Visium
Mouse kidney
GSM8441002
bronze Interactive viewer H&E renal fibrosis Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM8441002_No19_hires_image': DataArray[cyx] (3, 1817, 2000)
│ └── 'GSM8441002_No19_lowres_image': DataArray[cyx] (3, 545, 600)
├── Shapes
│ └── 'GSM8441002_No19': GeoDataFrame shape: (2051, 2) (2D shapes)
└── Tables
└── 'table': AnnData (2051, 19465)
with coordinate systems:
▸ 'GSM8441002_No19', with elements:
GSM8441002_No19_hires_image (Images), GSM8441002_No19_lowres_image (Images), GSM8441002_No19 (Shapes)
▸ 'GSM8441002_No19_downscaled_hires', with elements:
GSM8441002_No19_hires_image (Images), GSM8441002_No19 (Shapes)
▸ 'GSM8441002_No19_downscaled_lowres', with elements:
GSM8441002_No19_lowres_image (Images), GSM8441002_No19 (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("4h5ljZYfb1MnBw1w0000")
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("4h5ljZYfb1MnBw1w") # 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 4h5ljZYfb1MnBw1w0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/4h5ljZYfb1MnBw1w
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid 4h5ljZYfb1MnBw1wLicense: NCBI GEO policy
Part of collection
CH6824025, potent and selective DDR1 inhibitor, reduces kidney fibrosis in UUO mice→ 8 datasets · comparison
Metadata
- Technology
- Visium
- Organism
- mouse
- Tissue
- kidney
- Condition
- renal fibrosis
- Modality
- RNA
- Observations (spots)
- 2,051
- Tier
- bronze
- Chemistry
- Visium v1
- Magnification
- other
- Resolution
- 2,000 × 1,817 px
- mpp
- 4.054 µm/px
- Size
- 60.4 MB
- Sample ID
- GSM8441002
- License
- NCBI GEO policy
- Published
- Dec 31, 2024
Cite this dataset
doi.org/10.1124/jpet.124.002330 ↗ BibTeX
@article{Yasui_2024,
title = {CH6824025, Potent and Selective Discoidin Domain Receptor 1 Inhibitor, Reduces Kidney Fibrosis in Unilateral Ureteral Obstruction Mice},
volume = {391},
ISSN = {0022-3565},
url = {http://dx.doi.org/10.1124/jpet.124.002330},
DOI = {10.1124/jpet.124.002330},
number = {3},
journal = {The Journal of Pharmacology and Experimental Therapeutics},
publisher = {Elsevier BV},
author = {Yasui, Yukari and Murata, Takeshi and Tsuboi, Yoshinori and Murai, Atsuko and Horiba, Naoshi},
year = {2024},
month = Dec,
pages = {450–459}
}Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB