Visium

Mouse spinal cord

GSM8314106

bronze Interactive viewer H&E Provisional

Preview Client Lamin CLI

print(sdata)

SpatialData object
├── Images
│     ├── 'GSM8314106_SC1_hires_image': DataArray[cyx] (3, 2000, 2000)
│     └── 'GSM8314106_SC1_lowres_image': DataArray[cyx] (3, 600, 600)
├── Shapes
│     └── 'GSM8314106_SC1': GeoDataFrame shape: (4992, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (4992, 32285)
with coordinate systems:
    ▸ 'GSM8314106_SC1', with elements:
        GSM8314106_SC1_hires_image (Images), GSM8314106_SC1_lowres_image (Images), GSM8314106_SC1 (Shapes)
    ▸ 'GSM8314106_SC1_downscaled_hires', with elements:
        GSM8314106_SC1_hires_image (Images), GSM8314106_SC1 (Shapes)
    ▸ 'GSM8314106_SC1_downscaled_lowres', with elements:
        GSM8314106_SC1_lowres_image (Images), GSM8314106_SC1 (Shapes)

Install (Python 3.12+) Docs →

Python · sddb client

from sddb import Catalog

ds = Catalog().dataset("q03ioXmET35QeMGa0000")
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("q03ioXmET35QeMGa")   # 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 q03ioXmET35QeMGa0000 --dest data/

# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/q03ioXmET35QeMGa

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid q03ioXmET35QeMGa

Install (Python 3.12+) Docs →

License: NCBI GEO policy

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

Part of collection

Spatial characterization of the transcriptome of the adult healthy and mutant FUS mouse spinal cords [Spatial transcriptomics]→

4 datasets · other

Metadata

Technology: Visium
Organism: mouse
Tissue: spinal cord
Modality: RNA
Observations (spots): 4,992
Tier: bronze
Chemistry: Visium v1
Magnification: other
Resolution: 2,000 × 2,000 px
mpp: 4.059 µm/px
Size: 11.8 MB
Sample ID: GSM8314106
License: NCBI GEO policy
Published: Jan 8, 2026

Cite this dataset

doi.org/10.1038/s41593-025-02101-2 ↗

BibTeX

@article{Piol_2025,
  title = {Axonal Eif5a hypusination controls local translation and mitigates defects in FUS-ALS},
  volume = {29},
  ISSN = {1546-1726},
  url = {http://dx.doi.org/10.1038/s41593-025-02101-2},
  DOI = {10.1038/s41593-025-02101-2},
  number = {1},
  journal = {Nature Neuroscience},
  publisher = {Springer Science and Business Media LLC},
  author = {Piol, Diana and Khalil, Bilal and Robberechts, Tessa and Killian, Theo and Georgopoulou, Maria and Partel, Gabriele and Wouters, David and Hecker, Nikolai and Tziortzouda, Paraskevi and Verresen, Yana and Corthout, Nikky and Kint, Sam and Vandereyken, Katy and Van Damme, Philip and Voet, Thierry and Davie, Kristofer and Poovathingal, Suresh and Van Den Bosch, Ludo and Aerts, Stein and Sifrim, Alejandro and Da Cruz, Sandrine},
  year = {2025},
  month = Dec,
  pages = {53–66}
}

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