10x Xenium
Rat kidney
GSM9866601
bronze Interactive viewer Provisional
print(sdata)
SpatialData object
├── Images
│ └── 'morphology_mip': DataTree[cyx] (1, 30728, 48362), (1, 15364, 24181), (1, 7682, 12090), (1, 3841, 6045), (1, 1920, 3022)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (28831, 43803), (14415, 21901), (7207, 10950), (3603, 5475), (1801, 2737)
│ └── 'nucleus_labels': DataTree[yx] (28784, 43756), (14392, 21878), (7196, 10939), (3598, 5469), (1799, 2734)
├── Points
│ └── 'transcripts': DataFrame with shape: (48941899, 11) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (349164, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (349164, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (349164, 2) (2D shapes)
└── Tables
└── 'table': AnnData (349164, 50)
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("dSCZTDWDFKHEatLs") # 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/dSCZTDWDFKHEatLs
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid dSCZTDWDFKHEatLs Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["dSCZTDWDFKHEatLs0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- 10x Xenium
- Organism
- rat
- Tissue
- kidney
- Modality
- RNA
- Observations
- 349,164
- Transcripts
- 48,941,899
- Tier
- bronze
- Size
- 3.6 GB
- Sample ID
- GSM9866601
- License
- unknown
- Published
- Jul 10, 2026
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB