Visium
Human skin of body
GSM9483977
bronze Interactive viewer H&E cutaneous leishmaniasis Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM9483977_P1_L_hires_image': DataArray[cyx] (3, 2000, 1986)
│ └── 'GSM9483977_P1_L_lowres_image': DataArray[cyx] (3, 600, 596)
├── Shapes
│ └── 'GSM9483977_P1_L': GeoDataFrame shape: (870, 2) (2D shapes)
└── Tables
└── 'table': AnnData (870, 17943)
with coordinate systems:
▸ 'GSM9483977_P1_L', with elements:
GSM9483977_P1_L_hires_image (Images), GSM9483977_P1_L_lowres_image (Images), GSM9483977_P1_L (Shapes)
▸ 'GSM9483977_P1_L_downscaled_hires', with elements:
GSM9483977_P1_L_hires_image (Images), GSM9483977_P1_L (Shapes)
▸ 'GSM9483977_P1_L_downscaled_lowres', with elements:
GSM9483977_P1_L_lowres_image (Images), GSM9483977_P1_L (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("XgW5WDDDqXSgZoxG") # 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/XgW5WDDDqXSgZoxG
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid XgW5WDDDqXSgZoxG Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["XgW5WDDDqXSgZoxG0000"])[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
- 870
- Tier
- bronze
- Chemistry
- Visium v1
- Magnification
- other
- Resolution
- 1,986 × 2,000 px
- mpp
- 3.532 µm/px
- Size
- 16 MB
- Sample ID
- GSM9483977
- 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