10x Xenium
Human skin of body
GSM9079631
silver Interactive viewer acne No linked publication
print(sdata)
SpatialData object
├── Images
│ └── 'morphology_mip': DataTree[cyx] (1, 20588, 23057), (1, 10294, 11528), (1, 5147, 5764), (1, 2573, 2882), (1, 1286, 1441)
├── Labels
│ ├── 'cell_labels': DataTree[yx] (19872, 22449), (9936, 11224), (4968, 5612), (2484, 2806), (1242, 1403)
│ └── 'nucleus_labels': DataTree[yx] (19248, 22128), (9624, 11064), (4812, 5532), (2406, 2766), (1203, 1383)
├── Points
│ └── 'transcripts': DataFrame with shape: (732910, 11) (3D points)
├── Shapes
│ ├── 'cell_boundaries': GeoDataFrame shape: (6679, 1) (2D shapes)
│ ├── 'cell_circles': GeoDataFrame shape: (6679, 2) (2D shapes)
│ └── 'nucleus_boundaries': GeoDataFrame shape: (6625, 2) (2D shapes)
└── Tables
└── 'table': AnnData (6679, 100)
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("LdeKmdZkygSqNla2") # 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/LdeKmdZkygSqNla2
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid LdeKmdZkygSqNla2 Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["LdeKmdZkygSqNla20000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openMetadata
- Technology
- 10x Xenium
- Organism
- human
- Tissue
- skin of body
- Condition
- acne
- Modality
- RNA
- Observations
- 6,679
- Transcripts
- 732,910
- Tier
- silver
- Size
- 394 MB
- Sample ID
- GSM9079631
- License
- unknown
- Published
- Dec 3, 2025
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB