10x Xenium
Human coronary artery
GSM9423580
bronze Interactive viewer atherosclerosis Provisional
print(sdata)
SpatialData object
├── Images
│ └── 'morphology_mip': DataTree[cyx] (1, 20526, 19950), (1, 10263, 9975), (1, 5131, 4987), (1, 2565, 2493), (1, 1282, 1246)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (20223, 16290), (10111, 8145), (5055, 4072), (2527, 2036), (1263, 1018)
│ └── 'nucleus_labels': DataTree[yx] (20200, 16264), (10100, 8132), (5050, 4066), (2525, 2033), (1262, 1016)
├── Points
│ └── 'transcripts': DataFrame with shape: (891234, 13) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (6004, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (6004, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (5831, 2) (2D shapes)
└── Tables
└── 'table': AnnData (6004, 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("e3szJUgXVFRD376t") # 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/e3szJUgXVFRD376t
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid e3szJUgXVFRD376t Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["e3szJUgXVFRD376t0000"])[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
- 6,004
- Transcripts
- 891,234
- Tier
- bronze
- Size
- 314 MB
- Sample ID
- GSM9423580
- 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