Visium HD

Human skin of body

GSM9031942

silver Interactive viewer H&E pustulosis palmaris et plantaris ✓ Verified publication

Preview Client Lamin CLI

print(sdata)

SpatialData object
├── Images
│     ├── 'GSM9031942_square_002um_hires_image': DataArray[cyx] (3, 4082, 6000)
│     └── 'GSM9031942_square_002um_lowres_image': DataArray[cyx] (3, 408, 600)
├── Shapes
│     ├── 'GSM9031942_square_002um_square_002um': GeoDataFrame shape: (1311995, 1) (2D shapes)
│     ├── 'GSM9031942_square_002um_square_008um': GeoDataFrame shape: (84472, 1) (2D shapes)
│     ├── 'GSM9031942_square_002um_square_016um': GeoDataFrame shape: (21980, 1) (2D shapes)
│     └── 'GSM9031942_square_002um_square_016um_for_vitessce': GeoDataFrame shape: (21980, 2) (2D shapes)
└── Tables
      ├── 'square_002um': AnnData (1311995, 18085)
      ├── 'square_008um': AnnData (84472, 18085)
      └── 'square_016um': AnnData (21980, 18085)
with coordinate systems:
    ▸ 'GSM9031942_square_002um', with elements:
        GSM9031942_square_002um_hires_image (Images), GSM9031942_square_002um_lowres_image (Images), GSM9031942_square_002um_square_002um (Shapes), GSM9031942_square_002um_square_008um (Shapes), GSM9031942_square_002um_square_016um (Shapes), GSM9031942_square_002um_square_016um_for_vitessce (Shapes)
    ▸ 'GSM9031942_square_002um_downscaled_hires', with elements:
        GSM9031942_square_002um_hires_image (Images), GSM9031942_square_002um_square_002um (Shapes), GSM9031942_square_002um_square_008um (Shapes), GSM9031942_square_002um_square_016um (Shapes), GSM9031942_square_002um_square_016um_for_vitessce (Shapes)
    ▸ 'GSM9031942_square_002um_downscaled_lowres', with elements:
        GSM9031942_square_002um_lowres_image (Images), GSM9031942_square_002um_square_002um (Shapes), GSM9031942_square_002um_square_008um (Shapes), GSM9031942_square_002um_square_016um (Shapes), GSM9031942_square_002um_square_016um_for_vitessce (Shapes)

Install (Python 3.12+) Docs →

Python · sddb client

from sddb import Catalog

ds = Catalog().dataset("CSPSlmuINB8Omplh0000")
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("CSPSlmuINB8Omplh")   # 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 CSPSlmuINB8Omplh0000 --dest data/

# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/CSPSlmuINB8Omplh

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid CSPSlmuINB8Omplh

Install (Python 3.12+) Docs →

License: NCBI GEO policy

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

Part of collection

Immune Dynamics in Palmoplantar Pustulosis Unveiled by Single-Cell and High-Resolution Spatial Transcriptomics [Spatial Transcriptomics]→

2 datasets · publication

Metadata

Technology: Visium HD
Organism: human
Tissue: skin of body
Condition: pustulosis palmaris et plantaris
Modality: RNA
Observations (bins): 84,472
Tier: silver
Resolution: 6,000 × 4,082 px
mpp: 0.946 µm/px
Size: 220 MB
Sample ID: GSM9031942
License: NCBI GEO policy
Published: Mar 9, 2026

Cite this dataset

doi.org/10.1016/j.jaci.2026.01.028 ↗

BibTeX

@article{Lee_2026,
  title = {Single-cell and spatial transcriptomics unveil myeloid–lymphoid cross talk and the dermal immune niche underlying palmoplantar pustulosis},
  volume = {157},
  ISSN = {0091-6749},
  url = {http://dx.doi.org/10.1016/j.jaci.2026.01.028},
  DOI = {10.1016/j.jaci.2026.01.028},
  number = {6},
  journal = {Journal of Allergy and Clinical Immunology},
  publisher = {Elsevier BV},
  author = {Lee, Hanjae and Lee, Juyoung and Ahn, Hyeok and Park, Kyunghyuk and Cha, Bukyung and Lee, Cheol and Kwon, Ohsang and Jo, Seong Jin and Kim, Jong-Il},
  year = {2026},
  month = June,
  pages = {1339–1354}
}

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