Visium
Human ovary
GSM8454235
bronze Interactive viewer H&E ovarian serous adenocarcinoma Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM8454235_Patient_8_hires_image': DataArray[cyx] (3, 1498, 2000)
│ └── 'GSM8454235_Patient_8_lowres_image': DataArray[cyx] (3, 450, 600)
├── Shapes
│ └── 'GSM8454235_Patient_8': GeoDataFrame shape: (4116, 2) (2D shapes)
└── Tables
└── 'table': AnnData (4116, 18085)
with coordinate systems:
▸ 'GSM8454235_Patient_8', with elements:
GSM8454235_Patient_8_hires_image (Images), GSM8454235_Patient_8_lowres_image (Images), GSM8454235_Patient_8 (Shapes)
▸ 'GSM8454235_Patient_8_downscaled_hires', with elements:
GSM8454235_Patient_8_hires_image (Images), GSM8454235_Patient_8 (Shapes)
▸ 'GSM8454235_Patient_8_downscaled_lowres', with elements:
GSM8454235_Patient_8_lowres_image (Images), GSM8454235_Patient_8 (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("DNH4rL9znRKbXTK50000")
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("DNH4rL9znRKbXTK5") # 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 DNH4rL9znRKbXTK50000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/DNH4rL9znRKbXTK5
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid DNH4rL9znRKbXTK5License: NCBI GEO policy
Part of collection
Spatial transcriptomics for platinum-resistant high-grade serous ovarian carcinoma→ 3 datasets · replicates
Metadata
- Technology
- Visium
- Organism
- human
- Tissue
- ovary
- Condition
- ovarian serous adenocarcinoma
- Modality
- RNA
- Observations (spots)
- 4,116
- Tier
- bronze
- Chemistry
- Visium v1
- Magnification
- other
- Resolution
- 2,000 × 1,498 px
- mpp
- 3.753 µm/px
- Size
- 108 MB
- Sample ID
- GSM8454235
- License
- NCBI GEO policy
- Published
- Sep 3, 2025
Cite this dataset
doi.org/10.1038/s42003-025-08771-9 ↗ BibTeX
@article{Suzuki_2025,
title = {Overcoming platinum-resistant ovarian cancer targeting the activated JAK-STAT pathways via extracellular vesicles},
volume = {8},
ISSN = {2399-3642},
url = {http://dx.doi.org/10.1038/s42003-025-08771-9},
DOI = {10.1038/s42003-025-08771-9},
number = {1},
journal = {Communications Biology},
publisher = {Springer Science and Business Media LLC},
author = {Suzuki, Kazuhiro and Yokoi, Akira and Yoshida, Kosuke and Suzuki, Hironori and Kitagawa, Masami and Asano-Inami, Eri and Matsuo, Seiko and Yoshihara, Masato and Tamauchi, Satoshi and Yoshikawa, Nobuhisa and Niimi, Kaoru and Sudo, Tamotsu and Yamaguchi, Satoshi and Yamamoto, Yusuke and Kajiyama, Hiroaki},
year = {2025},
month = Aug
}Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB