CosMx SMI
Human kidney
GSM8554642
human kidney kidney neoplasm 1.7 GB 283,682 cells bronze NCBI GEO policy
TechnologyCosMx SMI
Organismhuman
Tissuekidney
Conditionkidney neoplasm
Cells283,682
bronze NCBI GEO policy
Collections / geo-gse278766
geo-gse278766
Datasets1
Size~1.7 GB
TechnologyCosMx SMI
Samplehuman · kidney
KindPublication
Download the whole collection
Python · sddb client
from sddb import Catalog
cohort = Catalog().collection("geo-gse278766")
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-gse278766")
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-gse278766 --dest data/Licenses: 1 NCBI GEO policy
About the study
Rigor and Reproducibility of Spatial Transcriptomics Performed on Clinically Sourced Human Tissues.
Read the abstract at the source →Member datasets · 1
Cite this collection
No linked publication found — please cite the data source.