10x Xenium
Human breast
xenium-ffpe-human-breast-biomarkers__human-breast-biomarkers-s2-mid
silver Interactive viewer H&E No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'he_image': DataTree[cyx] (3, 38540, 27235), (3, 19270, 13617), (3, 9635, 6808), (3, 4817, 3404), (3, 2408, 1702)
│ └── 'morphology_focus': DataTree[cyx] (4, 37351, 51082), (4, 18675, 25541), (4, 9337, 12770), (4, 4668, 6385), (4, 2334, 3192)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (37351, 51082), (18675, 25541), (9337, 12770), (4668, 6385), (2334, 3192)
│ └── 'nucleus_labels': DataTree[yx] (37351, 51082), (18675, 25541), (9337, 12770), (4668, 6385), (2334, 3192)
├── Points
│ └── 'transcripts': DataFrame with shape: (74273457, 13) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (380739, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (380739, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (387485, 2) (2D shapes)
└── Tables
└── 'table': AnnData (380739, 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("dNKJ7pgFj8SVgwaf") # 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/dNKJ7pgFj8SVgwaf
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid dNKJ7pgFj8SVgwaf Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["dNKJ7pgFj8SVgwaf0001"])[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
- 380,739
- Transcripts
- 74,273,457
- Tier
- silver
- Chemistry
- Xenium v1
- Magnification
- 40x
- Resolution
- 27,235 × 38,540 px
- mpp
- 0.007 µm/px
- Size
- 9.6 GB
- Sample ID
- xenium-ffpe-human-breast-biomarkers__human-breast-biomarkers-s2-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