10x Xenium
Human rectum
GSM9345501
bronze Interactive viewer Provisional
print(sdata)
SpatialData object
├── Images
│ └── 'morphology_mip': DataTree[cyx] (1, 20491, 19954), (1, 10245, 9977), (1, 5122, 4988), (1, 2561, 2494), (1, 1280, 1247)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (18033, 18901), (9016, 9450), (4508, 4725), (2254, 2362), (1127, 1181)
│ └── 'nucleus_labels': DataTree[yx] (18027, 15062), (9013, 7531), (4506, 3765), (2253, 1882), (1126, 941)
├── Points
│ └── 'transcripts': DataFrame with shape: (3304175, 13) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (26686, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (26686, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (26717, 2) (2D shapes)
└── Tables
└── 'table': AnnData (26686, 322)
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("0O5xjuPMQymOmH2s") # 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/0O5xjuPMQymOmH2s
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid 0O5xjuPMQymOmH2s Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["0O5xjuPMQymOmH2s0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- 10x Xenium
- Organism
- human
- Tissue
- rectum
- Modality
- RNA
- Observations
- 26,686
- Transcripts
- 3,304,175
- Tier
- bronze
- Size
- 319 MB
- Sample ID
- GSM9345501
- License
- unknown
- Published
- Mar 13, 2026
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB