10x Xenium
Mouse bone tissue
mouse-bone-data-with-custom-add-on-panel-1-standard__mfemur-edta-pfa-3daydecal-section
silver Interactive viewer H&E No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'he_image': DataTree[cyx] (3, 52743, 23253), (3, 26371, 11626), (3, 13185, 5813), (3, 6592, 2906), (3, 3296, 1453)
│ ├── 'morphology_focus': DataTree[cyx] (1, 30619, 53947), (1, 15309, 26973), (1, 7654, 13486), (1, 3827, 6743), (1, 1913, 3371)
│ └── 'morphology_mip': DataTree[cyx] (1, 30619, 53947), (1, 15309, 26973), (1, 7654, 13486), (1, 3827, 6743), (1, 1913, 3371)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (30619, 53947), (15309, 26973), (7654, 13486), (3827, 6743), (1913, 3371)
│ └── 'nucleus_labels': DataTree[yx] (30619, 53947), (15309, 26973), (7654, 13486), (3827, 6743), (1913, 3371)
├── Points
│ └── 'transcripts': DataFrame with shape: (34308528, 10) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (247876, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (247876, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (247876, 1) (2D shapes)
└── Tables
└── 'table': AnnData (247876, 479)
with coordinate systems:
▸ 'global', with elements:
he_image (Images), 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("ftcwfWqbDwNk5EMp") # 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/ftcwfWqbDwNk5EMp
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid ftcwfWqbDwNk5EMp Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["ftcwfWqbDwNk5EMp0001"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- 10x Xenium
- Organism
- mouse
- Tissue
- bone tissue
- Modality
- RNA
- Observations
- 247,876
- Transcripts
- 34,308,528
- Tier
- silver
- Chemistry
- Xenium v1
- Resolution
- 23,253 × 52,743 px
- Size
- 7.0 GB
- Sample ID
- mouse-bone-data-with-custom-add-on-panel-1-standard__mfemur-edta-pfa-3daydecal-section
- License
- CC BY 4.0
- Published
- Apr 3, 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