Visium
Mouse heart
GSM9527707
bronze Interactive viewer H&E heart failure Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM9527707_alpha_MHC_MerCreMer_Het_TOP2B_LSL_full_image': DataTree[cyx] (3, 3000, 3000), (3, 1500, 1500), (3, 750, 750), (3, 375, 375), (3, 187, 187)
│ ├── 'GSM9527707_alpha_MHC_MerCreMer_Het_TOP2B_LSL_hires_image': DataArray[cyx] (3, 2000, 2000)
│ └── 'GSM9527707_alpha_MHC_MerCreMer_Het_TOP2B_LSL_lowres_image': DataArray[cyx] (3, 600, 600)
├── Shapes
│ └── 'GSM9527707_alpha_MHC_MerCreMer_Het_TOP2B_LSL': GeoDataFrame shape: (924, 2) (2D shapes)
└── Tables
└── 'table': AnnData (924, 19465)
with coordinate systems:
▸ 'GSM9527707_alpha_MHC_MerCreMer_Het_TOP2B_LSL', with elements:
GSM9527707_alpha_MHC_MerCreMer_Het_TOP2B_LSL_full_image (Images), GSM9527707_alpha_MHC_MerCreMer_Het_TOP2B_LSL_hires_image (Images), GSM9527707_alpha_MHC_MerCreMer_Het_TOP2B_LSL_lowres_image (Images), GSM9527707_alpha_MHC_MerCreMer_Het_TOP2B_LSL (Shapes)
▸ 'GSM9527707_alpha_MHC_MerCreMer_Het_TOP2B_LSL_downscaled_hires', with elements:
GSM9527707_alpha_MHC_MerCreMer_Het_TOP2B_LSL_hires_image (Images), GSM9527707_alpha_MHC_MerCreMer_Het_TOP2B_LSL (Shapes)
▸ 'GSM9527707_alpha_MHC_MerCreMer_Het_TOP2B_LSL_downscaled_lowres', with elements:
GSM9527707_alpha_MHC_MerCreMer_Het_TOP2B_LSL_lowres_image (Images), GSM9527707_alpha_MHC_MerCreMer_Het_TOP2B_LSL (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("u4z6zqY5vKtTYEGX") # 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/u4z6zqY5vKtTYEGX
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid u4z6zqY5vKtTYEGX Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["u4z6zqY5vKtTYEGX0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
Spatial transcriptomic profiling of TOP2B-driven anthracycline-induced cardiotoxicity in mouse hearts→ 2 datasets · comparison
Metadata
- Technology
- Visium
- Organism
- mouse
- Tissue
- heart
- Condition
- heart failure
- Modality
- RNA
- Observations
- 924
- Tier
- bronze
- Chemistry
- Visium CytAssist v2
- Resolution
- 3,000 × 3,000 px
- mpp
- 3.680 µm/px
- Size
- 38 MB
- Sample ID
- GSM9527707
- License
- unknown
- Published
- Apr 8, 2026
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB