Spatial transcriptomics reveals ovarian cancer subclones with different microenvironments

import lamindb as ln
import spatialdata as sd

coll = ln.Collection.get(key="geo-gse211956")
coll.ordered_artifacts.df()                 # the 8 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()}