Stereo-seq
Mouse thymus
GSM9765780
bronze Interactive viewer Provisional
print(sdata)
SpatialData object
├── Shapes
│ ├── '5PCAAAAJBBA2D5_Transcriptomics_square_025um': GeoDataFrame shape: (20196, 1) (2D shapes)
│ └── '5PCAAAAJBBA2D5_Transcriptomics_square_025um_for_vitessce': GeoDataFrame shape: (20196, 2) (2D shapes)
└── Tables
└── 'table': AnnData (20196, 25277)
with coordinate systems:
▸ 'global', with elements:
5PCAAAAJBBA2D5_Transcriptomics_square_025um (Shapes), 5PCAAAAJBBA2D5_Transcriptomics_square_025um_for_vitessce (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("Ka7ts3vHpH9YdUNs0000")
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("Ka7ts3vHpH9YdUNs") # 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 Ka7ts3vHpH9YdUNs0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/Ka7ts3vHpH9YdUNs
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid Ka7ts3vHpH9YdUNsLicense: NCBI GEO policy
Metadata
- Technology
- Stereo-seq
- Organism
- mouse
- Tissue
- thymus
- Modality
- RNA
- Observations
- 20,196
- Tier
- bronze
- Size
- 90.1 MB
- Sample ID
- GSM9765780
- 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