Collections / geo-gse328460

geo-gse328460

Datasets1
Size~1.1 GB
TechnologyCosMx SMI
Samplehuman · kidney
KindOther
Flag a data issue
Python · sddb client
from sddb import Catalog

cohort = Catalog().collection("geo-gse328460")
cohort.members        # the 1 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-gse328460")
coll.ordered_artifacts.to_dataframe()   # the 1 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-gse328460 --dest data/

Licenses: 1 NCBI GEO policy

Open in Vitessce
CosMx SMI
Human kidney
GSM9683939
human kidney renal cell carcinoma 1.1 GB 118,109 cells silver NCBI GEO policy
TechnologyCosMx SMI
Organismhuman
Tissuekidney
Conditionrenal cell carcinoma
Size1.1 GB
Cells118,109
silver NCBI GEO policy Open in Vitessce