10x Xenium

Human skin of body

GSM9636817

bronze Interactive viewer cutaneous neuroendocrine carcinoma Provisional

Preview Client Lamin CLI

print(sdata)

SpatialData object
├── Images
│     └── 'morphology_mip': DataTree[cyx] (1, 20503, 22786), (1, 10251, 11393), (1, 5125, 5696), (1, 2562, 2848), (1, 1281, 1424)
├── Labels
│     ├── 'cell_labels': DataTree[yx] (16899, 21710), (8449, 10855), (4224, 5427), (2112, 2713), (1056, 1356)
│     └── 'nucleus_labels': DataTree[yx] (16853, 21665), (8426, 10832), (4213, 5416), (2106, 2708), (1053, 1354)
├── Points
│     └── 'transcripts': DataFrame with shape: (2582553, 13) (3D points)
├── Shapes
│     ├── 'cell_boundaries': GeoDataFrame shape: (51539, 1) (2D shapes)
│     ├── 'cell_circles': GeoDataFrame shape: (51539, 2) (2D shapes)
│     └── 'nucleus_boundaries': GeoDataFrame shape: (51539, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (51539, 480)
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)

Install (Python 3.12+) Docs →

Python · sddb client

from sddb import Catalog

ds = Catalog().dataset("26Fo6iDsILpxQ0MX0000")
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("26Fo6iDsILpxQ0MX")   # 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 26Fo6iDsILpxQ0MX0000 --dest data/

# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/26Fo6iDsILpxQ0MX

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid 26Fo6iDsILpxQ0MX

Install (Python 3.12+) Docs →

License: NCBI GEO policy

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Part of collection

Reprogramming engineered autologous T cells to overcome resistance in patients with Merkel cell carcinoma [Xenium]→

6 datasets · time course

Metadata

Technology: 10x Xenium
Organism: human
Tissue: skin of body
Condition: cutaneous neuroendocrine carcinoma
Modality: RNA
Observations (cells): 51,539
Transcripts: 2,582,553
Tier: bronze
Size: 563 MB
Sample ID: GSM9636817
License: NCBI GEO policy
Published: May 1, 2026

Cite this dataset

doi.org/10.1126/scitranslmed.aea8773 ↗

BibTeX

@article{geo:GSM9636817,
  doi = {10.1126/scitranslmed.aea8773},
  title = {GSM9636817},
  year = {2026}
}

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