10x Xenium
Human subcutaneous adipose tissue
GSM8959879
bronze Interactive viewer Provisional
print(sdata)
SpatialData object
├── Images
│ └── 'morphology_mip': DataTree[cyx] (1, 20549, 19961), (1, 10274, 9980), (1, 5137, 4990), (1, 2568, 2495), (1, 1284, 1247)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (19986, 18370), (9993, 9185), (4996, 4592), (2498, 2296), (1249, 1148)
│ └── 'nucleus_labels': DataTree[yx] (19846, 18231), (9923, 9115), (4961, 4557), (2480, 2278), (1240, 1139)
├── Points
│ └── 'transcripts': DataFrame with shape: (748247, 10) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (2711, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (2711, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (2711, 1) (2D shapes)
└── Tables
└── 'table': AnnData (2711, 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("7r3kGDTwMPyb6UE2") # 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/7r3kGDTwMPyb6UE2
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid 7r3kGDTwMPyb6UE2 Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["7r3kGDTwMPyb6UE20000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- 10x Xenium
- Organism
- human
- Tissue
- subcutaneous adipose tissue
- Modality
- RNA
- Observations
- 2,711
- Transcripts
- 748,247
- Tier
- bronze
- Size
- 286 MB
- Sample ID
- GSM8959879
- License
- unknown
- Published
- Jun 19, 2025
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB