10x Xenium
Human pelvic lymph node
GSM9636819
bronze Interactive viewer cutaneous neuroendocrine carcinoma Provisional
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) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("POK6NlJAsa1EGirN") # 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 Load from the CLI
# one-shot: 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 Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["POK6NlJAsa1EGirN0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart 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
- 106,368
- Transcripts
- 28,824,042
- Tier
- bronze
- Size
- 1.3 GB
- Sample ID
- GSM9636819
- License
- unknown
- Published
- May 1, 2026
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB