10x Xenium
Human lung
xenium-human-lung-cancer-post-xenium-technote__human-lung-cancer-ffpe
silver Interactive viewer H&E lung cancer No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'he_image': DataTree[cyx] (3, 43448, 25078), (3, 21724, 12539), (3, 10862, 6269), (3, 5431, 3134), (3, 2715, 1567)
│ └── 'morphology_focus': DataTree[cyx] (1, 34191, 54061), (1, 17095, 27030), (1, 8547, 13515), (1, 4273, 6757), (1, 2136, 3378)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (34191, 54061), (17095, 27030), (8547, 13515), (4273, 6757), (2136, 3378)
│ └── 'nucleus_labels': DataTree[yx] (34191, 54061), (17095, 27030), (8547, 13515), (4273, 6757), (2136, 3378)
├── Points
│ └── 'transcripts': DataFrame with shape: (32073729, 13) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (278659, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (278659, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (278659, 2) (2D shapes)
└── Tables
└── 'table': AnnData (278659, 289)
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("zU8xEuiIiOh0uPCY") # 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/zU8xEuiIiOh0uPCY
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid zU8xEuiIiOh0uPCY Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["zU8xEuiIiOh0uPCY0001"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- 10x Xenium
- Organism
- human
- Tissue
- lung
- Condition
- lung cancer
- Modality
- RNA
- Observations
- 278,659
- Transcripts
- 32,073,729
- Tier
- silver
- Chemistry
- Xenium v1
- Magnification
- 40x
- Resolution
- 25,078 × 43,448 px
- mpp
- 0.012 µm/px
- Size
- 5.9 GB
- Sample ID
- xenium-human-lung-cancer-post-xenium-technote__human-lung-cancer-ffpe
- License
- CC BY 4.0
- Published
- Nov 6, 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