Collections / geo-gse277782

geo-gse277782

Datasets2
Size~854 MB
TechnologyCosMx SMI
Samplehuman · unknown
KindPublication
Flag a data issue
10.1038/s41586-025-08927-x ↗
Python · sddb client
from sddb import Catalog

cohort = Catalog().collection("geo-gse277782")
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-gse277782")
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-gse277782 --dest data/

Licenses: 2 NCBI GEO policy

Spatial mapping of transcriptomic plasticity in metastatic pancreatic cancer.

Read the abstract at the source →
Open in Vitessce
CosMx SMI
Human unknown
GSE277782:Run5961_PDAC_Slide1
human unknown pancreatic ductal adenocarcinoma 389 MB 35,385 cells bronze NCBI GEO policy
TechnologyCosMx SMI
Organismhuman
Tissueunknown
Conditionpancreatic ductal adenocarcinoma
Size389 MB
Cells35,385
bronze NCBI GEO policy Open in Vitessce
Open in Vitessce
CosMx SMI
Human unknown
GSE277782:Run5961_PDAC_Slide2
human unknown pancreatic ductal adenocarcinoma 465 MB 52,329 cells bronze NCBI GEO policy
TechnologyCosMx SMI
Organismhuman
Tissueunknown
Conditionpancreatic ductal adenocarcinoma
Size465 MB
Cells52,329
bronze NCBI GEO policy Open in Vitessce

Cite this collection

No linked publication found — please cite the data source.