Visium
Mouse descending colon
GSM7508783
bronze Interactive viewer H&E Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM7508783_V10S15-056_A_hires_image': DataArray[cyx] (3, 1710, 2000)
│ └── 'GSM7508783_V10S15-056_A_lowres_image': DataArray[cyx] (3, 513, 600)
├── Shapes
│ └── 'GSM7508783_V10S15-056_A': GeoDataFrame shape: (502, 2) (2D shapes)
└── Tables
└── 'table': AnnData (502, 32285)
with coordinate systems:
▸ 'GSM7508783_V10S15-056_A', with elements:
GSM7508783_V10S15-056_A_hires_image (Images), GSM7508783_V10S15-056_A_lowres_image (Images), GSM7508783_V10S15-056_A (Shapes)
▸ 'GSM7508783_V10S15-056_A_downscaled_hires', with elements:
GSM7508783_V10S15-056_A_hires_image (Images), GSM7508783_V10S15-056_A (Shapes)
▸ 'GSM7508783_V10S15-056_A_downscaled_lowres', with elements:
GSM7508783_V10S15-056_A_lowres_image (Images), GSM7508783_V10S15-056_A (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("J8cTkkoyYSkZaNy60000")
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("J8cTkkoyYSkZaNy6") # 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 J8cTkkoyYSkZaNy60000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/J8cTkkoyYSkZaNy6
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid J8cTkkoyYSkZaNy6License: NCBI GEO policy
Part of collection
Spatial Transcriptomic profiling of day2 wounds and intact tissues of Hgfac WT and KO mice→ 3 datasets · comparison
Metadata
- Technology
- Visium
- Organism
- mouse
- Tissue
- descending colon
- Modality
- RNA
- Observations (spots)
- 502
- Tier
- bronze
- Chemistry
- Visium v1
- Magnification
- other
- Resolution
- 2,000 × 1,710 px
- mpp
- 4.637 µm/px
- Size
- 10.9 MB
- Sample ID
- GSM7508783
- License
- NCBI GEO policy
- Published
- Oct 26, 2023
Cite this dataset
doi.org/10.1126/scitranslmed.adg5252 ↗ BibTeX
@article{Nakata_2023,
title = {Genetic vulnerability to Crohn’s disease reveals a spatially resolved epithelial restitution program},
volume = {15},
ISSN = {1946-6242},
url = {http://dx.doi.org/10.1126/scitranslmed.adg5252},
DOI = {10.1126/scitranslmed.adg5252},
number = {719},
journal = {Science Translational Medicine},
publisher = {American Association for the Advancement of Science (AAAS)},
author = {Nakata, Toru and Li, Chenhao and Mayassi, Toufic and Lin, Helen and Ghosh, Koushik and Segerstolpe, Åsa and Diamond, Emma L. and Herbst, Paula and Biancalani, Tommaso and Gaddam, Shreya and Parkar, Saurabh and Lu, Ziqing and Jaiswal, Alok and Li, Bihua and Creasey, Elizabeth A. and Lefkovith, Ariel and Daly, Mark J. and Graham, Daniel B. and Xavier, Ramnik J.},
year = {2023},
month = Oct
}Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB