10x Xenium
Human ovary
xenium-comparison-fresh-frozen-human-ovarian-cancer__prime-human-ovary-cancer-ff
silver Interactive viewer H&E ovarian cancer No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'he_image': DataTree[cyx] (3, 54232, 51163), (3, 27116, 25581), (3, 13558, 12790), (3, 6779, 6395), (3, 3389, 3197)
│ └── 'morphology_focus': DataTree[cyx] (4, 34192, 36931), (4, 17096, 18465), (4, 8548, 9232), (4, 4274, 4616), (4, 2137, 2308)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (34192, 36931), (17096, 18465), (8548, 9232), (4274, 4616), (2137, 2308)
│ └── 'nucleus_labels': DataTree[yx] (34192, 36931), (17096, 18465), (8548, 9232), (4274, 4616), (2137, 2308)
├── Points
│ └── 'transcripts': DataFrame with shape: (450349704, 13) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (200900, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (200900, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (206175, 2) (2D shapes)
└── Tables
└── 'table': AnnData (200900, 5001)
with coordinate systems:
▸ 'global', with elements:
he_image (Images), morphology_focus (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("9gj73j25dg5HbI4d") # 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/9gj73j25dg5HbI4d
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid 9gj73j25dg5HbI4d Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["9gj73j25dg5HbI4d0001"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- 10x Xenium
- Organism
- human
- Tissue
- ovary
- Condition
- ovarian cancer
- Modality
- RNA
- Observations
- 200,900
- Transcripts
- 450,349,704
- Tier
- silver
- Chemistry
- Xenium v1
- Magnification
- 40x
- Resolution
- 51,163 × 54,232 px
- mpp
- 0.005 µm/px
- Size
- 21 GB
- Sample ID
- xenium-comparison-fresh-frozen-human-ovarian-cancer__prime-human-ovary-cancer-ff
- License
- CC BY 4.0
- Published
- Oct 7, 2025
Cite this dataset
No linked publication found — please cite the data source: 10x Genomics ↗.
Source: 10x Genomics ↗ · License: CC BY 4.0 ↗ · Reprocessed to SpatialData by SpatialData-DB