10x Xenium
Human breast
xenium-ffpe-human-breast-biomarkers__human-breast-biomarkers-s1-bot
silver Interactive viewer H&E No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'he_image': DataTree[cyx] (3, 45088, 29458), (3, 22544, 14729), (3, 11272, 7364), (3, 5636, 3682), (3, 2818, 1841)
│ └── 'morphology_focus': DataTree[cyx] (4, 40942, 54100), (4, 20471, 27050), (4, 10235, 13525), (4, 5117, 6762), (4, 2558, 3381)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (40942, 54100), (20471, 27050), (10235, 13525), (5117, 6762), (2558, 3381)
│ └── 'nucleus_labels': DataTree[yx] (40942, 54100), (20471, 27050), (10235, 13525), (5117, 6762), (2558, 3381)
├── Points
│ └── 'transcripts': DataFrame with shape: (142664090, 13) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (254480, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (254480, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (251124, 2) (2D shapes)
└── Tables
└── 'table': AnnData (254480, 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("KjDkeTwHCZ354K6p") # 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/KjDkeTwHCZ354K6p
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid KjDkeTwHCZ354K6p Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["KjDkeTwHCZ354K6p0001"])[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
- 254,480
- Transcripts
- 142,664,090
- Tier
- silver
- Chemistry
- Xenium v1
- Magnification
- 40x
- Resolution
- 29,458 × 45,088 px
- mpp
- 0.009 µm/px
- Size
- 12 GB
- Sample ID
- xenium-ffpe-human-breast-biomarkers__human-breast-biomarkers-s1-bot
- 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