Visium
Mouse heart
GSM8645796
bronze Interactive viewer H&E Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM8645796_P2_E14_hires_image': DataArray[cyx] (3, 1986, 2000)
│ └── 'GSM8645796_P2_E14_lowres_image': DataArray[cyx] (3, 596, 600)
├── Shapes
│ └── 'GSM8645796_P2_E14': GeoDataFrame shape: (664, 2) (2D shapes)
└── Tables
└── 'table': AnnData (664, 32285)
with coordinate systems:
▸ 'GSM8645796_P2_E14', with elements:
GSM8645796_P2_E14_hires_image (Images), GSM8645796_P2_E14_lowres_image (Images), GSM8645796_P2_E14 (Shapes)
▸ 'GSM8645796_P2_E14_downscaled_hires', with elements:
GSM8645796_P2_E14_hires_image (Images), GSM8645796_P2_E14 (Shapes)
▸ 'GSM8645796_P2_E14_downscaled_lowres', with elements:
GSM8645796_P2_E14_lowres_image (Images), GSM8645796_P2_E14 (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("mLPPcpyvcIzxniiN0000")
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("mLPPcpyvcIzxniiN") # 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 mLPPcpyvcIzxniiN0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/mLPPcpyvcIzxniiN
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid mLPPcpyvcIzxniiNLicense: NCBI GEO policy
Part of collection
Spatial transcriptomic analysis of developing hearts at embryonic and neonatal stages→ 8 datasets · other
Metadata
- Technology
- Visium
- Organism
- mouse
- Tissue
- heart
- Modality
- RNA
- Observations (spots)
- 664
- Tier
- bronze
- Chemistry
- Visium v1
- Magnification
- other
- Resolution
- 2,000 × 1,986 px
- mpp
- 3.509 µm/px
- Size
- 15.1 MB
- Sample ID
- GSM8645796
- License
- NCBI GEO policy
- Published
- Apr 28, 2026
Cite this dataset
doi.org/10.1038/s42003-026-10259-z ↗ BibTeX
@article{Hu_2026,
title = {Spatial transcriptomic profiling of developing mouse hearts reveals a spatially patterned signaling environment},
volume = {9},
ISSN = {2399-3642},
url = {http://dx.doi.org/10.1038/s42003-026-10259-z},
DOI = {10.1038/s42003-026-10259-z},
number = {1},
journal = {Communications Biology},
publisher = {Springer Science and Business Media LLC},
author = {Hu, Junqi and He, Haoting and Xu, Juan and MacDonald, William A. and He, Yuanhang and Liu, Tianhao and Chen, Wei and Li, Guang},
year = {2026},
month = May
}Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB