Stereo-seq
Mouse liver
GSE276063:B02822B2
bronze Interactive viewer No linked publication
print(sdata)
SpatialData object
├── Shapes
│ ├── 'GSE276063_B02822B2_square_025um': GeoDataFrame shape: (89983, 1) (2D shapes)
│ └── 'GSE276063_B02822B2_square_025um_for_vitessce': GeoDataFrame shape: (89983, 2) (2D shapes)
└── Tables
└── 'table': AnnData (89983, 37100)
with coordinate systems:
▸ 'global', with elements:
GSE276063_B02822B2_square_025um (Shapes), GSE276063_B02822B2_square_025um_for_vitessce (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("m9Mf2rpBIgADZ3JR0000")
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("m9Mf2rpBIgADZ3JR") # 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 m9Mf2rpBIgADZ3JR0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/m9Mf2rpBIgADZ3JR
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid m9Mf2rpBIgADZ3JRLicense: NCBI GEO policy
Metadata
- Technology
- Stereo-seq
- Organism
- mouse
- Tissue
- liver
- Modality
- RNA
- Observations
- 89,983
- Tier
- bronze
- Size
- 240 MB
- Sample ID
- GSE276063:B02822B2
- License
- NCBI GEO policy
- Published
- Feb 11, 2025
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