10x Xenium
Human corpus striatum
GSM9963632
silver Interactive viewer No linked publication
print(sdata)
SpatialData object
├── Images
│ └── 'morphology_mip': DataTree[cyx] (1, 8164, 9664), (1, 4082, 4832), (1, 2041, 2416), (1, 1020, 1208), (1, 510, 604)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (8214, 9463), (4107, 4731), (2053, 2365), (1026, 1182), (513, 591)
│ └── 'nucleus_labels': DataTree[yx] (8181, 9433), (4090, 4716), (2045, 2358), (1022, 1179), (511, 589)
├── Points
│ └── 'transcripts': DataFrame with shape: (9822810, 13) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (35125, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (35125, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (35194, 2) (2D shapes)
└── Tables
└── 'table': AnnData (35125, 5001)
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("hkBl8nmCUUgu5pYN") # 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/hkBl8nmCUUgu5pYN
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid hkBl8nmCUUgu5pYN Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["hkBl8nmCUUgu5pYN0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- 10x Xenium
- Organism
- human
- Tissue
- corpus striatum
- Modality
- RNA
- Observations
- 35,125
- Transcripts
- 9,822,810
- Tier
- silver
- Size
- 362 MB
- Sample ID
- GSM9963632
- License
- unknown
- Published
- Sep 30, 2026
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB