10x Xenium
Human liver
GSM9815457
silver Interactive viewer No linked publication
print(sdata)
SpatialData object
├── Images
│ └── 'morphology_mip': DataTree[cyx] (1, 34077, 48320), (1, 17038, 24160), (1, 8519, 12080), (1, 4259, 6040), (1, 2129, 3020)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (34070, 47884), (17035, 23942), (8517, 11971), (4258, 5985), (2129, 2992)
│ └── 'nucleus_labels': DataTree[yx] (34044, 47872), (17022, 23936), (8511, 11968), (4255, 5984), (2127, 2992)
├── Points
│ └── 'transcripts': DataFrame with shape: (3827968, 13) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (186496, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (186496, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (190025, 2) (2D shapes)
└── Tables
└── 'table': AnnData (186496, 462)
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("juRqIyBoVERe9Uvi") # 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/juRqIyBoVERe9Uvi
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid juRqIyBoVERe9Uvi Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["juRqIyBoVERe9Uvi0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- 10x Xenium
- Organism
- human
- Tissue
- liver
- Modality
- RNA
- Observations
- 186,496
- Transcripts
- 3,827,968
- Tier
- silver
- Size
- 2.1 GB
- Sample ID
- GSM9815457
- License
- unknown
- Published
- Aug 3, 2026
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB