10x Xenium

Human ascending aorta

GSM9485373

bronze Interactive viewer aortic valve stenosis Provisional

Preview Client Lamin CLI

print(sdata)

SpatialData object
├── Labels
│     ├── 'cell_labels': DataTree[yx] (40954, 41707), (20477, 20853), (10238, 10426), (5119, 5213), (2559, 2606)
│     └── 'nucleus_labels': DataTree[yx] (40814, 41567), (20407, 20783), (10203, 10391), (5101, 5195), (2550, 2597)
├── Points
│     └── 'transcripts': DataFrame with shape: (2427484, 10) (3D points)
├── Shapes
│     ├── 'cell_boundaries': GeoDataFrame shape: (35491, 1) (2D shapes)
│     ├── 'cell_circles': GeoDataFrame shape: (35491, 2) (2D shapes)
│     └── 'nucleus_boundaries': GeoDataFrame shape: (35491, 1) (2D shapes)
└── Tables
      └── 'table': AnnData (35491, 377)
with coordinate systems:
    ▸ 'global', with elements:
        cell_labels (Labels), nucleus_labels (Labels), transcripts (Points), cell_boundaries (Shapes), cell_circles (Shapes), nucleus_boundaries (Shapes)

Install (Python 3.12+) Docs →

Python · sddb client

from sddb import Catalog

ds = Catalog().dataset("GJs0gpw3oQ3gM1ma0000")
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("GJs0gpw3oQ3gM1ma")   # 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 GJs0gpw3oQ3gM1ma0000 --dest data/

# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/GJs0gpw3oQ3gM1ma

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid GJs0gpw3oQ3gM1ma

Install (Python 3.12+) Docs →

License: NCBI GEO policy

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Part of collection

Spatial gene expression profiling of aortitis samples.→

10 datasets · comparison

Metadata

Technology: 10x Xenium
Organism: human
Tissue: ascending aorta
Condition: aortic valve stenosis
Modality: RNA
Observations (cells): 35,491
Transcripts: 2,427,484
Tier: bronze
Size: 134 MB
Sample ID: GSM9485373
License: NCBI GEO policy
Published: Feb 5, 2026

Cite this dataset

doi.org/10.1172/jci.insight.200255 ↗

BibTeX

@article{geo:GSM9485373,
  doi = {10.1172/jci.insight.200255},
  title = {GSM9485373},
  year = {2026}
}

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