Stereo-seq
Mouse spleen
GSM9765782
bronze Interactive viewer Provisional
print(sdata)
SpatialData object
├── Shapes
│ ├── '2ADIDB6B2_Transcriptomics_square_025um': GeoDataFrame shape: (16053, 1) (2D shapes)
│ └── '2ADIDB6B2_Transcriptomics_square_025um_for_vitessce': GeoDataFrame shape: (16053, 2) (2D shapes)
└── Tables
└── 'table': AnnData (16053, 27192)
with coordinate systems:
▸ 'global', with elements:
2ADIDB6B2_Transcriptomics_square_025um (Shapes), 2ADIDB6B2_Transcriptomics_square_025um_for_vitessce (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("rNWEdftEEQjJOoOv0000")
ds.elements() # inspect without downloading
sdata = ds.to_sdata() # cached locally, reused
print(sdata) Python · lamindb
Needs pip install lamindb and network access to the Lamin database, which is limited during the alpha. If it fails, use the Client tab.
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("rNWEdftEEQjJOoOv") # stem uid: Lamin resolves it to the 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 Shell
# sddb client: download the .zarr into data/
sddb-cli download rNWEdftEEQjJOoOv0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/rNWEdftEEQjJOoOv
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid rNWEdftEEQjJOoOvLicense: NCBI GEO policy
Metadata
- Technology
- Stereo-seq
- Organism
- mouse
- Tissue
- spleen
- Modality
- RNA
- Observations
- 16,053
- Tier
- bronze
- Size
- 106 MB
- Sample ID
- GSM9765782
- License
- NCBI GEO policy
- Published
- May 27, 2026
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB