Visium
Mouse brain
GSM8321877
silver Interactive viewer H&E glioma No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM8321877_tumor1_hires_image': DataArray[cyx] (3, 2000, 1974)
│ └── 'GSM8321877_tumor1_lowres_image': DataArray[cyx] (3, 600, 592)
├── Shapes
│ └── 'GSM8321877_tumor1': GeoDataFrame shape: (2327, 2) (2D shapes)
└── Tables
└── 'table': AnnData (2327, 32285)
with coordinate systems:
▸ 'GSM8321877_tumor1', with elements:
GSM8321877_tumor1_hires_image (Images), GSM8321877_tumor1_lowres_image (Images), GSM8321877_tumor1 (Shapes)
▸ 'GSM8321877_tumor1_downscaled_hires', with elements:
GSM8321877_tumor1_hires_image (Images), GSM8321877_tumor1 (Shapes)
▸ 'GSM8321877_tumor1_downscaled_lowres', with elements:
GSM8321877_tumor1_lowres_image (Images), GSM8321877_tumor1 (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("841eF87UsuL2vJMQ") # 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/841eF87UsuL2vJMQ
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid 841eF87UsuL2vJMQ Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["841eF87UsuL2vJMQ0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
Specific oncogenic drivers differently shaped the composition and functional diversity of immune cells in the microenvironment of experimental gliomas→ 3 datasets · comparison
Metadata
- Technology
- Visium
- Organism
- mouse
- Tissue
- brain
- Condition
- glioma
- Modality
- RNA
- Observations
- 2,327
- Tier
- silver
- Chemistry
- Visium v1
- Resolution
- 1,974 × 2,000 px
- mpp
- 3.280 µm/px
- Size
- 36 MB
- Sample ID
- GSM8321877
- License
- unknown
- Published
- Sep 12, 2025
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB