Visium
Human breast
GSM9294639
bronze Interactive viewer H&E estrogen-receptor positive breast cancer Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM9294639_UIC020_Primary_tumor_hires_image': DataArray[cyx] (3, 3000, 3000)
│ └── 'GSM9294639_UIC020_Primary_tumor_lowres_image': DataArray[cyx] (3, 600, 600)
├── Shapes
│ └── 'GSM9294639_UIC020_Primary_tumor': GeoDataFrame shape: (13516, 2) (2D shapes)
└── Tables
└── 'table': AnnData (13516, 18085)
with coordinate systems:
▸ 'GSM9294639_UIC020_Primary_tumor', with elements:
GSM9294639_UIC020_Primary_tumor_hires_image (Images), GSM9294639_UIC020_Primary_tumor_lowres_image (Images), GSM9294639_UIC020_Primary_tumor (Shapes)
▸ 'GSM9294639_UIC020_Primary_tumor_downscaled_hires', with elements:
GSM9294639_UIC020_Primary_tumor_hires_image (Images), GSM9294639_UIC020_Primary_tumor (Shapes)
▸ 'GSM9294639_UIC020_Primary_tumor_downscaled_lowres', with elements:
GSM9294639_UIC020_Primary_tumor_lowres_image (Images), GSM9294639_UIC020_Primary_tumor (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("nXCEnSwg0JY1jKm30000")
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("nXCEnSwg0JY1jKm3") # 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 nXCEnSwg0JY1jKm30000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/nXCEnSwg0JY1jKm3
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid nXCEnSwg0JY1jKm3License: NCBI GEO policy
Part of collection
Translational profiling of ET-insensitive cell populations in ER+ breast cancer reveals new therapeutic vulnerabilities→ 4 datasets · comparison
Metadata
- Technology
- Visium
- Organism
- human
- Tissue
- breast
- Condition
- estrogen-receptor positive breast cancer
- Modality
- RNA
- Observations (spots)
- 13,516
- Tier
- bronze
- Chemistry
- Visium v1
- Resolution
- 3,000 × 3,000 px
- mpp
- 4.257 µm/px
- Size
- 374 MB
- Sample ID
- GSM9294639
- License
- NCBI GEO policy
- Published
- Oct 5, 2026
Cite this dataset
doi.org/10.64898/2026.09.10.750719 ↗ BibTeX
@article{geo:GSM9294639,
doi = {10.64898/2026.09.10.750719},
title = {GSM9294639},
year = {2026}
}Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB