10x Xenium
Human uterine cervix
xenium-prime-ffpe-human-cervical-cancer
silver Interactive viewer H&E cervical cancer No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'he_image': DataTree[cyx] (3, 46545, 38219), (3, 23272, 19109), (3, 11636, 9554), (3, 5818, 4777), (3, 2909, 2388)
│ └── 'morphology_focus': DataTree[cyx] (4, 51205, 54125), (4, 25602, 27062), (4, 12801, 13531), (4, 6400, 6765), (4, 3200, 3382)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (51205, 54125), (25602, 27062), (12801, 13531), (6400, 6765), (3200, 3382)
│ └── 'nucleus_labels': DataTree[yx] (51205, 54125), (25602, 27062), (12801, 13531), (6400, 6765), (3200, 3382)
├── Points
│ └── 'transcripts': DataFrame with shape: (113697508, 13) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (840387, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (840387, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (839632, 2) (2D shapes)
└── Tables
└── 'table': AnnData (840387, 5101)
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("PPV2HttD3rk5nMQJ") # 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/PPV2HttD3rk5nMQJ
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid PPV2HttD3rk5nMQJ Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["PPV2HttD3rk5nMQJ0001"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- 10x Xenium
- Organism
- human
- Tissue
- uterine cervix
- Condition
- cervical cancer
- Modality
- RNA
- Observations
- 840,387
- Transcripts
- 113,697,508
- Tier
- silver
- Chemistry
- Xenium Prime
- Resolution
- 38,219 × 46,545 px
- Size
- 23 GB
- Sample ID
- xenium-prime-ffpe-human-cervical-cancer
- License
- CC BY 4.0
- Published
- Sep 4, 2024
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