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Visium

Human coronary artery

GSM9414345

bronze Interactive viewer H&E atherosclerosis Provisional
Human coronary artery preview
print(sdata)
SpatialData object
├── Images
│     ├── 'GSM9414345_T1071_hires_image': DataArray[cyx] (3, 1951, 2000)
│     └── 'GSM9414345_T1071_lowres_image': DataArray[cyx] (3, 585, 600)
├── Shapes
│     └── 'GSM9414345_T1071': GeoDataFrame shape: (1523, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (1523, 17943)
with coordinate systems:
    ▸ 'GSM9414345_T1071', with elements:
        GSM9414345_T1071_hires_image (Images), GSM9414345_T1071_lowres_image (Images), GSM9414345_T1071 (Shapes)
    ▸ 'GSM9414345_T1071_downscaled_hires', with elements:
        GSM9414345_T1071_hires_image (Images), GSM9414345_T1071 (Shapes)
    ▸ 'GSM9414345_T1071_downscaled_lowres', with elements:
        GSM9414345_T1071_lowres_image (Images), GSM9414345_T1071 (Shapes)
Python · sddb client
from sddb import Catalog

ds = Catalog().dataset("1LqbCsZ3o5PP2z3p0000")
ds.elements()          # inspect without downloading
sdata = ds.to_sdata()  # cached locally, reused
print(sdata)
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("1LqbCsZ3o5PP2z3p")   # 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
Shell
# sddb client: download the .zarr into data/
sddb-cli download 1LqbCsZ3o5PP2z3p0000 --dest data/

# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/1LqbCsZ3o5PP2z3p

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid 1LqbCsZ3o5PP2z3p

License: NCBI GEO policy

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

Metadata

Technology
Visium
Organism
human
Tissue
coronary artery
Condition
atherosclerosis
Modality
RNA
Observations (spots)
1,523
Tier
bronze
Chemistry
Visium v1
Resolution
2,000 × 1,951 px
mpp
3.752 µm/px
Size
11.6 MB
Sample ID
GSM9414345
License
NCBI GEO policy
Published
Feb 2, 2026

Cite this dataset

doi.org/10.1126/science.adx1736 ↗
BibTeX
@article{Amrute_2026,
  title = {Targeting modulated vascular smooth muscle cells in atherosclerosis via FAP-directed immunotherapy},
  volume = {392},
  ISSN = {1095-9203},
  url = {http://dx.doi.org/10.1126/science.adx1736},
  DOI = {10.1126/science.adx1736},
  number = {6793},
  journal = {Science},
  publisher = {American Association for the Advancement of Science (AAAS)},
  author = {Amrute, Junedh M. and Jung, In-Hyuk and Yamawaki, Tracy and Lin, Wen-Ling and Bredemeyer, Andrea and Diekmann, Johanna and Hayat, Sikander and Zhang, Xianglong and Wakefield, Devin L. and Luo, Xin and Maryam, Sidrah and Heo, Gyu Seong and Yang, Steven and Lee, Chang Jie Mick and Wang, Chen and Chou, Caroline and Kuppe, Christoph and Cook, Kevin D. and Kovacs, Atilla and Chintalgattu, Vishnu and Pruitt, Danielle and Barreda, Jose and Stitziel, Nathan O. and Cheng, Paul and Liu, Yongjian and Kramann, Rafael and Kreisel, Daniel and Foo, Roger S.-Y. and Rulifson, Ingrid C. and Martin, Scott and Grunert, David and Thomas, Melissa and Cui, Jixin and Quertermous, Thomas and Bengel, Frank M. and Jackson, Simon and Li, Chi-Ming and Ason, Brandon and Lavine, Kory J.},
  year = {2026},
  month = Apr
}

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