Visium
Mouse brain
GSM8471249
bronze Interactive viewer H&E Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM8471249_WTvehicule_hires_image': DataArray[cyx] (3, 1992, 2000)
│ └── 'GSM8471249_WTvehicule_lowres_image': DataArray[cyx] (3, 598, 600)
├── Shapes
│ └── 'GSM8471249_WTvehicule': GeoDataFrame shape: (4953, 2) (2D shapes)
└── Tables
└── 'table': AnnData (4953, 32285)
with coordinate systems:
▸ 'GSM8471249_WTvehicule', with elements:
GSM8471249_WTvehicule_hires_image (Images), GSM8471249_WTvehicule_lowres_image (Images), GSM8471249_WTvehicule (Shapes)
▸ 'GSM8471249_WTvehicule_downscaled_hires', with elements:
GSM8471249_WTvehicule_hires_image (Images), GSM8471249_WTvehicule (Shapes)
▸ 'GSM8471249_WTvehicule_downscaled_lowres', with elements:
GSM8471249_WTvehicule_lowres_image (Images), GSM8471249_WTvehicule (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("yul15NSRV19ZzWZK0000")
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("yul15NSRV19ZzWZK") # 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 yul15NSRV19ZzWZK0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/yul15NSRV19ZzWZK
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid yul15NSRV19ZzWZKLicense: NCBI GEO policy
Part of collection
Effects of inhibiting stearoyl-CoA desaturase (SCD) on the spatial transcriptome in a mouse model of Alzheimer's disease (AD)→ 4 datasets · comparison
Metadata
- Technology
- Visium
- Organism
- mouse
- Tissue
- brain
- Modality
- RNA
- Observations (spots)
- 4,953
- Tier
- bronze
- Chemistry
- Visium v1
- Magnification
- other
- Resolution
- 2,000 × 1,992 px
- mpp
- 3.688 µm/px
- Size
- 51.6 MB
- Sample ID
- GSM8471249
- License
- NCBI GEO policy
- Published
- Jan 22, 2026
Cite this dataset
doi.org/10.1016/j.neuropharm.2026.110835 ↗ BibTeX
@article{Hector_2026,
title = {Electrocorticographic, astrocytic and transcriptomic signatures in the triple transgenic mouse model of Alzheimer’s disease submitted to stearoyl-CoA desaturase inhibition},
volume = {289},
ISSN = {0028-3908},
url = {http://dx.doi.org/10.1016/j.neuropharm.2026.110835},
DOI = {10.1016/j.neuropharm.2026.110835},
journal = {Neuropharmacology},
publisher = {Elsevier BV},
author = {Hector, Audrey and Leduc, Tanya and da Costa Caiado, Maria João and Delignat-Lavaud, Benoît and Dufort-Gervais, Julien and Daneault, Caroline and Des Rosiers, Christine and Bourguignon, Clément and Lina, Jean-Marc and Fernandes, Karl and Brouillette, Jonathan and Mongrain, Valérie},
year = {2026},
month = May,
pages = {110835}
}Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB