10x Xenium
Human skin of body
GSM8734927
silver Interactive viewer No linked publication
print(sdata)
SpatialData object
├── Images
│ └── 'morphology_mip': DataTree[cyx] (1, 98582, 45556), (1, 49291, 22778), (1, 24645, 11389), (1, 12322, 5694), (1, 6161, 2847)
├── Points
│ └── 'transcripts': DataFrame with shape: (55423170, 13) (3D points)
├── Shapes
│ └── 'cell_circles': GeoDataFrame shape: (145489, 2) (2D shapes)
└── Tables
└── 'table': AnnData (145489, 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("zP4mrVjugWwVzi8s") # 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/zP4mrVjugWwVzi8s
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid zP4mrVjugWwVzi8s Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["zP4mrVjugWwVzi8s0000"])[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
- 145,489
- Transcripts
- 55,423,170
- Tier
- silver
- Size
- 6.7 GB
- Sample ID
- GSM8734927
- 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