Visium

Mouse prostate gland

GSM8649344

bronze Interactive viewer H&E prostate cancer Provisional

Preview Client Lamin CLI

print(sdata)

SpatialData object
├── Images
│     ├── 'GSM8649344_551_hires_image': DataArray[cyx] (3, 1946, 2000)
│     └── 'GSM8649344_551_lowres_image': DataArray[cyx] (3, 584, 600)
├── Shapes
│     └── 'GSM8649344_551': GeoDataFrame shape: (2965, 2) (2D shapes)
└── Tables
      └── 'table': AnnData (2965, 19465)
with coordinate systems:
    ▸ 'GSM8649344_551', with elements:
        GSM8649344_551_hires_image (Images), GSM8649344_551_lowres_image (Images), GSM8649344_551 (Shapes)
    ▸ 'GSM8649344_551_downscaled_hires', with elements:
        GSM8649344_551_hires_image (Images), GSM8649344_551 (Shapes)
    ▸ 'GSM8649344_551_downscaled_lowres', with elements:
        GSM8649344_551_lowres_image (Images), GSM8649344_551 (Shapes)

Install (Python 3.12+) Docs →

Python · sddb client

from sddb import Catalog

ds = Catalog().dataset("EDcxRds05aIKtunp0000")
ds.elements()          # inspect without downloading
sdata = ds.to_sdata()  # cached locally, reused
print(sdata)

Install (Python 3.12+) Docs →

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("EDcxRds05aIKtunp")   # 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

Install (Python 3.12+) Docs →

Shell

# sddb client: download the .zarr into data/
sddb-cli download EDcxRds05aIKtunp0000 --dest data/

# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/EDcxRds05aIKtunp

# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid EDcxRds05aIKtunp

Install (Python 3.12+) Docs →

License: NCBI GEO policy

View on Lamin ↗ Open in Vitessce ↗ Flag a data issue

Part of collection

FOXA1 loss drives basal/squamous de-differentiation of prostate cancer and induces an immunosuppressive tumor microenvironment→

4 datasets · comparison

Metadata

Technology: Visium
Organism: mouse
Tissue: prostate gland
Condition: prostate cancer
Modality: RNA
Observations (spots): 2,965
Tier: bronze
Chemistry: Visium v1
Magnification: other
Resolution: 2,000 × 1,946 px
mpp: 3.746 µm/px
Size: 76.3 MB
Sample ID: GSM8649344
License: NCBI GEO policy
Published: Feb 21, 2026

Cite this dataset

doi.org/10.1038/s41467-026-71121-8 ↗

BibTeX

@article{Brea_2026,
  title = {FOXA1 loss drives basal/squamous de-differentiation of prostate cancer and induces an immunosuppressive tumor microenvironment},
  volume = {17},
  ISSN = {2041-1723},
  url = {http://dx.doi.org/10.1038/s41467-026-71121-8},
  DOI = {10.1038/s41467-026-71121-8},
  number = {1},
  journal = {Nature Communications},
  publisher = {Springer Science and Business Media LLC},
  author = {Brea, Lourdes and Shi, Hongshun and Keo, Viriya and Huang, Jing and Peng, Liu and Chu, Qi and Xie, Wanqing and Xie, Yinghua and Senthil, Sambhavi and Breneman, Matthew T. and Fan, Jie and Xie, Ping and Lu, Xiaodong and Degraff, David J. and Abdulkadir, Sarki A. and Yang, Ximing and Kosoff, David and Zhao, Jonathan C. and Zhang, Bin and Hu, Jian and Yu, Jindan},
  year = {2026},
  month = Mar
}

Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB