10x Xenium
Mouse skin of body
GSM9636012
bronze Interactive viewer Provisional
print(sdata)
SpatialData object
├── Images
│ └── 'morphology_mip': DataTree[cyx] (1, 17120, 42589), (1, 8560, 21294), (1, 4280, 10647), (1, 2140, 5323), (1, 1070, 2661)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (16713, 42010), (8356, 21005), (4178, 10502), (2089, 5251), (1044, 2625)
│ └── 'nucleus_labels': DataTree[yx] (16237, 41979), (8118, 20989), (4059, 10494), (2029, 5247), (1014, 2623)
├── Points
│ └── 'transcripts': DataFrame with shape: (17420461, 13) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (41266, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (41266, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (40981, 2) (2D shapes)
└── Tables
└── 'table': AnnData (41266, 5106)
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("13wPbOGU5TLBuCnF") # 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/13wPbOGU5TLBuCnF
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid 13wPbOGU5TLBuCnF Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["13wPbOGU5TLBuCnF0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- 10x Xenium
- Organism
- mouse
- Tissue
- skin of body
- Modality
- RNA
- Observations
- 41,266
- Transcripts
- 17,420,461
- Tier
- bronze
- Size
- 836 MB
- Sample ID
- GSM9636012
- License
- unknown
- Published
- Jun 25, 2026
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB