10x Xenium
Human skin of body
GSM9079619
silver Interactive viewer acne No linked publication
print(sdata)
SpatialData object
├── Images
│ └── 'morphology_mip': DataTree[cyx] (1, 20469, 14419), (1, 10234, 7209), (1, 5117, 3604), (1, 2558, 1802), (1, 1279, 901)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (20114, 13762), (10057, 6881), (5028, 3440), (2514, 1720), (1257, 860)
│ └── 'nucleus_labels': DataTree[yx] (19979, 13623), (9989, 6811), (4994, 3405), (2497, 1702), (1248, 851)
├── Points
│ └── 'transcripts': DataFrame with shape: (669409, 10) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (22670, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (22670, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (22670, 1) (2D shapes)
└── Tables
└── 'table': AnnData (22670, 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("xuOaJp7taK9yEOve") # 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/xuOaJp7taK9yEOve
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid xuOaJp7taK9yEOve Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["xuOaJp7taK9yEOve0000"])[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
- 22,670
- Transcripts
- 669,409
- Tier
- silver
- Size
- 279 MB
- Sample ID
- GSM9079619
- 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