Visium

Human skin of body

GSM9483975

bronze H&E cutaneous leishmaniasis Provisional

Preview Client Lamin CLI

print(sdata)

SpatialData object
├── Images
│     ├── 'GSM9483975_P5_L_hires_image': DataArray[cyx] (3, 1942, 2000)
│     └── 'GSM9483975_P5_L_lowres_image': DataArray[cyx] (3, 583, 600)
├── Shapes
│     └── 'GSM9483975_P5_L': GeoDataFrame shape: (544, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (544, 17943)
with coordinate systems:
    ▸ 'GSM9483975_P5_L', with elements:
        GSM9483975_P5_L_hires_image (Images), GSM9483975_P5_L_lowres_image (Images), GSM9483975_P5_L (Shapes)
    ▸ 'GSM9483975_P5_L_downscaled_hires', with elements:
        GSM9483975_P5_L_hires_image (Images), GSM9483975_P5_L (Shapes)
    ▸ 'GSM9483975_P5_L_downscaled_lowres', with elements:
        GSM9483975_P5_L_lowres_image (Images), GSM9483975_P5_L (Shapes)

Install (Python 3.12+) Docs →

Python · sddb client

from sddb import Catalog

ds = Catalog().dataset("iyrJ3lvmwvDoMHSd0001")
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("iyrJ3lvmwvDoMHSd")   # 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 iyrJ3lvmwvDoMHSd0001 --dest data/

# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/iyrJ3lvmwvDoMHSd

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid iyrJ3lvmwvDoMHSd

Install (Python 3.12+) Docs →

License: NCBI GEO policy

View on Lamin ↗ Flag a data issue

Part of collection

Spatial mapping of Ethiopian cutaneous leishmaniasis lesions reveals patient-defined immune signatures→

10 datasets · comparison

Metadata

Technology: Visium
Organism: human
Tissue: skin of body
Condition: cutaneous leishmaniasis
Modality: RNA
Observations (spots): 544
Tier: bronze
Chemistry: Visium v1
Resolution: 2,000 × 1,942 px
mpp: 3.639 µm/px
Size: 11.1 MB
Sample ID: GSM9483975
License: NCBI GEO policy
Published: Aug 12, 2026

Cite this dataset

doi.org/10.3389/fimmu.2026.1870524 ↗

BibTeX

@article{Dey_2026,
  title = {Spatial mapping of Ethiopian cutaneous leishmaniasis lesions reveals distinct tissue level immune programs},
  volume = {17},
  ISSN = {1664-3224},
  url = {http://dx.doi.org/10.3389/fimmu.2026.1870524},
  DOI = {10.3389/fimmu.2026.1870524},
  journal = {Frontiers in Immunology},
  publisher = {Frontiers Media SA},
  author = {Dey, Nidhi S. and Pham, Thao-Thy and Dey, Shoumit and Kassa, Mekibib and Mekonnen, Tigist and Fikre, Helina and Monsieurs, Pieter and Consortium, Spatial CL and Pareyn, Myrthe and van Griensven, Johan and Domagalska, Malgorzata and Dujardin, Jean-Claude and Asres, Mezgebu Silamsaw and Woldetensay, Mikias and Kaye, Paul M. and Adriaensen, Wim},
  year = {2026},
  month = July
}

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