10x Xenium
Human corpus striatum
GSM9963634
silver Interactive viewer No linked publication
print(sdata)
SpatialData object
├── Images
│ └── 'morphology_mip': DataTree[cyx] (1, 8524, 10705), (1, 4262, 5352), (1, 2131, 2676), (1, 1065, 1338), (1, 532, 669)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (8317, 10375), (4158, 5187), (2079, 2593), (1039, 1296), (519, 648)
│ └── 'nucleus_labels': DataTree[yx] (8303, 10349), (4151, 5174), (2075, 2587), (1037, 1293), (518, 646)
├── Points
│ └── 'transcripts': DataFrame with shape: (7367436, 13) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (36166, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (36166, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (36234, 2) (2D shapes)
└── Tables
└── 'table': AnnData (36166, 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("itZp0PVPEDWl4HU7") # 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/itZp0PVPEDWl4HU7
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid itZp0PVPEDWl4HU7 Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["itZp0PVPEDWl4HU70000"])[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
- 36,166
- Transcripts
- 7,367,436
- Tier
- silver
- Size
- 326 MB
- Sample ID
- GSM9963634
- 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