Mouse brain
ZEN60
mouse brain 242 MB 3,541 spots silver H&E
TechnologyVisium
Organismmouse
Tissuebrain
Spots3,541
silver H&E
Collections / Spotiphy: generative modeling in single-cell spatial whole transcriptomics
Spotiphy: generative modeling in single-cell spatial whole transcriptomics
Datasets2
Size~496 MB
AssayVisium
Samplemouse · brain
KindComparison
Download the whole collection
Python · sddb client
from sddb import Catalog
cohort = Catalog().collection("doi-10-5281-zenodo-10520022")
cohort.members # the 2 datasets as a table
print(cohort.licenses()) # check the terms before you download
sdatas = cohort.to_dict() # {uid: SpatialData}, cached locally
# or keep the .zarr files in a folder of your choice:
# sdatas = cohort.to_dict(dest="data/") 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")
coll = db.Collection.get(key="doi-10.5281/zenodo.10520022")
coll.ordered_artifacts.to_dataframe() # the 2 members, ordered
# download every member .zarr to the local cache:
paths = [a.cache() for a in coll.ordered_artifacts.all()] Shell
# sddb client: download every member .zarr into data/
sddb-cli download --collection doi-10-5281-zenodo-10520022 --dest data/Licenses: 2 CC BY-NC-SA 4.0
Member datasets · 2
Mouse brain
ZEN61
mouse brain Alzheimer disease 255 MB 3,476 spots silver H&E
TechnologyVisium
Organismmouse
Tissuebrain
ConditionAlzheimer disease
Spots3,476
silver H&E
Cite this collection
doi.org/10.5281/zenodo.10520022 ↗ BibTeX
@misc{https://doi.org/10.5281/zenodo.10520022,
doi = {10.5281/ZENODO.10520022},
url = {https://zenodo.org/doi/10.5281/zenodo.10520022},
author = {Yang, Jiyuan and Zheng, Ziqian and Yu, Jiyang},
language = {en},
title = {Spotiphy enables single-cell spatial whole transcriptomics across the entire section},
publisher = {Zenodo},
year = {2024},
copyright = {Creative Commons Attribution 4.0 International}
}