Visium
Mouse uterus
GSM8972899
bronze Interactive viewer H&E Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM8972899_control_1_hires_image': DataArray[cyx] (3, 1855, 2000)
│ └── 'GSM8972899_control_1_lowres_image': DataArray[cyx] (3, 557, 600)
├── Shapes
│ └── 'GSM8972899_control_1': GeoDataFrame shape: (1530, 2) (2D shapes)
└── Tables
└── 'table': AnnData (1530, 32285)
with coordinate systems:
▸ 'GSM8972899_control_1', with elements:
GSM8972899_control_1_hires_image (Images), GSM8972899_control_1_lowres_image (Images), GSM8972899_control_1 (Shapes)
▸ 'GSM8972899_control_1_downscaled_hires', with elements:
GSM8972899_control_1_hires_image (Images), GSM8972899_control_1 (Shapes)
▸ 'GSM8972899_control_1_downscaled_lowres', with elements:
GSM8972899_control_1_lowres_image (Images), GSM8972899_control_1 (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("4jgSdW843Cva5xdC0000")
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("4jgSdW843Cva5xdC") # 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 4jgSdW843Cva5xdC0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/4jgSdW843Cva5xdC
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid 4jgSdW843Cva5xdCLicense: NCBI GEO policy
Part of collection
Mouse uterine gene expressions during decidual processes [Visium]→ 4 datasets · comparison
Metadata
- Technology
- Visium
- Organism
- mouse
- Tissue
- uterus
- Modality
- RNA
- Observations (spots)
- 1,530
- Tier
- bronze
- Chemistry
- Visium v1
- Resolution
- 2,000 × 1,855 px
- mpp
- 3.622 µm/px
- Size
- 31.6 MB
- Sample ID
- GSM8972899
- License
- NCBI GEO policy
- Published
- Jun 3, 2026
Cite this dataset
doi.org/10.1073/pnas.2528309123 ↗ BibTeX
@article{He_2026,
title = {TAZ integrates ECM remodeling with uterine stromal differentiation to maintain early pregnancy},
volume = {123},
ISSN = {1091-6490},
url = {http://dx.doi.org/10.1073/pnas.2528309123},
DOI = {10.1073/pnas.2528309123},
number = {21},
journal = {Proceedings of the National Academy of Sciences},
publisher = {National Academy of Sciences},
author = {He, Xueting and Aikawa, Shizu and Fukui, Yamato and Ishizawa, Chihiro and Shimizu-Hirota, Ryoko and Hiratsuka, Daiki and Hiraoka, Takehiro and Matsuo, Mitsunori and Hirota, Yasushi},
year = {2026},
month = May
}Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB