Visium
Mouse heart
GSM9254699
bronze Interactive viewer H&E Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM9254699_Sham_ST_hires_image': DataArray[cyx] (3, 2000, 1977)
│ └── 'GSM9254699_Sham_ST_lowres_image': DataArray[cyx] (3, 600, 593)
├── Shapes
│ └── 'GSM9254699_Sham_ST': GeoDataFrame shape: (1676, 2) (2D shapes)
└── Tables
└── 'table': AnnData (1676, 32285)
with coordinate systems:
▸ 'GSM9254699_Sham_ST', with elements:
GSM9254699_Sham_ST_hires_image (Images), GSM9254699_Sham_ST_lowres_image (Images), GSM9254699_Sham_ST (Shapes)
▸ 'GSM9254699_Sham_ST_downscaled_hires', with elements:
GSM9254699_Sham_ST_hires_image (Images), GSM9254699_Sham_ST (Shapes)
▸ 'GSM9254699_Sham_ST_downscaled_lowres', with elements:
GSM9254699_Sham_ST_lowres_image (Images), GSM9254699_Sham_ST (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("S1uQrhpkkpZKraBm0000")
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("S1uQrhpkkpZKraBm") # 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 S1uQrhpkkpZKraBm0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/S1uQrhpkkpZKraBm
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid S1uQrhpkkpZKraBmLicense: NCBI GEO policy
Part of collection
Integrated Spatial Transcriptomics and Single-Cell RNA Sequencing Reveal Lars2-Mediated Spatiotemporal Dynamics of Myocardial Remodeling in a Mouse Model of Transverse Aortic Constriction (TAC)→ 3 datasets · comparison
Metadata
- Technology
- Visium
- Organism
- mouse
- Tissue
- heart
- Modality
- RNA
- Observations (spots)
- 1,676
- Tier
- bronze
- Chemistry
- Visium v1
- Magnification
- other
- Resolution
- 1,977 × 2,000 px
- mpp
- 3.453 µm/px
- Size
- 20.1 MB
- Sample ID
- GSM9254699
- License
- NCBI GEO policy
- Published
- Feb 2, 2026
Cite this dataset
doi.org/10.3389/fimmu.2026.1701776 ↗ BibTeX
@article{Ni_2026,
title = {Integrated spatial transcriptomics and single-cell RNA sequencing reveal Lars2-mediated spatiotemporal dynamics of myocardial remodeling in a mouse model of transverse aortic constriction},
volume = {17},
ISSN = {1664-3224},
url = {http://dx.doi.org/10.3389/fimmu.2026.1701776},
DOI = {10.3389/fimmu.2026.1701776},
journal = {Frontiers in Immunology},
publisher = {Frontiers Media SA},
author = {Ni, Hanwen and Liang, Feng and Huo, Huanhuan and Feng, Xuechao and He, Ben},
year = {2026},
month = Mar
}Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB