Collections / geo-gse293783

geo-gse293783

Datasets2
Size~899 MB
TechnologyVisium HD
Samplehuman · adrenal gland
KindOther
Flag a data issue
Python · sddb client
from sddb import Catalog

cohort = Catalog().collection("geo-gse293783")
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/")
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-gse293783")
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()]
Shell
# sddb client: download every member .zarr into data/
sddb-cli download --collection geo-gse293783 --dest data/

Licenses: 2 NCBI GEO policy

Open in Vitessce
Visium HD
Human adrenal gland
GSM8890018
human adrenal gland 152 MB 127,893 bins silver H&E NCBI GEO policy
TechnologyVisium HD
Organismhuman
Tissueadrenal gland
Size152 MB
Bins127,893
silver H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium HD
Human adrenal gland
GSM8890017
human adrenal gland 747 MB 111,746 bins silver H&E NCBI GEO policy
TechnologyVisium HD
Organismhuman
Tissueadrenal gland
Size747 MB
Bins111,746
silver H&E NCBI GEO policy Open in Vitessce