Visium

Macaque retina

GSM9151613

bronze Interactive viewer H&E uveitis Provisional

Preview Client Lamin CLI

print(sdata)

SpatialData object
├── Images
│     ├── 'GSM9151613_CR20_hires_image': DataArray[cyx] (3, 2000, 1952)
│     └── 'GSM9151613_CR20_lowres_image': DataArray[cyx] (3, 600, 586)
├── Shapes
│     └── 'GSM9151613_CR20': GeoDataFrame shape: (4875, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (4875, 26533)
with coordinate systems:
    ▸ 'GSM9151613_CR20', with elements:
        GSM9151613_CR20_hires_image (Images), GSM9151613_CR20_lowres_image (Images), GSM9151613_CR20 (Shapes)
    ▸ 'GSM9151613_CR20_downscaled_hires', with elements:
        GSM9151613_CR20_hires_image (Images), GSM9151613_CR20 (Shapes)
    ▸ 'GSM9151613_CR20_downscaled_lowres', with elements:
        GSM9151613_CR20_lowres_image (Images), GSM9151613_CR20 (Shapes)

Install (Python 3.12+) Docs →

Python · sddb client

from sddb import Catalog

ds = Catalog().dataset("ttO8rNCx1jnvFDZf0000")
ds.elements()          # inspect without downloading
sdata = ds.to_sdata()  # cached locally, reused
print(sdata)

Install (Python 3.12+) Docs →

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("ttO8rNCx1jnvFDZf")   # 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

Install (Python 3.12+) Docs →

Shell

# sddb client: download the .zarr into data/
sddb-cli download ttO8rNCx1jnvFDZf0000 --dest data/

# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/ttO8rNCx1jnvFDZf

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid ttO8rNCx1jnvFDZf

Install (Python 3.12+) Docs →

License: NCBI GEO policy

View on Lamin ↗ Open in Vitessce ↗ Flag a data issue

Part of collection

Single-cell and spatial transcriptomic analyses of gene therapy-associated retinal inflammation in non-human primates→

4 datasets · time course

Metadata

Technology: Visium
Organism: macaque
Tissue: retina
Condition: uveitis
Modality: RNA
Observations (spots): 4,875
Tier: bronze
Chemistry: Visium v1
Magnification: other
Resolution: 1,952 × 2,000 px
mpp: 3.667 µm/px
Size: 6.8 MB
Sample ID: GSM9151613
License: NCBI GEO policy
Published: Mar 30, 2026

Cite this dataset

doi.org/10.1016/j.omta.2026.201726 ↗

BibTeX

@article{Sourd_2026,
  title = {Single-cell and spatial transcriptomic analyses of gene therapy-associated retinal inflammation in non-human primates},
  volume = {34},
  ISSN = {3117-387X},
  url = {http://dx.doi.org/10.1016/j.omta.2026.201726},
  DOI = {10.1016/j.omta.2026.201726},
  number = {2},
  journal = {Molecular Therapy Advances},
  publisher = {Elsevier BV},
  author = {Sourd, Célia and Quinn, Joel and John, Molly C. and Martinez-Fernandez de la Camara, Cristina and Wickramasinghe, Lakshanie C. and Attar, Moustafa and Shamsnajafabadi, Hoda and Salman, Ahmed and Cowley, Sally A. and Dendrou, Calliope A. and MacLaren, Robert E. and Cehajic-Kapetanovic, Jasmina and Xue, Kanmin},
  year = {2026},
  month = June,
  pages = {201726}
}

Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB