Collections / Spatial Transcriptomics of Human Fetal Lungs
Spatial Transcriptomics of Human Fetal Lungs
Spatial transcriptomic profiles were generated using lung tissue sections obtained from twelve prenatal human lung samples ranging in gestational age from 13 – 20 weeks, of which four were diagnosed with Trisomy 21, with defined hypoplasia.
Datasets12
Size~738 MB
AssayVisium
Samplehuman · lung
KindTime course
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Python · sddb client
from sddb import Catalog
cohort = Catalog().collection("geo-gse310610")
cohort.members # the 12 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/") Python · lamindb
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-gse310610")
coll.ordered_artifacts.to_dataframe() # the 12 members, ordered
# download every member .zarr to the local cache:
paths = [a.cache() for a in coll.ordered_artifacts.all()] Shell
# sddb client: download every member .zarr into data/
sddb-cli download --collection geo-gse310610 --dest data/ Licenses: 12 NCBI GEO policy
Member datasets · 12
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