10x Xenium

Human pelvic lymph node

GSM9636820

bronze Interactive viewer cutaneous neuroendocrine carcinoma Provisional

Preview Client Lamin CLI

print(sdata)

SpatialData object
├── Images
│     └── 'morphology_mip': DataTree[cyx] (1, 20521, 31294), (1, 10260, 15647), (1, 5130, 7823), (1, 2565, 3911), (1, 1282, 1955)
├── Labels
│     ├── 'cell_labels': DataTree[yx] (20038, 29660), (10019, 14830), (5009, 7415), (2504, 3707), (1252, 1853)
│     └── 'nucleus_labels': DataTree[yx] (19993, 29613), (9996, 14806), (4998, 7403), (2499, 3701), (1249, 1850)
├── Points
│     └── 'transcripts': DataFrame with shape: (12508654, 13) (3D points)
├── Shapes
│     ├── 'cell_boundaries': GeoDataFrame shape: (59563, 1) (2D shapes)
│     ├── 'cell_circles': GeoDataFrame shape: (59563, 2) (2D shapes)
│     └── 'nucleus_boundaries': GeoDataFrame shape: (59563, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (59563, 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("Bvfoh4orVFbdXoKL0000")
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("Bvfoh4orVFbdXoKL")   # 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 Bvfoh4orVFbdXoKL0000 --dest data/

# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/Bvfoh4orVFbdXoKL

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid Bvfoh4orVFbdXoKL

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: pelvic lymph node
Condition: cutaneous neuroendocrine carcinoma
Modality: RNA
Observations (cells): 59,563
Transcripts: 12,508,654
Tier: bronze
Size: 741 MB
Sample ID: GSM9636820
License: NCBI GEO policy
Published: May 1, 2026

Cite this dataset

doi.org/10.1126/scitranslmed.aea8773 ↗

BibTeX

@article{geo:GSM9636820,
  doi = {10.1126/scitranslmed.aea8773},
  title = {GSM9636820},
  year = {2026}
}

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