10x Xenium
Human rectum
GSM9345505
bronze Interactive viewer Provisional
print(sdata)
SpatialData object
├── Images
│ └── 'morphology_mip': DataTree[cyx] (1, 20499, 19960), (1, 10249, 9980), (1, 5124, 4990), (1, 2562, 2495), (1, 1281, 1247)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (18335, 19543), (9167, 9771), (4583, 4885), (2291, 2442), (1145, 1221)
│ └── 'nucleus_labels': DataTree[yx] (16825, 18629), (8412, 9314), (4206, 4657), (2103, 2328), (1051, 1164)
├── Points
│ └── 'transcripts': DataFrame with shape: (11638683, 13) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (37399, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (37399, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (36462, 2) (2D shapes)
└── Tables
└── 'table': AnnData (37399, 5001)
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("OgKWd3EoHVsLnjuG") # 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/OgKWd3EoHVsLnjuG
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid OgKWd3EoHVsLnjuG Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["OgKWd3EoHVsLnjuG0000"])[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
- 37,399
- Transcripts
- 11,638,683
- Tier
- bronze
- Size
- 577 MB
- Sample ID
- GSM9345505
- 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