Visium
Human lung
GSM8375642
silver Interactive viewer H&E COVID-19 No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM8375642_L11P_hires_image': DataArray[cyx] (3, 1954, 2000)
│ └── 'GSM8375642_L11P_lowres_image': DataArray[cyx] (3, 586, 600)
├── Shapes
│ └── 'GSM8375642_L11P': GeoDataFrame shape: (4768, 2) (2D shapes)
└── Tables
└── 'table': AnnData (4768, 17943)
with coordinate systems:
▸ 'GSM8375642_L11P', with elements:
GSM8375642_L11P_hires_image (Images), GSM8375642_L11P_lowres_image (Images), GSM8375642_L11P (Shapes)
▸ 'GSM8375642_L11P_downscaled_hires', with elements:
GSM8375642_L11P_hires_image (Images), GSM8375642_L11P (Shapes)
▸ 'GSM8375642_L11P_downscaled_lowres', with elements:
GSM8375642_L11P_lowres_image (Images), GSM8375642_L11P (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("WLqB4WJx1cnj2ggs") # 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/WLqB4WJx1cnj2ggs
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid WLqB4WJx1cnj2ggs Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["WLqB4WJx1cnj2ggs0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
Spatial transcriptomics unveils the in situ cellular and molecular hallmarks of the lung in fatal COVID-19→ 22 datasets · comparison
Metadata
- Technology
- Visium
- Organism
- human
- Tissue
- lung
- Condition
- COVID-19
- Modality
- RNA
- Observations
- 4,768
- Tier
- silver
- Chemistry
- Visium v1
- Resolution
- 2,000 × 1,954 px
- mpp
- 3.546 µm/px
- Size
- 18 MB
- Sample ID
- GSM8375642
- License
- unknown
- Published
- Aug 10, 2026
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB