10x Xenium
Human pelvic lymph node
GSM9636820
bronze Interactive viewer cutaneous neuroendocrine carcinoma Provisional
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) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("Bvfoh4orVFbdXoKL") # 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/Bvfoh4orVFbdXoKL
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid Bvfoh4orVFbdXoKL Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["Bvfoh4orVFbdXoKL0000"])[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
- 59,563
- Transcripts
- 12,508,654
- Tier
- bronze
- Size
- 707 MB
- Sample ID
- GSM9636820
- 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