10x Xenium
Mouse brain
GSM9304337
silver Interactive viewer No linked publication
print(sdata)
SpatialData object
├── Images
│ └── 'morphology_mip': DataTree[cyx] (1, 20485, 25618), (1, 10242, 12809), (1, 5121, 6404), (1, 2560, 3202), (1, 1280, 1601)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (20178, 25571), (10089, 12785), (5044, 6392), (2522, 3196), (1261, 1598)
│ └── 'nucleus_labels': DataTree[yx] (19886, 25554), (9943, 12777), (4971, 6388), (2485, 3194), (1242, 1597)
├── Points
│ └── 'transcripts': DataFrame with shape: (28019471, 11) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (111474, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (111474, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (111794, 2) (2D shapes)
└── Tables
└── 'table': AnnData (111474, 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("nPMsYOqp9k5LduKt") # 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/nPMsYOqp9k5LduKt
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid nPMsYOqp9k5LduKt Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["nPMsYOqp9k5LduKt0000"])[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
- 111,474
- Transcripts
- 28,019,471
- Tier
- silver
- Size
- 1.7 GB
- Sample ID
- GSM9304337
- 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