Visium
Human lung
GSM8770961
silver Interactive viewer H&E sarcoidosis No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM8770961_SARH14_hires_image': DataArray[cyx] (3, 18141, 19120)
│ └── 'GSM8770961_SARH14_lowres_image': DataArray[cyx] (3, 569, 600)
├── Shapes
│ └── 'GSM8770961_SARH14': GeoDataFrame shape: (4992, 2) (2D shapes)
└── Tables
└── 'table': AnnData (4992, 37082)
with coordinate systems:
▸ 'GSM8770961_SARH14', with elements:
GSM8770961_SARH14_hires_image (Images), GSM8770961_SARH14_lowres_image (Images), GSM8770961_SARH14 (Shapes)
▸ 'GSM8770961_SARH14_downscaled_hires', with elements:
GSM8770961_SARH14_hires_image (Images), GSM8770961_SARH14 (Shapes)
▸ 'GSM8770961_SARH14_downscaled_lowres', with elements:
GSM8770961_SARH14_lowres_image (Images), GSM8770961_SARH14 (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("XXie1j6W0YhuAhEX") # 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/XXie1j6W0YhuAhEX
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid XXie1j6W0YhuAhEX Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["XXie1j6W0YhuAhEX0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
Spatial transcriptomics of cellular niches in pulmonary granuloma of chronic sarcoidosis patients→ 9 datasets · other
Metadata
- Technology
- Visium
- Organism
- human
- Tissue
- lung
- Condition
- sarcoidosis
- Modality
- RNA
- Observations
- 4,992
- Tier
- silver
- Chemistry
- Visium v1
- Resolution
- 19,120 × 18,141 px
- mpp
- 3.765 µm/px
- Size
- 668 MB
- Sample ID
- GSM8770961
- License
- unknown
- Published
- Mar 24, 2026
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB