Visium
Human lung
GSM8770954
silver Interactive viewer H&E sarcoidosis No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM8770954_SAR001_hires_image': DataArray[cyx] (3, 18347, 18508)
│ └── 'GSM8770954_SAR001_lowres_image': DataArray[cyx] (3, 595, 600)
├── Shapes
│ └── 'GSM8770954_SAR001': GeoDataFrame shape: (4992, 2) (2D shapes)
└── Tables
└── 'table': AnnData (4992, 37082)
with coordinate systems:
▸ 'GSM8770954_SAR001', with elements:
GSM8770954_SAR001_hires_image (Images), GSM8770954_SAR001_lowres_image (Images), GSM8770954_SAR001 (Shapes)
▸ 'GSM8770954_SAR001_downscaled_hires', with elements:
GSM8770954_SAR001_hires_image (Images), GSM8770954_SAR001 (Shapes)
▸ 'GSM8770954_SAR001_downscaled_lowres', with elements:
GSM8770954_SAR001_lowres_image (Images), GSM8770954_SAR001 (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("Ki6r6odT2c8xc9em") # 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/Ki6r6odT2c8xc9em
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid Ki6r6odT2c8xc9em Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["Ki6r6odT2c8xc9em0000"])[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
- 18,508 × 18,347 px
- mpp
- 3.646 µm/px
- Size
- 825 MB
- Sample ID
- GSM8770954
- 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