Collections / Spatial transcriptomics reveal unnresolved wound repair as potential driver of PFA Ependymoma progression
Spatial transcriptomics reveal unnresolved wound repair as potential driver of PFA Ependymoma progression
Datasets14
Size~5.3 GB
AssayVisium
Samplehuman · brain
KindReplicates
Download the whole collection
Python · lamindb
import lamindb as ln
import spatialdata as sd
coll = ln.Collection.get(key="doi-10.1093/neuonc/noac079.165")
coll.ordered_artifacts.df() # the 14 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 · 14
Cite this collection
doi.org/10.1093/neuonc/noac079.165 ↗ BibTeX
@article{Donson_2022,
title = {EPEN-29. Spatial transcriptomic analysis of ependymoma implicates unresolved wound healing as a driver of tumor progression},
volume = {24},
ISSN = {1523-5866},
url = {http://dx.doi.org/10.1093/neuonc/noac079.165},
DOI = {10.1093/neuonc/noac079.165},
number = {Supplement_1},
journal = {Neuro-Oncology},
publisher = {Oxford University Press (OUP)},
author = {Donson, Andrew and Fu, Rui and Norris, gregory and Willard, Nicholas and Griesinger, Andrea and Riemondy, Kent and Amani, Vladimir and Grimaldo, Enrique and Harris, Faith and Hankinson, Todd and Mitra, Siddhartha and Ritzmann, timothy and Grundy, Richard and Foreman, Nicholas},
year = {2022},
month = June,
pages = {i45–i45}
}