)
└── Tables
└── 'table': AnnData (171924, 297)
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("EJCgo6cDH38sa5sF") # 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/EJCgo6cDH38sa5sF
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid EJCgo6cDH38sa5sF Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["EJCgo6cDH38sa5sF0000"])[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
- 171,924
- Transcripts
- 129,979,312
- Tier
- silver
- Size
- 4.7 GB
- Sample ID
- GSM10073652
- License
- unknown
- Published
- Sep 24, 2026
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB