10x Xenium
Human kidney
xenium-protein-ffpe-human-renal-carcinoma
silver Interactive viewer H&E renal cell carcinoma No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'he_image': DataTree[cyx] (3, 60680, 24096), (3, 30340, 12048), (3, 15170, 6024), (3, 7585, 3012), (3, 3792, 1506)
│ └── 'morphology_focus': DataTree[cyx] (35, 27328, 54002), (35, 13664, 27001), (35, 6832, 13500), (35, 3416, 6750), (35, 1708, 3375)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (27328, 54002), (13664, 27001), (6832, 13500), (3416, 6750), (1708, 3375)
│ └── 'nucleus_labels': DataTree[yx] (27328, 54002), (13664, 27001), (6832, 13500), (3416, 6750), (1708, 3375)
├── Points
│ └── 'transcripts': DataFrame with shape: (77056936, 13) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (465534, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (465534, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (471228, 2) (2D shapes)
└── Tables
└── 'table': AnnData (465534, 405)
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("XEI3sPvCHL7WJgd8") # 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/XEI3sPvCHL7WJgd8
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid XEI3sPvCHL7WJgd8 Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["XEI3sPvCHL7WJgd80001"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- 10x Xenium
- Organism
- human
- Tissue
- kidney
- Condition
- renal cell carcinoma
- Modality
- RNA
- Observations
- 465,534
- Transcripts
- 77,056,936
- Tier
- silver
- Chemistry
- Xenium v1
- Magnification
- 40x
- Resolution
- 24,096 × 60,680 px
- mpp
- 0.003 µm/px
- Size
- 42 GB
- Sample ID
- xenium-protein-ffpe-human-renal-carcinoma
- License
- CC BY 4.0
- Published
- Sep 25, 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