10x Xenium
Human sural nerve
GSM8714497
bronze Interactive viewer Provisional
print(sdata)
SpatialData object
├── Images
│ └── 'morphology_mip': DataTree[cyx] (1, 17097, 22791), (1, 8548, 11395), (1, 4274, 5697), (1, 2137, 2848), (1, 1068, 1424)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (15435, 19747), (7717, 9873), (3858, 4936), (1929, 2468), (964, 1234)
│ └── 'nucleus_labels': DataTree[yx] (15295, 19607), (7647, 9803), (3823, 4901), (1911, 2450), (955, 1225)
├── Points
│ └── 'transcripts': DataFrame with shape: (278164, 10) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (9899, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (9899, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (9899, 1) (2D shapes)
└── Tables
└── 'table': AnnData (9899, 99)
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("qD6VWCNpmPXnNQRs") # 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/qD6VWCNpmPXnNQRs
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid qD6VWCNpmPXnNQRs Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["qD6VWCNpmPXnNQRs0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- 10x Xenium
- Organism
- human
- Tissue
- sural nerve
- Modality
- RNA
- Observations
- 9,899
- Transcripts
- 278,164
- Tier
- bronze
- Size
- 334 MB
- Sample ID
- GSM8714497
- License
- unknown
- Published
- Jun 28, 2025
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB