Collections / geo-gse305627

geo-gse305627

Datasets1
Size~174 MB
AssayStereo-seq
Samplehuman · peritoneum
KindOther
Flag a data issue
Python · sddb client
from sddb import Catalog

cohort = Catalog().collection("geo-gse305627")
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-gse305627")
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-gse305627 --dest data/

Licenses: 1 NCBI GEO policy

Open in Vitessce
Stereo-seq
Human peritoneum
GSM9181123
human peritoneum 174 MB 73,843 cells bronze Under review NCBI GEO policy
TechnologyStereo-seq
Organismhuman
Tissueperitoneum
Size174 MB
Cells73,843
bronze Under review NCBI GEO policy Open in Vitessce