Visium
Mouse prostate gland
GSM8941073
bronze Interactive viewer H&E Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM8941073_Slide4A_hires_image': DataArray[cyx] (3, 1930, 2000)
│ └── 'GSM8941073_Slide4A_lowres_image': DataArray[cyx] (3, 579, 600)
├── Shapes
│ └── 'GSM8941073_Slide4A': GeoDataFrame shape: (1185, 2) (2D shapes)
└── Tables
└── 'table': AnnData (1185, 19465)
with coordinate systems:
▸ 'GSM8941073_Slide4A', with elements:
GSM8941073_Slide4A_hires_image (Images), GSM8941073_Slide4A_lowres_image (Images), GSM8941073_Slide4A (Shapes)
▸ 'GSM8941073_Slide4A_downscaled_hires', with elements:
GSM8941073_Slide4A_hires_image (Images), GSM8941073_Slide4A (Shapes)
▸ 'GSM8941073_Slide4A_downscaled_lowres', with elements:
GSM8941073_Slide4A_lowres_image (Images), GSM8941073_Slide4A (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("hD55b4GWfHWn3V5x0000")
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("hD55b4GWfHWn3V5x") # 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 hD55b4GWfHWn3V5x0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/hD55b4GWfHWn3V5x
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid hD55b4GWfHWn3V5xLicense: NCBI GEO policy
Part 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 (spots)
- 1,185
- Tier
- bronze
- Chemistry
- Visium v1
- Magnification
- other
- Resolution
- 2,000 × 1,930 px
- mpp
- 4.082 µm/px
- Size
- 29.2 MB
- Sample ID
- GSM8941073
- License
- NCBI GEO policy
- Published
- Dec 2, 2025
Cite this dataset
doi.org/10.1016/j.neo.2025.101230 ↗ BibTeX
@article{Shelley_2025,
title = {A spatiotemporal atlas of orchiectomy-induced androgen deprivation-mediated modulation of cellular composition and gene expression in the mouse prostate},
volume = {69},
ISSN = {1476-5586},
url = {http://dx.doi.org/10.1016/j.neo.2025.101230},
DOI = {10.1016/j.neo.2025.101230},
journal = {Neoplasia},
publisher = {Elsevier BV},
author = {Shelley, Greg and May, Allison and Robinson, Tyler and Dai, Jinlu and Pitchiaya, Sethu and Keller, Evan T.},
year = {2025},
month = Nov,
pages = {101230}
}Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB