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Visium

Human zone of skin

GSM9338172

silver Interactive viewer H&E systemic sclerosis ✓ Verified publication
Human zone of skin preview
print(sdata) 
SpatialData object
├── Images
│     ├── 'GSM9338172_SSC2_full_image': DataTree[cyx] (3, 3000, 3000), (3, 1500, 1500), (3, 750, 750), (3, 375, 375), (3, 187, 187)
│     ├── 'GSM9338172_SSC2_hires_image': DataArray[cyx] (3, 2000, 2000)
│     └── 'GSM9338172_SSC2_lowres_image': DataArray[cyx] (3, 600, 600)
├── Shapes
│     └── 'GSM9338172_SSC2': GeoDataFrame shape: (4925, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (4925, 37082)
with coordinate systems:
    ▸ 'GSM9338172_SSC2', with elements:
        GSM9338172_SSC2_full_image (Images), GSM9338172_SSC2_hires_image (Images), GSM9338172_SSC2_lowres_image (Images), GSM9338172_SSC2 (Shapes)
    ▸ 'GSM9338172_SSC2_downscaled_hires', with elements:
        GSM9338172_SSC2_hires_image (Images), GSM9338172_SSC2 (Shapes)
    ▸ 'GSM9338172_SSC2_downscaled_lowres', with elements:
        GSM9338172_SSC2_lowres_image (Images), GSM9338172_SSC2 (Shapes)
Install (Python 3.12+) Docs →
Python · sddb client 
from sddb import Catalog

ds = Catalog().dataset("ChVEyCG6WpGXmu160000")
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("ChVEyCG6WpGXmu16")   # 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 ChVEyCG6WpGXmu160000 --dest data/

# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/ChVEyCG6WpGXmu16

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid ChVEyCG6WpGXmu16
Install (Python 3.12+) Docs →

License: CC BY 4.0

View on Lamin ↗ Open in Vitessce ↗ Flag a data issue
Part of collection
Single-nuclei multiome and spatial analyses of early, untreated SSc skin identify a proinflammatory vascular niche of macrophage-fibroblast signaling→
10 datasets · other

Metadata

Technology
Visium
Organism
human
Tissue
zone of skin
Condition
systemic sclerosis
Modality
RNA
Observations (spots)
4,925
Tier
silver
Chemistry
Visium CytAssist v2
Resolution
2,000 × 2,000 px
mpp
2.959 µm/px
Size
34.9 MB
Sample ID
GSM9338172
License
CC BY 4.0
Published
Dec 12, 2025

Cite this dataset

doi.org/10.1172/jci.insight.198954 ↗
BibTeX 
@article{Jarnagin_2025,
  title = {Multimodal analyses of early, untreated systemic sclerosis skin identify a proinflammatory vascular niche of macrophage-fibroblast signaling},
  volume = {11},
  ISSN = {2379-3708},
  url = {http://dx.doi.org/10.1172/jci.insight.198954},
  DOI = {10.1172/jci.insight.198954},
  number = {3},
  journal = {JCI Insight},
  publisher = {American Society for Clinical Investigation},
  author = {Jarnagin, Helen C. and Parvizi, Rezvan and Gong, Zhiyun and Gedert, Rosemary and Xing, Xianying and Tsoi, Lam (Alex) C. and Bogle, Rachael and Morrisson, Madeline J. and Perreard, Laurent and Pioli, Patricia A. and Kolling, Fred and Gudjonsson, Johann E. and Khanna, Dinesh and Whitfield, Michael L.},
  year = {2025},
  month = Dec
}

Source: NCBI GEO ↗ · License: CC BY 4.0 ↗ · Reprocessed to SpatialData by SpatialData-DB