Collections / Spotiphy: generative modeling in single-cell spatial whole transcriptomics
Spotiphy: generative modeling in single-cell spatial whole transcriptomics
Datasets2
Size~473 MB
AssayVisium
Samplemouse · brain
KindComparison
Download the whole collection
Python · lamindb
import lamindb as ln
import spatialdata as sd
coll = ln.Collection.get(key="doi-10.5281/zenodo.10520022")
coll.ordered_artifacts.df() # the 2 members, ordered
# download every member .zarr to the local cache:
paths = [a.cache() for a in coll.ordered_artifacts.all()]
# …or load each straight into memory as a SpatialData object:
sdatas = {a.key: sd.read_zarr(a.cache()) for a in coll.ordered_artifacts.all()} Member datasets · 2
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}
}