Visium
Human ovary
GSM9807708
silver Interactive viewer H&E ovarian serous adenocarcinoma No linked publication
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM9807708_TMA_1-A_hires_image': DataArray[cyx] (3, 3292, 4000)
│ └── 'GSM9807708_TMA_1-A_lowres_image': DataArray[cyx] (3, 494, 600)
├── Shapes
│ └── 'GSM9807708_TMA_1-A': GeoDataFrame shape: (4674, 2) (2D shapes)
└── Tables
└── 'table': AnnData (4674, 18132)
with coordinate systems:
▸ 'GSM9807708_TMA_1-A', with elements:
GSM9807708_TMA_1-A_hires_image (Images), GSM9807708_TMA_1-A_lowres_image (Images), GSM9807708_TMA_1-A (Shapes)
▸ 'GSM9807708_TMA_1-A_downscaled_hires', with elements:
GSM9807708_TMA_1-A_hires_image (Images), GSM9807708_TMA_1-A (Shapes)
▸ 'GSM9807708_TMA_1-A_downscaled_lowres', with elements:
GSM9807708_TMA_1-A_lowres_image (Images), GSM9807708_TMA_1-A (Shapes) Load in Python
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
artifact = db.Artifact.get("a6IhS6yZFQ5RZh5X") # 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/a6IhS6yZFQ5RZh5X
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid a6IhS6yZFQ5RZh5X Load with the Python client
# pip install git+https://github.com/theislab/spatialdata-db-client
from sddb import Catalog
ds = Catalog().cohort(uids=["a6IhS6yZFQ5RZh5X0000"])[0]
ds.elements() # inspect without downloading
sdata = ds.load(lazy=False) # copy to the local cache and openPart of collection
Spatial transcriptomic analysis of patient- and cell line-derived high grade serous ovarian cancer spheroids→ 2 datasets · other
Metadata
- Technology
- Visium
- Organism
- human
- Tissue
- ovary
- Condition
- ovarian serous adenocarcinoma
- Modality
- RNA
- Observations
- 4,674
- Tier
- silver
- Chemistry
- Visium v1
- Resolution
- 4,000 × 3,292 px
- mpp
- 3.135 µm/px
- Size
- 38 MB
- Sample ID
- GSM9807708
- License
- unknown
- Published
- Jun 16, 2026
Cite this dataset
No linked publication found — please cite the data source: NCBI GEO ↗.
Source: NCBI GEO ↗ · Reprocessed to SpatialData by SpatialData-DB