10x Xenium
Human skin of body
GSM9079613
silver Interactive viewer No linked publication
print(sdata)
SpatialData object
├── Images
│ └── 'morphology_mip': DataTree[cyx] (1, 17139, 11663), (1, 8569, 5831), (1, 4284, 2915), (1, 2142, 1457), (1, 1071, 728)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (16762, 11604), (8381, 5802), (4190, 2901), (2095, 1450), (1047, 725)
│ └── 'nucleus_labels': DataTree[yx] (16736, 11080), (8368, 5540), (4184, 2770), (2092, 1385), (1046, 692)
├── Points
│ └── 'transcripts': DataFrame with shape: (1495923, 11) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (10079, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (10079, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (10093, 2) (2D shapes)
└── Tables
└── 'table': AnnData (10079, 100)
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("Bfx67JT3ppxrpVUr") # 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/Bfx67JT3ppxrpVUr
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid Bfx67JT3ppxrpVUr Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["Bfx67JT3ppxrpVUr0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- 10x Xenium
- Organism
- human
- Tissue
- skin of body
- Modality
- RNA
- Observations
- 10,079
- Transcripts
- 1,495,923
- Tier
- silver
- Size
- 257 MB
- Sample ID
- GSM9079613
- License
- unknown
- Published
- Dec 3, 2025
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB