We attempted to determine histological localization of chemoresistant cancer subpopulation by performing spatial transcriptomics.
from sddb import Catalog
cohort = Catalog().collection("geo-gse224335")
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/")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="geo-gse224335")
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()]# sddb client: download every member .zarr into data/
sddb-cli download --collection geo-gse224335 --dest data/Licenses: 2 NCBI GEO policy
@article{Mori_2024,
title = {Targeting PDGF signaling of cancer-associated fibroblasts blocks feedback activation of HIF-1α and tumor progression of clear cell ovarian cancer},
volume = {5},
ISSN = {2666-3791},
url = {http://dx.doi.org/10.1016/j.xcrm.2024.101532},
DOI = {10.1016/j.xcrm.2024.101532},
number = {5},
journal = {Cell Reports Medicine},
publisher = {Elsevier BV},
author = {Mori, Yutaro and Okimoto, Yoshie and Sakai, Hiroaki and Kanda, Yusuke and Ohata, Hirokazu and Shiokawa, Daisuke and Suzuki, Mikiko and Yoshida, Hiroshi and Ueda, Haruka and Sekizuka, Tomoyuki and Tamura, Ryo and Yamawaki, Kaoru and Ishiguro, Tatsuya and Mateos, Raul Nicolas and Shiraishi, Yuichi and Yatabe, Yasushi and Hamada, Akinobu and Yoshihara, Kosuke and Enomoto, Takayuki and Okamoto, Koji},
year = {2024},
month = May,
pages = {101532}
}