Visium
Human head of femur
GSM9936742
silver Interactive viewer H&E osteoarthritis No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM9936742_HD-02_full_image': DataTree[cyx] (3, 3000, 3200), (3, 1500, 1600), (3, 750, 800), (3, 375, 400), (3, 187, 200)
│ ├── 'GSM9936742_HD-02_hires_image': DataArray[cyx] (3, 2770, 2707)
│ └── 'GSM9936742_HD-02_lowres_image': DataArray[cyx] (3, 600, 587)
├── Shapes
│ └── 'GSM9936742_HD-02': GeoDataFrame shape: (14400, 2) (2D shapes)
└── Tables
└── 'table': AnnData (14400, 18085)
with coordinate systems:
▸ 'GSM9936742_HD-02', with elements:
GSM9936742_HD-02_full_image (Images), GSM9936742_HD-02_hires_image (Images), GSM9936742_HD-02_lowres_image (Images), GSM9936742_HD-02 (Shapes)
▸ 'GSM9936742_HD-02_downscaled_hires', with elements:
GSM9936742_HD-02_hires_image (Images), GSM9936742_HD-02 (Shapes)
▸ 'GSM9936742_HD-02_downscaled_lowres', with elements:
GSM9936742_HD-02_lowres_image (Images), GSM9936742_HD-02 (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("qzSwmOf7s7QlKQBR0000")
ds.elements() # inspect without downloading
sdata = ds.to_sdata() # cached locally, reused
print(sdata) Python · lamindb
Needs pip install lamindb and network access to the Lamin database, which is limited during the alpha. If it fails, use the Client tab.
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("qzSwmOf7s7QlKQBR") # stem uid: Lamin resolves it to the 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 Shell
# sddb client: download the .zarr into data/
sddb-cli download qzSwmOf7s7QlKQBR0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/qzSwmOf7s7QlKQBR
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid qzSwmOf7s7QlKQBRLicense: NCBI GEO policy
Part of collection
Spatial transcriptomics reveals microenvironmental heterogeneity in osteoarthritic subchondral bone→ 4 datasets · other
Metadata
- Technology
- Visium
- Organism
- human
- Tissue
- head of femur
- Condition
- osteoarthritis
- Modality
- RNA
- Observations (spots)
- 14,400
- Tier
- silver
- Chemistry
- Visium CytAssist v2
- Resolution
- 3,200 × 3,000 px
- mpp
- 2.828 µm/px
- Size
- 50.5 MB
- Sample ID
- GSM9936742
- License
- NCBI GEO policy
- Published
- Aug 9, 2026
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB