CosMx SMI
Human lung
GSM8647890
bronze Interactive viewer Provisional
print(sdata)
SpatialData object
├── Points
│ └── 'points': DataFrame with shape: (261737, 12) (2D points)
├── Shapes
│ ├── 'cell_circles': GeoDataFrame shape: (2365, 2) (2D shapes)
│ └── 'fov_boxes': GeoDataFrame shape: (1, 2) (2D shapes)
└── Tables
└── 'table': AnnData (2365, 985)
with coordinate systems:
▸ 'global', with elements:
points (Points), cell_circles (Shapes), fov_boxes (Shapes)
▸ 'microns', with elements:
points (Points), fov_boxes (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("tfNP38uO7gIRWa8J0000")
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("tfNP38uO7gIRWa8J") # 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 tfNP38uO7gIRWa8J0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/tfNP38uO7gIRWa8J
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid tfNP38uO7gIRWa8JLicense: NCBI GEO policy
Metadata
- Technology
- CosMx SMI
- Vendor
- Bruker
- Organism
- human
- Tissue
- lung
- Modality
- RNA
- Observations (cells)
- 2,365
- Transcripts
- 261,737
- Tier
- bronze
- Size
- 11.1 MB
- Sample ID
- GSM8647890
- License
- NCBI GEO policy
- Published
- Nov 22, 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