10x Xenium
Human breast
xenium-prime-ffpe-human-breast-cancer
silver Interactive viewer H&E breast cancer No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'he_image': DataTree[cyx] (3, 37433, 57382), (3, 18716, 28691), (3, 9358, 14345), (3, 4679, 7172), (3, 2339, 3586)
│ └── 'morphology_focus': DataTree[cyx] (4, 74945, 51265), (4, 37472, 25632), (4, 18736, 12816), (4, 9368, 6408), (4, 4684, 3204)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (74945, 51265), (37472, 25632), (18736, 12816), (9368, 6408), (4684, 3204)
│ └── 'nucleus_labels': DataTree[yx] (74945, 51265), (37472, 25632), (18736, 12816), (9368, 6408), (4684, 3204)
├── Points
│ └── 'transcripts': DataFrame with shape: (109411890, 13) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (699110, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (699110, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (701534, 2) (2D shapes)
└── Tables
└── 'table': AnnData (699110, 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("XlobaQGXpkAVt3DD") # 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/XlobaQGXpkAVt3DD
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid XlobaQGXpkAVt3DD Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["XlobaQGXpkAVt3DD0001"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- 10x Xenium
- Organism
- human
- Tissue
- breast
- Condition
- breast cancer
- Modality
- RNA
- Observations
- 699,110
- Transcripts
- 109,411,890
- Tier
- silver
- Chemistry
- Xenium Prime
- Magnification
- 40x
- Resolution
- 57,382 × 37,433 px
- mpp
- 0.011 µm/px
- Size
- 27 GB
- Sample ID
- xenium-prime-ffpe-human-breast-cancer
- License
- CC BY 4.0
- Published
- Oct 24, 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