10x Xenium
Human skin of body
GSM9079632
silver Interactive viewer acne No linked publication
print(sdata)
SpatialData object
├── Images
│ └── 'morphology_mip': DataTree[cyx] (1, 20710, 17389), (1, 10355, 8694), (1, 5177, 4347), (1, 2588, 2173), (1, 1294, 1086)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (19375, 17083), (9687, 8541), (4843, 4270), (2421, 2135), (1210, 1067)
│ └── 'nucleus_labels': DataTree[yx] (17994, 17058), (8997, 8529), (4498, 4264), (2249, 2132), (1124, 1066)
├── Points
│ └── 'transcripts': DataFrame with shape: (935417, 11) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (7378, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (7378, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (7354, 2) (2D shapes)
└── Tables
└── 'table': AnnData (7378, 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("4q8aTFCtY7dGVh8z") # 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/4q8aTFCtY7dGVh8z
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid 4q8aTFCtY7dGVh8z Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["4q8aTFCtY7dGVh8z0000"])[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
- Condition
- acne
- Modality
- RNA
- Observations
- 7,378
- Transcripts
- 935,417
- Tier
- silver
- Size
- 360 MB
- Sample ID
- GSM9079632
- 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