10x Xenium
Human kidney
GSM9210725
bronze Interactive viewer Provisional
print(sdata)
SpatialData object
├── Images
│ └── 'morphology_mip': DataTree[cyx] (1, 30687, 28500), (1, 15343, 14250), (1, 7671, 7125), (1, 3835, 3562), (1, 1917, 1781)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (30551, 28470), (15275, 14235), (7637, 7117), (3818, 3558), (1909, 1779)
│ └── 'nucleus_labels': DataTree[yx] (30510, 28189), (15255, 14094), (7627, 7047), (3813, 3523), (1906, 1761)
├── Points
│ └── 'transcripts': DataFrame with shape: (2201280, 11) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (43526, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (43526, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (43146, 2) (2D shapes)
└── Tables
└── 'table': AnnData (43526, 480)
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("RK9Fh9ThHucE3lvD") # 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/RK9Fh9ThHucE3lvD
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid RK9Fh9ThHucE3lvD Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["RK9Fh9ThHucE3lvD0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- 10x Xenium
- Organism
- human
- Tissue
- kidney
- Modality
- RNA
- Observations
- 43,526
- Transcripts
- 2,201,280
- Tier
- bronze
- Size
- 790 MB
- Sample ID
- GSM9210725
- License
- unknown
- Published
- May 5, 2026
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB