Visium
Mouse prostate gland
GSM8941074
bronze Interactive viewer H&E Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM8941074_Slide4B_hires_image': DataArray[cyx] (3, 2000, 1952)
│ └── 'GSM8941074_Slide4B_lowres_image': DataArray[cyx] (3, 600, 586)
├── Shapes
│ └── 'GSM8941074_Slide4B': GeoDataFrame shape: (2222, 2) (2D shapes)
└── Tables
└── 'table': AnnData (2222, 19465)
with coordinate systems:
▸ 'GSM8941074_Slide4B', with elements:
GSM8941074_Slide4B_hires_image (Images), GSM8941074_Slide4B_lowres_image (Images), GSM8941074_Slide4B (Shapes)
▸ 'GSM8941074_Slide4B_downscaled_hires', with elements:
GSM8941074_Slide4B_hires_image (Images), GSM8941074_Slide4B (Shapes)
▸ 'GSM8941074_Slide4B_downscaled_lowres', with elements:
GSM8941074_Slide4B_lowres_image (Images), GSM8941074_Slide4B (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("X8I8CNO2iETlajDJ") # 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/X8I8CNO2iETlajDJ
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid X8I8CNO2iETlajDJ Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["X8I8CNO2iETlajDJ0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
A spatiotemporal atlas of orchiectomy-induced modulation of cellular composition and gene expression in the mouse prostate→ 8 datasets · comparison
Metadata
- Technology
- Visium
- Organism
- mouse
- Tissue
- prostate gland
- Modality
- RNA
- Observations
- 2,222
- Tier
- bronze
- Chemistry
- Visium v1
- Magnification
- other
- Resolution
- 1,952 × 2,000 px
- mpp
- 3.970 µm/px
- Size
- 47 MB
- Sample ID
- GSM8941074
- License
- unknown
- Published
- Dec 2, 2025
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB