10x Xenium
Mouse heart left ventricle
GSM8595804
bronze heart disorder Provisional
print(sdata)
SpatialData object
├── Labels
│ ├── 'cell_labels': DataTree[yx] (16962, 16857), (8481, 8428), (4240, 4214), (2120, 2107), (1060, 1053)
│ └── 'nucleus_labels': DataTree[yx] (16737, 16843), (8368, 8421), (4184, 4210), (2092, 2105), (1046, 1052)
├── Points
│ └── 'transcripts': DataFrame with shape: (2975664, 11) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (27737, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (27737, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (26935, 2) (2D shapes)
└── Tables
└── 'table': AnnData (27737, 475)
with coordinate systems:
▸ 'global', with elements:
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("ihLeho7zCt6pTlb8") # 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/ihLeho7zCt6pTlb8
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid ihLeho7zCt6pTlb8 Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["ihLeho7zCt6pTlb80000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
Spatiotemporal dynamics of the cardioimmune niche during lesion repair [spatial]→ 7 datasets · comparison
Metadata
- Technology
- 10x Xenium
- Organism
- mouse
- Tissue
- heart left ventricle
- Condition
- heart disorder
- Modality
- RNA
- Observations
- 27,737
- Transcripts
- 2,975,664
- Tier
- bronze
- Size
- 155 MB
- Sample ID
- GSM8595804
- License
- unknown
- Published
- Sep 22, 2025
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB