10x Xenium

Human pelvic lymph node

GSM9636819

bronze Interactive viewer cutaneous neuroendocrine carcinoma Provisional

Preview Client Lamin CLI

print(sdata)

SpatialData object
├── Images
│     └── 'morphology_mip': DataTree[cyx] (1, 40840, 48288), (1, 20420, 24144), (1, 10210, 12072), (1, 5105, 6036), (1, 2552, 3018)
├── Labels
│     ├── 'cell_labels': DataTree[yx] (38919, 47369), (19459, 23684), (9729, 11842), (4864, 5921), (2432, 2960)
│     └── 'nucleus_labels': DataTree[yx] (38873, 47323), (19436, 23661), (9718, 11830), (4859, 5915), (2429, 2957)
├── Points
│     └── 'transcripts': DataFrame with shape: (28824042, 13) (3D points)
├── Shapes
│     ├── 'cell_boundaries': GeoDataFrame shape: (106368, 1) (2D shapes)
│     ├── 'cell_circles': GeoDataFrame shape: (106368, 2) (2D shapes)
│     └── 'nucleus_boundaries': GeoDataFrame shape: (106368, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (106368, 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("POK6NlJAsa1EGirN0000")
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("POK6NlJAsa1EGirN")   # 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 POK6NlJAsa1EGirN0000 --dest data/

# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/POK6NlJAsa1EGirN

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid POK6NlJAsa1EGirN

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): 106,368
Transcripts: 28,824,042
Tier: bronze
Size: 1.4 GB
Sample ID: GSM9636819
License: NCBI GEO policy
Published: May 1, 2026

Cite this dataset

doi.org/10.1126/scitranslmed.aea8773 ↗

BibTeX

@article{geo:GSM9636819,
  doi = {10.1126/scitranslmed.aea8773},
  title = {GSM9636819},
  year = {2026}
}

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