10x Xenium
Human breast
GSM7780153
bronze Interactive viewer breast cancer Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'morphology_focus': DataTree[cyx] (1, 25778, 35416), (1, 12889, 17708), (1, 6444, 8854), (1, 3222, 4427), (1, 1611, 2213)
│ └── 'morphology_mip': DataTree[cyx] (1, 25778, 35416), (1, 12889, 17708), (1, 6444, 8854), (1, 3222, 4427), (1, 1611, 2213)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (25778, 35416), (12889, 17708), (6444, 8854), (3222, 4427), (1611, 2213)
│ └── 'nucleus_labels': DataTree[yx] (25778, 35416), (12889, 17708), (6444, 8854), (3222, 4427), (1611, 2213)
├── Points
│ └── 'transcripts': DataFrame with shape: (42638083, 8) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (167780, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (167780, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (167780, 1) (2D shapes)
└── Tables
└── 'table': AnnData (167780, 313)
with coordinate systems:
▸ 'global', with elements:
morphology_focus (Images), morphology_mip (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("zwCYn0f7rVjpJ0wp") # 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/zwCYn0f7rVjpJ0wp
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid zwCYn0f7rVjpJ0wp Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["zwCYn0f7rVjpJ0wp0000"])[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
- 167,780
- Transcripts
- 42,638,083
- Tier
- bronze
- Size
- 3.9 GB
- Sample ID
- GSM7780153
- License
- unknown
- Published
- Oct 9, 2023
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB