Visium
Human ovary
GSM8413264
bronze Interactive viewer H&E ovarian squamous cell carcinoma Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM8413264_Cancer_2_hires_image': DataArray[cyx] (3, 2000, 1817)
│ └── 'GSM8413264_Cancer_2_lowres_image': DataArray[cyx] (3, 600, 545)
├── Shapes
│ └── 'GSM8413264_Cancer_2': GeoDataFrame shape: (2750, 2) (2D shapes)
└── Tables
└── 'table': AnnData (2750, 36601)
with coordinate systems:
▸ 'GSM8413264_Cancer_2', with elements:
GSM8413264_Cancer_2_hires_image (Images), GSM8413264_Cancer_2_lowres_image (Images), GSM8413264_Cancer_2 (Shapes)
▸ 'GSM8413264_Cancer_2_downscaled_hires', with elements:
GSM8413264_Cancer_2_hires_image (Images), GSM8413264_Cancer_2 (Shapes)
▸ 'GSM8413264_Cancer_2_downscaled_lowres', with elements:
GSM8413264_Cancer_2_lowres_image (Images), GSM8413264_Cancer_2 (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("8zp9FVbFTQNlmryY0000")
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("8zp9FVbFTQNlmryY") # 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 8zp9FVbFTQNlmryY0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/8zp9FVbFTQNlmryY
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid 8zp9FVbFTQNlmryYLicense: NCBI GEO policy
Part of collection
Spatial transcriptome analysis for squamous cell carcinoma arising from mature teratoma→ 4 datasets · replicates
Metadata
- Technology
- Visium
- Organism
- human
- Tissue
- ovary
- Condition
- ovarian squamous cell carcinoma
- Modality
- RNA
- Observations (spots)
- 2,750
- Tier
- bronze
- Chemistry
- Visium v1
- Magnification
- other
- Resolution
- 1,817 × 2,000 px
- mpp
- 4.046 µm/px
- Size
- 33.3 MB
- Sample ID
- GSM8413264
- License
- NCBI GEO policy
- Published
- Mar 21, 2025
Cite this dataset
doi.org/10.1111/cas.70022 ↗ BibTeX
@article{Yoshida_2025,
title = {Single‐Nucleus <scp>RNA</scp> Sequencing and Spatial Transcriptomics for Squamous Cell Carcinoma Arising From Ovarian Mature Teratoma},
volume = {116},
ISSN = {1349-7006},
url = {http://dx.doi.org/10.1111/cas.70022},
DOI = {10.1111/cas.70022},
number = {5},
journal = {Cancer Science},
publisher = {Wiley},
author = {Yoshida, Kosuke and Yokoi, Akira and Suzuki, Hironori and Tamauchi, Satoshi and Kitagawa, Masami and Inami, Eri and Nakayama, Jun and Mori, Yutaro and Okamoto, Koji and Suzuki, Yutaka and Yoshida, Hiroshi and Kato, Tomoyasu and Kajiyama, Hiroaki and Yamamoto, Yusuke},
year = {2025},
month = Feb,
pages = {1339–1351}
}Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB