Visium
Mouse lung
GSM7978619
bronze Interactive viewer H&E pulmonary fibrosis Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM7978619_B1_hires_image': DataArray[cyx] (3, 2000, 1817)
│ └── 'GSM7978619_B1_lowres_image': DataArray[cyx] (3, 600, 545)
├── Shapes
│ └── 'GSM7978619_B1': GeoDataFrame shape: (2775, 2) (2D shapes)
└── Tables
└── 'table': AnnData (2775, 32285)
with coordinate systems:
▸ 'GSM7978619_B1', with elements:
GSM7978619_B1_hires_image (Images), GSM7978619_B1_lowres_image (Images), GSM7978619_B1 (Shapes)
▸ 'GSM7978619_B1_downscaled_hires', with elements:
GSM7978619_B1_hires_image (Images), GSM7978619_B1 (Shapes)
▸ 'GSM7978619_B1_downscaled_lowres', with elements:
GSM7978619_B1_lowres_image (Images), GSM7978619_B1 (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("3JTVLlyZPSZ436Qr0000")
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("3JTVLlyZPSZ436Qr") # 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 3JTVLlyZPSZ436Qr0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/3JTVLlyZPSZ436Qr
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid 3JTVLlyZPSZ436QrLicense: NCBI GEO policy
Part of collection
Histological Signatures Reveal Anti-Fibrotic Factors in Mouse and Human Lungs [Visium]→ 8 datasets · time course
Metadata
- Technology
- Visium
- Organism
- mouse
- Tissue
- lung
- Condition
- pulmonary fibrosis
- Modality
- RNA
- Observations (spots)
- 2,775
- Tier
- bronze
- Chemistry
- Visium v1
- Magnification
- other
- Resolution
- 1,817 × 2,000 px
- mpp
- 4.049 µm/px
- Size
- 12.5 MB
- Sample ID
- GSM7978619
- License
- NCBI GEO policy
- Published
- Jan 7, 2025
Cite this dataset
doi.org/10.1038/s41586-025-08727-3 ↗ BibTeX
@article{Guo_2025,
title = {Histological signatures map anti-fibrotic factors in mouse and human lungs},
volume = {641},
ISSN = {1476-4687},
url = {http://dx.doi.org/10.1038/s41586-025-08727-3},
DOI = {10.1038/s41586-025-08727-3},
number = {8064},
journal = {Nature},
publisher = {Springer Science and Business Media LLC},
author = {Guo, Jason L. and Griffin, Michelle and Yoon, Jung-Ki and Lopez, David M. and Zhu, Yili and Lu, John M. and Mikos, Georgios and Parker, Jennifer B. L. and Mascharak, Shamik and Brenac, Camille and Guardino, Nicholas J. and Abbas, Darren B. and Li, Dayan J. and Valencia, Caleb and Liang, Norah E. and Januszyk, Michael and Chang, Howard Y. and Wan, Derrick C. and Desai, Tushar J. and Longaker, Michael T.},
year = {2025},
month = Mar,
pages = {993–1004}
}Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB