10x Xenium
Human skin of body
GSM9079612
silver Interactive viewer acne No linked publication
print(sdata)
SpatialData object
├── Images
│ └── 'morphology_mip': DataTree[cyx] (1, 17079, 14421), (1, 8539, 7210), (1, 4269, 3605), (1, 2134, 1802), (1, 1067, 901)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (15160, 13426), (7580, 6713), (3790, 3356), (1895, 1678), (947, 839)
│ └── 'nucleus_labels': DataTree[yx] (15113, 13381), (7556, 6690), (3778, 3345), (1889, 1672), (944, 836)
├── Points
│ └── 'transcripts': DataFrame with shape: (315628, 11) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (5914, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (5914, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (5949, 2) (2D shapes)
└── Tables
└── 'table': AnnData (5914, 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("YAQaY5xeiFyahJqy") # 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/YAQaY5xeiFyahJqy
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid YAQaY5xeiFyahJqy Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["YAQaY5xeiFyahJqy0000"])[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
- 5,914
- Transcripts
- 315,628
- Tier
- silver
- Size
- 218 MB
- Sample ID
- GSM9079612
- 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