Visium

Human cornea

GSM9116177

bronze Interactive viewer H&E Provisional

Preview Client Lamin CLI

print(sdata)

SpatialData object
├── Images
│     ├── 'GSM9116177_C4_hires_image': DataArray[cyx] (3, 1986, 2000)
│     └── 'GSM9116177_C4_lowres_image': DataArray[cyx] (3, 596, 600)
├── Shapes
│     └── 'GSM9116177_C4': GeoDataFrame shape: (2357, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (2357, 36601)
with coordinate systems:
    ▸ 'GSM9116177_C4', with elements:
        GSM9116177_C4_hires_image (Images), GSM9116177_C4_lowres_image (Images), GSM9116177_C4 (Shapes)
    ▸ 'GSM9116177_C4_downscaled_hires', with elements:
        GSM9116177_C4_hires_image (Images), GSM9116177_C4 (Shapes)
    ▸ 'GSM9116177_C4_downscaled_lowres', with elements:
        GSM9116177_C4_lowres_image (Images), GSM9116177_C4 (Shapes)

Install (Python 3.12+) Docs →

Python · sddb client

from sddb import Catalog

ds = Catalog().dataset("TokVAy5YnrD9TIar0000")
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("TokVAy5YnrD9TIar")   # 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 TokVAy5YnrD9TIar0000 --dest data/

# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/TokVAy5YnrD9TIar

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid TokVAy5YnrD9TIar

Install (Python 3.12+) Docs →

License: NCBI GEO policy

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

Part of collection

Eye-conic' spatial transcriptomics of keratoconus corneas→

13 datasets · comparison

Metadata

Technology: Visium
Organism: human
Tissue: cornea
Modality: RNA
Observations (spots): 2,357
Tier: bronze
Chemistry: Visium v1
Resolution: 2,000 × 1,986 px
mpp: 3.870 µm/px
Size: 11.2 MB
Sample ID: GSM9116177
License: NCBI GEO policy
Published: Apr 3, 2026

Cite this dataset

doi.org/10.1167/iovs.67.4.7 ↗

BibTeX

@article{Wysocka_2026,
  title = {“Eye-Conic” Spatial Transcriptomics Reveals the Layer-Specific Molecular Alterations in Corneas of Patients With Keratoconus},
  volume = {67},
  ISSN = {1552-5783},
  url = {http://dx.doi.org/10.1167/iovs.67.4.7},
  DOI = {10.1167/iovs.67.4.7},
  number = {4},
  journal = {Investigative Ophthalmology &amp; Visual Science},
  publisher = {Association for Research in Vision and Ophthalmology (ARVO)},
  author = {Wysocka, Alicja and Jaskiewicz-Rajewicz, Katarzyna and Wozniak, Jakub and Rydzanicz, Malgorzata and Ploski, Rafal and Udziela, Monika and Szaflik, Jacek P. and Gajecka, Marzena},
  year = {2026},
  month = Apr,
  pages = {7}
}

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