Visium
Mouse mammary gland
GSM8428408
bronze Interactive viewer H&E breast cancer Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM8428408_09.9_627_TM_V11Y03-083_A_hires_image': DataArray[cyx] (3, 1256, 2000)
│ └── 'GSM8428408_09.9_627_TM_V11Y03-083_A_lowres_image': DataArray[cyx] (3, 377, 600)
├── Shapes
│ └── 'GSM8428408_09.9_627_TM_V11Y03-083_A': GeoDataFrame shape: (2596, 2) (2D shapes)
└── Tables
└── 'table': AnnData (2596, 19465)
with coordinate systems:
▸ 'GSM8428408_09.9_627_TM_V11Y03-083_A', with elements:
GSM8428408_09.9_627_TM_V11Y03-083_A_hires_image (Images), GSM8428408_09.9_627_TM_V11Y03-083_A_lowres_image (Images), GSM8428408_09.9_627_TM_V11Y03-083_A (Shapes)
▸ 'GSM8428408_09.9_627_TM_V11Y03-083_A_downscaled_hires', with elements:
GSM8428408_09.9_627_TM_V11Y03-083_A_hires_image (Images), GSM8428408_09.9_627_TM_V11Y03-083_A (Shapes)
▸ 'GSM8428408_09.9_627_TM_V11Y03-083_A_downscaled_lowres', with elements:
GSM8428408_09.9_627_TM_V11Y03-083_A_lowres_image (Images), GSM8428408_09.9_627_TM_V11Y03-083_A (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("XK5EVtzRrBKC2TCF0000")
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("XK5EVtzRrBKC2TCF") # 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 XK5EVtzRrBKC2TCF0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/XK5EVtzRrBKC2TCF
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid XK5EVtzRrBKC2TCFLicense: NCBI GEO policy
Part of collection
Extraction of a Stromal Metastatic Gene Signature in Breast Cancer via Spatial Profiling→ 4 datasets · other
Metadata
- Technology
- Visium
- Organism
- mouse
- Tissue
- mammary gland
- Condition
- breast cancer
- Modality
- RNA
- Observations (spots)
- 2,596
- Tier
- bronze
- Chemistry
- Visium v1
- Resolution
- 2,000 × 1,256 px
- mpp
- 5.665 µm/px
- Size
- 22.9 MB
- Sample ID
- GSM8428408
- License
- NCBI GEO policy
- Published
- Aug 4, 2024
Cite this dataset
doi.org/10.1186/s13046-025-03353-3 ↗ BibTeX
@article{Bertolazzi_2025,
title = {Extraction of a stromal metastatic gene signature in breast cancer via spatial profiling},
volume = {44},
ISSN = {1756-9966},
url = {http://dx.doi.org/10.1186/s13046-025-03353-3},
DOI = {10.1186/s13046-025-03353-3},
number = {1},
journal = {Journal of Experimental & Clinical Cancer Research},
publisher = {Springer Science and Business Media LLC},
author = {Bertolazzi, Giorgio and Cancila, Valeria and Vacca, Davide and Belmonte, Beatrice and Lecis, Daniele and Moghaddam, Parsa Sirati and Di Napoli, Arianna and Colombo, Mario Paolo and Pruneri, Giancarlo and Del Sal, Giannino and Scita, Giorgio and Fassan, Matteo and Vecchione, Andrea and Bicciato, Silvio and Tripodo, Claudio},
year = {2025},
month = Mar
}Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB