10x Xenium
Human coronary artery
GSM9423573
bronze Interactive viewer atherosclerosis Provisional
print(sdata)
SpatialData object
├── Images
│ └── 'morphology_mip': DataTree[cyx] (1, 23906, 17173), (1, 11953, 8586), (1, 5976, 4293), (1, 2988, 2146), (1, 1494, 1073)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (22672, 17053), (11336, 8526), (5668, 4263), (2834, 2131), (1417, 1065)
│ └── 'nucleus_labels': DataTree[yx] (21356, 16473), (10678, 8236), (5339, 4118), (2669, 2059), (1334, 1029)
├── Points
│ └── 'transcripts': DataFrame with shape: (772981, 13) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (10288, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (10288, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (10204, 2) (2D shapes)
└── Tables
└── 'table': AnnData (10288, 477)
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("cHhDNbfKc2vSLYh9") # 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/cHhDNbfKc2vSLYh9
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid cHhDNbfKc2vSLYh9 Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["cHhDNbfKc2vSLYh90000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- 10x Xenium
- Organism
- human
- Tissue
- coronary artery
- Condition
- atherosclerosis
- Modality
- RNA
- Observations
- 10,288
- Transcripts
- 772,981
- Tier
- bronze
- Size
- 374 MB
- Sample ID
- GSM9423573
- License
- unknown
- Published
- Feb 2, 2026
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB