10x Xenium
Human kidney
GSM8720413
silver diabetic kidney disease No linked publication
print(sdata)
SpatialData object
├── Points
│ └── 'transcripts': DataFrame with shape: (325661, 11) (3D points)
├── Shapes
│ └── 'cell_circles': GeoDataFrame shape: (20472, 2) (2D shapes)
└── Tables
└── 'table': AnnData (20472, 50)
with coordinate systems:
▸ 'global', with elements:
transcripts (Points), cell_circles (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("4aa7meIGBU5btyG6") # 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/4aa7meIGBU5btyG6
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid 4aa7meIGBU5btyG6 Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["4aa7meIGBU5btyG60000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
Single-nucleus transcriptomic landscape of human glomerular diseases [Xenium]→ 21 datasets · comparison
Metadata
- Technology
- 10x Xenium
- Organism
- human
- Tissue
- kidney
- Condition
- diabetic kidney disease
- Modality
- RNA
- Observations
- 20,472
- Transcripts
- 325,661
- Tier
- silver
- Size
- 13 MB
- Sample ID
- GSM8720413
- License
- unknown
- Published
- Sep 8, 2026
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB