10x Xenium
Human breast
xenium-ffpe-human-breast-biomarkers__human-breast-biomarkers-s3-mid
silver Interactive viewer H&E No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'he_image': DataTree[cyx] (3, 35502, 32654), (3, 17751, 16327), (3, 8875, 8163), (3, 4437, 4081), (3, 2218, 2040)
│ └── 'morphology_focus': DataTree[cyx] (4, 44376, 45619), (4, 22188, 22809), (4, 11094, 11404), (4, 5547, 5702), (4, 2773, 2851)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (44376, 45619), (22188, 22809), (11094, 11404), (5547, 5702), (2773, 2851)
│ └── 'nucleus_labels': DataTree[yx] (44376, 45619), (22188, 22809), (11094, 11404), (5547, 5702), (2773, 2851)
├── Points
│ └── 'transcripts': DataFrame with shape: (212515116, 13) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (373150, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (373150, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (375359, 2) (2D shapes)
└── Tables
└── 'table': AnnData (373150, 280)
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("XXeyNnBTewPiLRTH") # 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/XXeyNnBTewPiLRTH
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid XXeyNnBTewPiLRTH Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["XXeyNnBTewPiLRTH0001"])[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
- Modality
- RNA
- Observations
- 373,150
- Transcripts
- 212,515,116
- Tier
- silver
- Chemistry
- Xenium v1
- Magnification
- 40x
- Resolution
- 32,654 × 35,502 px
- mpp
- 0.009 µm/px
- Size
- 14 GB
- Sample ID
- xenium-ffpe-human-breast-biomarkers__human-breast-biomarkers-s3-mid
- License
- CC BY 4.0
- Published
- Dec 11, 2025
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