10x Xenium
Human skin of body
GSM9636818
bronze Interactive viewer cutaneous neuroendocrine carcinoma Provisional
print(sdata)
SpatialData object
├── Images
│ └── 'morphology_mip': DataTree[cyx] (1, 47609, 25644), (1, 23804, 12822), (1, 11902, 6411), (1, 5951, 3205), (1, 2975, 1602)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (45841, 25583), (22920, 12791), (11460, 6395), (5730, 3197), (2865, 1598)
│ └── 'nucleus_labels': DataTree[yx] (45795, 25544), (22897, 12772), (11448, 6386), (5724, 3193), (2862, 1596)
├── Points
│ └── 'transcripts': DataFrame with shape: (35219941, 13) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (213088, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (213088, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (213088, 2) (2D shapes)
└── Tables
└── 'table': AnnData (213088, 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("gHOpZTOsGPHECkuK") # 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/gHOpZTOsGPHECkuK
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid gHOpZTOsGPHECkuK Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["gHOpZTOsGPHECkuK0000"])[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
- skin of body
- Condition
- cutaneous neuroendocrine carcinoma
- Modality
- RNA
- Observations
- 213,088
- Transcripts
- 35,219,941
- Tier
- bronze
- Size
- 1.4 GB
- Sample ID
- GSM9636818
- 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