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
10.5281/zenodo.10520022 ↗
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()}
Open in Vitessce
Visium
Mouse brain
ZEN60
mouse brain 230 MB 3,541 obs silver H&E
TechnologyVisium
Organismmouse
Tissuebrain
Size230 MB
Obs3,541
silver H&E Open in Vitessce
Open in Vitessce
Visium
Mouse brain
ZEN61
mouse brain Alzheimer disease 243 MB 3,476 obs silver H&E
TechnologyVisium
Organismmouse
Tissuebrain
ConditionAlzheimer disease
Size243 MB
Obs3,476
silver H&E Open in Vitessce

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}
}