Collections / geo-gse277441

geo-gse277441

Datasets3
Size~482 MB
TechnologyCosMx SMI
Samplehuman · coronary artery
KindOther
Flag a data issue
Python · sddb client
from sddb import Catalog

cohort = Catalog().collection("geo-gse277441")
cohort.members        # the 3 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-gse277441")
coll.ordered_artifacts.to_dataframe()   # the 3 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-gse277441 --dest data/

Licenses: 3 NCBI GEO policy

Open in Vitessce
CosMx SMI
Human coronary artery
GSM8522533
human coronary artery coronary atherosclerosis 45.9 MB 7,207 cells silver NCBI GEO policy
TechnologyCosMx SMI
Organismhuman
Tissuecoronary artery
Conditioncoronary atherosclerosis
Size45.9 MB
Cells7,207
silver NCBI GEO policy Open in Vitessce
Open in Vitessce
CosMx SMI
Human coronary artery
GSM8522534
human coronary artery coronary atherosclerosis 121 MB 19,050 cells silver NCBI GEO policy
TechnologyCosMx SMI
Organismhuman
Tissuecoronary artery
Conditioncoronary atherosclerosis
Size121 MB
Cells19,050
silver NCBI GEO policy Open in Vitessce
Open in Vitessce
CosMx SMI
Human coronary artery
GSM8522535
human coronary artery coronary atherosclerosis 315 MB 53,439 cells silver NCBI GEO policy
TechnologyCosMx SMI
Organismhuman
Tissuecoronary artery
Conditioncoronary atherosclerosis
Size315 MB
Cells53,439
silver NCBI GEO policy Open in Vitessce