Visium

Mouse skin of face

GSM8745174

bronze Interactive viewer H&E Provisional

Preview Client Lamin CLI

print(sdata)

SpatialData object
├── Images
│     ├── 'GSM8745174_F_POD4_hires_image': DataArray[cyx] (3, 2000, 1819)
│     └── 'GSM8745174_F_POD4_lowres_image': DataArray[cyx] (3, 600, 546)
├── Shapes
│     └── 'GSM8745174_F_POD4': GeoDataFrame shape: (1141, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (1141, 32285)
with coordinate systems:
    ▸ 'GSM8745174_F_POD4', with elements:
        GSM8745174_F_POD4_hires_image (Images), GSM8745174_F_POD4_lowres_image (Images), GSM8745174_F_POD4 (Shapes)
    ▸ 'GSM8745174_F_POD4_downscaled_hires', with elements:
        GSM8745174_F_POD4_hires_image (Images), GSM8745174_F_POD4 (Shapes)
    ▸ 'GSM8745174_F_POD4_downscaled_lowres', with elements:
        GSM8745174_F_POD4_lowres_image (Images), GSM8745174_F_POD4 (Shapes)

Install (Python 3.12+) Docs →

Python · sddb client

from sddb import Catalog

ds = Catalog().dataset("9ccqgFB1Roc6az180000")
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("9ccqgFB1Roc6az18")   # 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 9ccqgFB1Roc6az180000 --dest data/

# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/9ccqgFB1Roc6az18

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid 9ccqgFB1Roc6az18

Install (Python 3.12+) Docs →

License: NCBI GEO policy

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

Part of collection

Gas6-Axl signaling drives oral regenerative wound repair→

4 datasets · comparison

Metadata

Technology: Visium
Organism: mouse
Tissue: skin of face
Modality: RNA
Observations (spots): 1,141
Tier: bronze
Chemistry: Visium v1
Resolution: 1,819 × 2,000 px
mpp: 4.049 µm/px
Size: 17.4 MB
Sample ID: GSM8745174
License: NCBI GEO policy
Published: Apr 30, 2025

Cite this dataset

doi.org/10.1126/scitranslmed.adk2101 ↗

BibTeX

@article{Griffin_2025,
  title = {Growth arrest specific–6 and angiotoxin receptor–like signaling drive oral regenerative wound repair},
  volume = {17},
  ISSN = {1946-6242},
  url = {http://dx.doi.org/10.1126/scitranslmed.adk2101},
  DOI = {10.1126/scitranslmed.adk2101},
  number = {805},
  journal = {Science Translational Medicine},
  publisher = {American Association for the Advancement of Science (AAAS)},
  author = {Griffin, Michelle F. and Cook, Jessica and Morgan, Annah and Boffelli, Dario and Downer, Mauricio and Spielman, Amanda F. and Guardino, Nicholas J. and Guo, Jason L. and Parker, Jennifer B. L. and Januszyk, Michael and Valencia, Caleb and Kuhnert, Maxwell and Lu, John and Zwick, Rachel and Wan, Derrick C. and Klein, Ophir D. and Longaker, Michael T.},
  year = {2025},
  month = July
}

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