To understand the role of hypoxia in metastatic progression, we sought to spatially map gene expression in hypoxic cells compared with cells that migrated to oxygenated tumor regions. We adapted the Visium spatial transcriptomics protocol to perform concurrent transcriptional profiling and fluorescent imaging of our hypoxia fate-mapping system.
from sddb import Catalog
cohort = Catalog().collection("geo-gse240212")
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-gse240212")
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-gse240212 --dest data/Licenses: 2 NCBI GEO policy
@article{Godet_2024,
title = {Hypoxia induces ROS-resistant memory upon reoxygenation in vivo promoting metastasis in part via MUC1-C},
volume = {15},
ISSN = {2041-1723},
url = {http://dx.doi.org/10.1038/s41467-024-51995-2},
DOI = {10.1038/s41467-024-51995-2},
number = {1},
journal = {Nature Communications},
publisher = {Springer Science and Business Media LLC},
author = {Godet, Inês and Oza, Harsh H. and Shi, Yi and Joe, Natalie S. and Weinstein, Alyssa G. and Johnson, Jeanette and Considine, Michael and Talluri, Swathi and Zhang, Jingyuan and Xu, Reid and Doctorman, Steven and Mbulaiteye, Delma and Stein-O’Brien, Genevieve and Kagohara, Luciane T. and Santa-Maria, Cesar A. and Fertig, Elana J. and Gilkes, Daniele M.},
year = {2024},
month = Sept
}