Aging results in changes in mammary gland cell proportions, gene expression, and chromatin accessibility. Cell types captured include epithelial, immune, and stromal cell types.
from sddb import Catalog
cohort = Catalog().collection("geo-gse216542")
cohort.members # the 4 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-gse216542")
coll.ordered_artifacts.to_dataframe() # the 4 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-gse216542 --dest data/Licenses: 4 NCBI GEO policy
@article{Angarola_2024,
title = {Comprehensive single-cell aging atlas of healthy mammary tissues reveals shared epigenomic and transcriptomic signatures of aging and cancer},
volume = {5},
ISSN = {2662-8465},
url = {http://dx.doi.org/10.1038/s43587-024-00751-8},
DOI = {10.1038/s43587-024-00751-8},
number = {1},
journal = {Nature Aging},
publisher = {Springer Science and Business Media LLC},
author = {Angarola, Brittany L. and Sharma, Siddhartha and Katiyar, Neerja and Kang, Hyeon Gu and Nehar-Belaid, Djamel and Park, SungHee and Gott, Rachel and Eryilmaz, Giray N. and LaBarge, Mark A. and Palucka, Karolina and Chuang, Jeffrey H. and Korstanje, Ron and Ucar, Duygu and Anczukόw, Olga},
year = {2024},
month = Nov,
pages = {122–143}
}