Human prepuce of penis
GSM6806992
human prepuce of penis 12.2 MB 659 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismhuman
Tissueprepuce of penis
Spots659
bronze H&E NCBI GEO policy
Collections / Reconstruction of 3-dimensional tissue organization at the single-cell resolution [ST]
Reconstruction of 3-dimensional tissue organization at the single-cell resolution [ST]
We designed a neural network-based computational method that learns transcriptome-to-space mapping and reconstructs 3D tissue organization by learning from scRNA-seq and spatial transcriptomic data.
Datasets2
Size~25.7 MB
AssayVisium
Samplehuman · prepuce of penis
KindOther
Download the whole collection
Python · sddb client
from sddb import Catalog
cohort = Catalog().collection("geo-gse220572")
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-gse220572")
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-gse220572 --dest data/Licenses: 2 NCBI GEO policy
Member datasets · 2
Human prepuce of penis
GSM6806993
human prepuce of penis 13.5 MB 653 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismhuman
Tissueprepuce of penis
Spots653
bronze H&E NCBI GEO policy
Cite this collection
No linked publication found — please cite the data source.