Visium

Mouse brain

GSM9517480

silver Interactive viewer H&E ✓ Verified publication

Preview Download via Python Download via CLI Load via sddb

print(sdata)

SpatialData object
├── Images
│     ├── 'GSM9517480_P3-58699_full_image': DataTree[cyx] (3, 3000, 3000), (3, 1500, 1500), (3, 750, 750), (3, 375, 375), (3, 187, 187)
│     ├── 'GSM9517480_P3-58699_hires_image': DataArray[cyx] (3, 2000, 1472)
│     └── 'GSM9517480_P3-58699_lowres_image': DataArray[cyx] (3, 600, 442)
├── Shapes
│     └── 'GSM9517480_P3-58699': GeoDataFrame shape: (4530, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (4530, 19465)
with coordinate systems:
    ▸ 'GSM9517480_P3-58699', with elements:
        GSM9517480_P3-58699_full_image (Images), GSM9517480_P3-58699_hires_image (Images), GSM9517480_P3-58699_lowres_image (Images), GSM9517480_P3-58699 (Shapes)
    ▸ 'GSM9517480_P3-58699_downscaled_hires', with elements:
        GSM9517480_P3-58699_hires_image (Images), GSM9517480_P3-58699 (Shapes)
    ▸ 'GSM9517480_P3-58699_downscaled_lowres', with elements:
        GSM9517480_P3-58699_lowres_image (Images), GSM9517480_P3-58699 (Shapes)

Load in Python

import lamindb as ln

db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("mUruFcVXJCBsTZL2")   # 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

Load from the CLI

# one-shot: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/mUruFcVXJCBsTZL2

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid mUruFcVXJCBsTZL2

Load with the Python client

# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog

ds = Catalog().cohort(uids=["mUruFcVXJCBsTZL20000"])[0]
ds.elements()                 # inspect without downloading
sdata = ds.load(lazy=False)   # copy to the local cache and open

Docs: finding & loading data →

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

Part of collection

Mapping the Secondary Response to Traumatic Brain Injury Using Spatial Transcriptomics Shows Acute 4-aminopyridine Treatment Mitigates Axonal and Molecular Pathology→

24 datasets · comparison

Metadata

Technology: Visium
Organism: mouse
Tissue: brain
Modality: RNA
Observations: 4,530
Tier: silver
Chemistry: Visium CytAssist v2
Resolution: 1,472 × 2,000 px
mpp: 4.370 µm/px
Size: 152 MB
Sample ID: GSM9517480
License: NCBI GEO policy
Published: Feb 12, 2026

Cite this dataset

doi.org/10.1186/s40478-025-02219-1 ↗

BibTeX

@article{Sullivan_2026,
  title = {Mapping the secondary response to traumatic brain injury using spatial transcriptomics shows acute 4-aminopyridine treatment mitigates axonal and molecular pathology},
  volume = {14},
  ISSN = {2051-5960},
  url = {http://dx.doi.org/10.1186/s40478-025-02219-1},
  DOI = {10.1186/s40478-025-02219-1},
  number = {1},
  journal = {Acta Neuropathologica Communications},
  publisher = {Springer Science and Business Media LLC},
  author = {Sullivan, Genevieve M. and Radomski, Kryslaine L. and He, Shaoqiu and Wilkerson, Matthew D. and Dalgard, Clifton L. and Alba, Camille and Zi, Xiaomei and Doughty, Martin L. and Armstrong, Regina C.},
  year = {2026},
  month = Jan
}

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