10x Xenium
Human ascending aorta
GSM9194119
bronze Interactive viewer temporal arteritis Provisional
print(sdata)
SpatialData object
├── Labels
│ ├── 'cell_labels': DataTree[yx] (20919, 41685), (10459, 20842), (5229, 10421), (2614, 5210), (1307, 2605)
│ └── 'nucleus_labels': DataTree[yx] (20779, 41548), (10389, 20774), (5194, 10387), (2597, 5193), (1298, 2596)
├── Points
│ └── 'transcripts': DataFrame with shape: (3693184, 10) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (55867, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (55867, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (55867, 1) (2D shapes)
└── Tables
└── 'table': AnnData (55867, 377)
with coordinate systems:
▸ 'global', with elements:
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("ntZfyQrcmxo5jsbX") # 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/ntZfyQrcmxo5jsbX
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid ntZfyQrcmxo5jsbX Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["ntZfyQrcmxo5jsbX0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- 10x Xenium
- Organism
- human
- Tissue
- ascending aorta
- Condition
- temporal arteritis
- Modality
- RNA
- Observations
- 55,867
- Transcripts
- 3,693,184
- Tier
- bronze
- Size
- 180 MB
- Sample ID
- GSM9194119
- License
- unknown
- Published
- Feb 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