10x Xenium
Human skin of body
GSM8734926
silver Interactive viewer No linked publication
print(sdata)
SpatialData object
├── Images
│ └── 'morphology_mip': DataTree[cyx] (1, 108755, 48300), (1, 54377, 24150), (1, 27188, 12075), (1, 13594, 6037), (1, 6797, 3018)
├── Points
│ └── 'transcripts': DataFrame with shape: (57529467, 13) (3D points)
├── Shapes
│ └── 'cell_circles': GeoDataFrame shape: (148741, 2) (2D shapes)
└── Tables
└── 'table': AnnData (148741, 360)
with coordinate systems:
▸ 'global', with elements:
morphology_mip (Images), transcripts (Points), cell_circles (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("nyV1oZ2PMvleAUcS") # 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/nyV1oZ2PMvleAUcS
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid nyV1oZ2PMvleAUcS Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["nyV1oZ2PMvleAUcS0000"])[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
- 148,741
- Transcripts
- 57,529,467
- Tier
- silver
- Size
- 6.9 GB
- Sample ID
- GSM8734926
- License
- unknown
- Published
- Feb 13, 2025
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB