Visium
Human skin of body
GSM9483972
bronze Interactive viewer H&E cutaneous leishmaniasis Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM9483972_P3_NL_hires_image': DataArray[cyx] (3, 1958, 2000)
│ └── 'GSM9483972_P3_NL_lowres_image': DataArray[cyx] (3, 588, 600)
├── Shapes
│ └── 'GSM9483972_P3_NL': GeoDataFrame shape: (401, 2) (2D shapes)
└── Tables
└── 'table': AnnData (401, 17943)
with coordinate systems:
▸ 'GSM9483972_P3_NL', with elements:
GSM9483972_P3_NL_hires_image (Images), GSM9483972_P3_NL_lowres_image (Images), GSM9483972_P3_NL (Shapes)
▸ 'GSM9483972_P3_NL_downscaled_hires', with elements:
GSM9483972_P3_NL_hires_image (Images), GSM9483972_P3_NL (Shapes)
▸ 'GSM9483972_P3_NL_downscaled_lowres', with elements:
GSM9483972_P3_NL_lowres_image (Images), GSM9483972_P3_NL (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("kspZSdTlwnUYKrJ1") # 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/kspZSdTlwnUYKrJ1
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid kspZSdTlwnUYKrJ1 Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["kspZSdTlwnUYKrJ10000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
Spatial mapping of Ethiopian cutaneous leishmaniasis lesions reveals patient-defined immune signatures→ 10 datasets · comparison
Metadata
- Technology
- Visium
- Organism
- human
- Tissue
- skin of body
- Condition
- cutaneous leishmaniasis
- Modality
- RNA
- Observations
- 401
- Tier
- bronze
- Chemistry
- Visium v1
- Resolution
- 2,000 × 1,958 px
- mpp
- 3.502 µm/px
- Size
- 4.5 MB
- Sample ID
- GSM9483972
- License
- unknown
- Published
- Aug 12, 2026
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB