10x Xenium
Human corpus striatum
GSM9963633
silver Interactive viewer No linked publication
print(sdata)
SpatialData object
├── Images
│ └── 'morphology_mip': DataTree[cyx] (1, 8715, 8748), (1, 4357, 4374), (1, 2178, 2187), (1, 1089, 1093), (1, 544, 546)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (8507, 8514), (4253, 4257), (2126, 2128), (1063, 1064), (531, 532)
│ └── 'nucleus_labels': DataTree[yx] (8505, 8510), (4252, 4255), (2126, 2127), (1063, 1063), (531, 531)
├── Points
│ └── 'transcripts': DataFrame with shape: (19815072, 13) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (19584, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (19584, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (19700, 2) (2D shapes)
└── Tables
└── 'table': AnnData (19584, 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("3tdcqfP7mXF7PsMZ") # 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/3tdcqfP7mXF7PsMZ
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid 3tdcqfP7mXF7PsMZ Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["3tdcqfP7mXF7PsMZ0000"])[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
- 19,584
- Transcripts
- 19,815,072
- Tier
- silver
- Size
- 518 MB
- Sample ID
- GSM9963633
- 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