Ductal carcinoma in situ (DCIS) is the most common preinvasive breast cancer, however our knowledge of the DCIS tumor microenvironment (TME) remains limited. We constructed a comprehensive atlas of the TME in estrogen-receptor positive DCIS using fresh samples collected from normal breast tissues, DCIS and invasive breast cancers. This Series is only for the Visium samples, see GSE348584 for the Xenium samples.
from sddb import Catalog
cohort = Catalog().collection("geo-gse348919")
cohort.members # the 11 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-gse348919")
coll.ordered_artifacts.to_dataframe() # the 11 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-gse348919 --dest data/Licenses: 11 NCBI GEO policy
No linked publication found — please cite the data source.