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10x Xenium

Human kidney

GSM8720429

silver Interactive viewer membranous glomerulonephritis No linked publication
Human kidney preview
print(sdata)
SpatialData object
├── Points
│     └── 'transcripts': DataFrame with shape: (2019706, 13) (3D points)
├── Shapes
│     └── 'cell_circles': GeoDataFrame shape: (49095, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (49095, 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("L63qBPEi1Jb14kUM")   # 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/L63qBPEi1Jb14kUM

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid L63qBPEi1Jb14kUM
Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog

ds = Catalog().cohort(uids=["L63qBPEi1Jb14kUM0000"])[0]
ds.elements()                 # inspect without downloading
sdata = ds.load(lazy=False)   # copy to the local cache and open

Docs: finding & loading data →

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Metadata

Technology
10x Xenium
Organism
human
Tissue
kidney
Condition
membranous glomerulonephritis
Modality
RNA
Observations
49,095
Transcripts
2,019,706
Tier
silver
Size
43 MB
Sample ID
GSM8720429
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