10x Xenium
Human coronary artery
GSM9423579
bronze Interactive viewer atherosclerosis Provisional
print(sdata)
SpatialData object
├── Images
│ └── 'morphology_mip': DataTree[cyx] (1, 23918, 19973), (1, 11959, 9986), (1, 5979, 4993), (1, 2989, 2496), (1, 1494, 1248)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (23850, 19691), (11925, 9845), (5962, 4922), (2981, 2461), (1490, 1230)
│ └── 'nucleus_labels': DataTree[yx] (23848, 19657), (11924, 9828), (5962, 4914), (2981, 2457), (1490, 1228)
├── Points
│ └── 'transcripts': DataFrame with shape: (1066846, 13) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (10580, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (10580, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (10513, 2) (2D shapes)
└── Tables
└── 'table': AnnData (10580, 477)
with coordinate systems:
▸ 'global', with elements:
morphology_mip (Images), cell_labels (Labels), nucleus_labels (Labels), transcripts (Points), cell_boundaries (Shapes), cell_circles (Shapes), nucleus_boundaries (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("n9NqREwK11BuiaYR0000")
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("n9NqREwK11BuiaYR") # 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 n9NqREwK11BuiaYR0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/n9NqREwK11BuiaYR
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid n9NqREwK11BuiaYRLicense: NCBI GEO policy
Metadata
- Technology
- 10x Xenium
- Organism
- human
- Tissue
- coronary artery
- Condition
- atherosclerosis
- Modality
- RNA
- Observations (cells)
- 10,580
- Transcripts
- 1,066,846
- Tier
- bronze
- Size
- 431 MB
- Sample ID
- GSM9423579
- 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