Visium
Human bone element
GSM8875086
bronze Interactive viewer H&E osteosarcoma Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM8875086_MR11A_hires_image': DataArray[cyx] (3, 1979, 2000)
│ └── 'GSM8875086_MR11A_lowres_image': DataArray[cyx] (3, 594, 600)
├── Shapes
│ └── 'GSM8875086_MR11A': GeoDataFrame shape: (4352, 2) (2D shapes)
└── Tables
└── 'table': AnnData (4352, 17922)
with coordinate systems:
▸ 'GSM8875086_MR11A', with elements:
GSM8875086_MR11A_hires_image (Images), GSM8875086_MR11A_lowres_image (Images), GSM8875086_MR11A (Shapes)
▸ 'GSM8875086_MR11A_downscaled_hires', with elements:
GSM8875086_MR11A_hires_image (Images), GSM8875086_MR11A (Shapes)
▸ 'GSM8875086_MR11A_downscaled_lowres', with elements:
GSM8875086_MR11A_lowres_image (Images), GSM8875086_MR11A (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("UMKLKrIzG8Ec85aJ") # 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/UMKLKrIzG8Ec85aJ
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid UMKLKrIzG8Ec85aJ Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["UMKLKrIzG8Ec85aJ0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
Spatial transcriptomic atlas of aggressive osteosarcomas reveals shared gene surface expression and immune landscape.→ 26 datasets · comparison
Metadata
- Technology
- Visium
- Organism
- human
- Tissue
- bone element
- Condition
- osteosarcoma
- Modality
- RNA
- Observations
- 4,352
- Tier
- bronze
- Chemistry
- Visium v1
- Magnification
- other
- Resolution
- 2,000 × 1,979 px
- mpp
- 3.435 µm/px
- Size
- 20 MB
- Sample ID
- GSM8875086
- License
- unknown
- Published
- Apr 10, 2026
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB