Visium
Mouse retina
GSM7916289
bronze Interactive viewer H&E Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM7916289_078_D1_hires_image': DataArray[cyx] (3, 2000, 1931)
│ └── 'GSM7916289_078_D1_lowres_image': DataArray[cyx] (3, 600, 579)
├── Shapes
│ └── 'GSM7916289_078_D1': GeoDataFrame shape: (733, 2) (2D shapes)
└── Tables
└── 'table': AnnData (733, 32285)
with coordinate systems:
▸ 'GSM7916289_078_D1', with elements:
GSM7916289_078_D1_hires_image (Images), GSM7916289_078_D1_lowres_image (Images), GSM7916289_078_D1 (Shapes)
▸ 'GSM7916289_078_D1_downscaled_hires', with elements:
GSM7916289_078_D1_hires_image (Images), GSM7916289_078_D1 (Shapes)
▸ 'GSM7916289_078_D1_downscaled_lowres', with elements:
GSM7916289_078_D1_lowres_image (Images), GSM7916289_078_D1 (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("rNQC5JYCaHxypnDm0000")
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("rNQC5JYCaHxypnDm") # 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 rNQC5JYCaHxypnDm0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/rNQC5JYCaHxypnDm
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid rNQC5JYCaHxypnDmLicense: NCBI GEO policy
Part of collection
Seeing the whole transcriptomics picture: Spatial gene expression analysis reveals photoreceptor stress as modulator of retinal vascular changes→ 7 datasets · comparison
Metadata
- Technology
- Visium
- Organism
- mouse
- Tissue
- retina
- Modality
- RNA
- Observations (spots)
- 733
- Tier
- bronze
- Chemistry
- Visium v1
- Magnification
- other
- Resolution
- 1,931 × 2,000 px
- mpp
- 3.673 µm/px
- Size
- 7.1 MB
- Sample ID
- GSM7916289
- License
- NCBI GEO policy
- Published
- Mar 3, 2025
Cite this dataset
doi.org/10.1038/s42003-025-07887-2 ↗ BibTeX
@article{Schumann_2025,
title = {Spatial transcriptomics reveals regionally altered gene expression that drives retinal degeneration},
volume = {8},
ISSN = {2399-3642},
url = {http://dx.doi.org/10.1038/s42003-025-07887-2},
DOI = {10.1038/s42003-025-07887-2},
number = {1},
journal = {Communications Biology},
publisher = {Springer Science and Business Media LLC},
author = {Schumann, Ulrike and Liu, Lixinyu and Aggio-Bruce, Riemke and Cioanca, Adrian V. and Shariev, Artur and Madigan, Michele C. and Valter, Krisztina and Wen, Jiayu and Natoli, Riccardo},
year = {2025},
month = Apr
}Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB