Visium
Mouse colon
GSM8429992
bronze Interactive viewer H&E colorectal carcinoma Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM8429992_SC2200582_hires_image': DataArray[cyx] (3, 2000, 1969)
│ └── 'GSM8429992_SC2200582_lowres_image': DataArray[cyx] (3, 600, 591)
├── Shapes
│ └── 'GSM8429992_SC2200582': GeoDataFrame shape: (2710, 2) (2D shapes)
└── Tables
└── 'table': AnnData (2710, 32285)
with coordinate systems:
▸ 'GSM8429992_SC2200582', with elements:
GSM8429992_SC2200582_hires_image (Images), GSM8429992_SC2200582_lowres_image (Images), GSM8429992_SC2200582 (Shapes)
▸ 'GSM8429992_SC2200582_downscaled_hires', with elements:
GSM8429992_SC2200582_hires_image (Images), GSM8429992_SC2200582 (Shapes)
▸ 'GSM8429992_SC2200582_downscaled_lowres', with elements:
GSM8429992_SC2200582_lowres_image (Images), GSM8429992_SC2200582 (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("aieCaby2TpVjbmoi0000")
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("aieCaby2TpVjbmoi") # 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 aieCaby2TpVjbmoi0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/aieCaby2TpVjbmoi
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid aieCaby2TpVjbmoiLicense: NCBI GEO policy
Part of collection
Mapping the genetic landscape establishing a tumor immune microenvironment favorable for anti-PD-1 response in mice and humans (Visium).→ 4 datasets · comparison
Metadata
- Technology
- Visium
- Organism
- mouse
- Tissue
- colon
- Condition
- colorectal carcinoma
- Modality
- RNA
- Observations (spots)
- 2,710
- Tier
- bronze
- Chemistry
- Visium v1
- Magnification
- other
- Resolution
- 1,969 × 2,000 px
- mpp
- 3.459 µm/px
- Size
- 57.9 MB
- Sample ID
- GSM8429992
- License
- NCBI GEO policy
- Published
- May 4, 2025
Cite this dataset
doi.org/10.1016/j.celrep.2025.115698 ↗ BibTeX
@article{Skelly_2025,
title = {Mapping the genetic landscape establishing a tumor immune microenvironment favorable for anti-PD-1 response},
volume = {44},
ISSN = {2211-1247},
url = {http://dx.doi.org/10.1016/j.celrep.2025.115698},
DOI = {10.1016/j.celrep.2025.115698},
number = {5},
journal = {Cell Reports},
publisher = {Elsevier BV},
author = {Skelly, Daniel A. and Graham, John P. and Cheng, Mingshan and Furuta, Mayuko and Walter, Andrew and Stoklasek, Thomas A. and Yang, Hongyuan and Stearns, Timothy M. and Poirion, Olivier and Zhang, Ji-Gang and Grassmann, Jessica D.S. and Luo, Diane and Flynn, William F. and Courtois, Elise T. and Chang, Chih-Hao and Serreze, David V. and Menghi, Francesca and Reinholdt, Laura G. and Liu, Edison T.},
year = {2025},
month = May,
pages = {115698}
}Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB