Visium
Mouse lung
GSM8659275
silver Interactive viewer H&E malaria No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM8659275_INF_H299_M_Day6_Lung_GEX50_B1_hires_image': DataArray[cyx] (3, 1984, 2000)
│ └── 'GSM8659275_INF_H299_M_Day6_Lung_GEX50_B1_lowres_image': DataArray[cyx] (3, 595, 600)
├── Shapes
│ └── 'GSM8659275_INF_H299_M_Day6_Lung_GEX50_B1': GeoDataFrame shape: (4222, 2) (2D shapes)
└── Tables
└── 'table': AnnData (4222, 38514)
with coordinate systems:
▸ 'GSM8659275_INF_H299_M_Day6_Lung_GEX50_B1', with elements:
GSM8659275_INF_H299_M_Day6_Lung_GEX50_B1_hires_image (Images), GSM8659275_INF_H299_M_Day6_Lung_GEX50_B1_lowres_image (Images), GSM8659275_INF_H299_M_Day6_Lung_GEX50_B1 (Shapes)
▸ 'GSM8659275_INF_H299_M_Day6_Lung_GEX50_B1_downscaled_hires', with elements:
GSM8659275_INF_H299_M_Day6_Lung_GEX50_B1_hires_image (Images), GSM8659275_INF_H299_M_Day6_Lung_GEX50_B1 (Shapes)
▸ 'GSM8659275_INF_H299_M_Day6_Lung_GEX50_B1_downscaled_lowres', with elements:
GSM8659275_INF_H299_M_Day6_Lung_GEX50_B1_lowres_image (Images), GSM8659275_INF_H299_M_Day6_Lung_GEX50_B1 (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("KGy9kgqAsVWk6Hm10000")
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("KGy9kgqAsVWk6Hm1") # 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 KGy9kgqAsVWk6Hm10000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/KGy9kgqAsVWk6Hm1
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid KGy9kgqAsVWk6Hm1License: NCBI GEO policy
Part of collection
Spatiotemporal transcriptomic niches of complement pathway and serine protease inhibitor activation in aging and infection→ 165 datasets · other
Metadata
- Technology
- Visium
- Organism
- mouse
- Tissue
- lung
- Condition
- malaria
- Modality
- RNA
- Observations (spots)
- 4,222
- Tier
- silver
- Chemistry
- Visium v1
- Resolution
- 2,000 × 1,984 px
- mpp
- 3.415 µm/px
- Size
- 59.1 MB
- Sample ID
- GSM8659275
- License
- NCBI GEO policy
- Published
- Aug 13, 2026
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