10x Xenium
Mouse lumbar spinal cord
GSM9986815
silver Interactive viewer No linked publication
print(sdata)
SpatialData object
├── Images
│ └── 'morphology_mip': DataTree[cyx] (1, 44296, 19964), (1, 22148, 9982), (1, 11074, 4991), (1, 5537, 2495), (1, 2768, 1247)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (44196, 19430), (22098, 9715), (11049, 4857), (5524, 2428), (2762, 1214)
│ └── 'nucleus_labels': DataTree[yx] (42920, 19025), (21460, 9512), (10730, 4756), (5365, 2378), (2682, 1189)
├── Points
│ └── 'transcripts': DataFrame with shape: (12337498, 11) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (26303, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (26303, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (26015, 2) (2D shapes)
└── Tables
└── 'table': AnnData (26303, 296)
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("HlweRGV8JaBfYics") # 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/HlweRGV8JaBfYics
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid HlweRGV8JaBfYics Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["HlweRGV8JaBfYics0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- 10x Xenium
- Organism
- mouse
- Tissue
- lumbar spinal cord
- Modality
- RNA
- Observations
- 26,303
- Transcripts
- 12,337,498
- Tier
- silver
- Size
- 1.1 GB
- Sample ID
- GSM9986815
- License
- unknown
- Published
- Sep 28, 2026
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB