10x Xenium
Mouse brain
GSM9304340
silver Interactive viewer No linked publication
print(sdata)
SpatialData object
├── Images
│ └── 'morphology_mip': DataTree[cyx] (1, 34043, 19968), (1, 17021, 9984), (1, 8510, 4992), (1, 4255, 2496), (1, 2127, 1248)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (33932, 19905), (16966, 9952), (8483, 4976), (4241, 2488), (2120, 1244)
│ └── 'nucleus_labels': DataTree[yx] (33329, 19891), (16664, 9945), (8332, 4972), (4166, 2486), (2083, 1243)
├── Points
│ └── 'transcripts': DataFrame with shape: (40672301, 11) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (115109, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (115109, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (114580, 2) (2D shapes)
└── Tables
└── 'table': AnnData (115109, 347)
with coordinate systems:
▸ 'global', with elements:
morphology_mip (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("ip5Q9amKmihi2SRj") # 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/ip5Q9amKmihi2SRj
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid ip5Q9amKmihi2SRj Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["ip5Q9amKmihi2SRj0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- 10x Xenium
- Organism
- mouse
- Tissue
- brain
- Modality
- RNA
- Observations
- 115,109
- Transcripts
- 40,672,301
- Tier
- silver
- Size
- 2.3 GB
- Sample ID
- GSM9304340
- License
- unknown
- Published
- Aug 12, 2026
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB