10x Xenium
Human ovary
xenium-prime-ffpe-human-ovarian-cancer
silver Interactive viewer H&E ovarian cancer No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'he_image': DataTree[cyx] (3, 43993, 30918), (3, 21996, 15459), (3, 10998, 7729), (3, 5499, 3864), (3, 2749, 1932)
│ └── 'morphology_focus': DataTree[cyx] (4, 37631, 54089), (4, 18815, 27044), (4, 9407, 13522), (4, 4703, 6761), (4, 2351, 3380)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (37631, 54089), (18815, 27044), (9407, 13522), (4703, 6761), (2351, 3380)
│ └── 'nucleus_labels': DataTree[yx] (37631, 54089), (18815, 27044), (9407, 13522), (4703, 6761), (2351, 3380)
├── Points
│ └── 'transcripts': DataFrame with shape: (147706750, 13) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (407124, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (407124, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (414533, 2) (2D shapes)
└── Tables
└── 'table': AnnData (407124, 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("99Y58M5eRc0YbF3f") # 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/99Y58M5eRc0YbF3f
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid 99Y58M5eRc0YbF3f Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["99Y58M5eRc0YbF3f0001"])[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
- 407,124
- Transcripts
- 147,706,750
- Tier
- silver
- Chemistry
- Xenium Prime
- Magnification
- 40x
- Resolution
- 30,918 × 43,993 px
- mpp
- 0.011 µm/px
- Size
- 17 GB
- Sample ID
- xenium-prime-ffpe-human-ovarian-cancer
- License
- CC BY 4.0
- Published
- Dec 17, 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