Collections / geo-gse267315

geo-gse267315

Datasets4

Size~848 MB

AssayStereo-seq

Samplehuman · ovary

KindOther

Flag a data issue

Download the whole collection

Client Lamin CLI

Python · sddb client

from sddb import Catalog

cohort = Catalog().collection("geo-gse267315")
cohort.members        # the 4 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/")

Install (Python 3.12+) Docs →

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-gse267315")
coll.ordered_artifacts.to_dataframe()   # the 4 members, ordered

# download every member .zarr to the local cache:
paths = [a.cache() for a in coll.ordered_artifacts.all()]

Install (Python 3.12+) Docs →

Shell

# sddb client: download every member .zarr into data/
sddb-cli download --collection geo-gse267315 --dest data/

Install (Python 3.12+) Docs →

Licenses: 4 NCBI GEO policy

Member datasets · 4

Stereo-seq

Human ovary

GSM8263826

human ovary 352 MB 91,519 obs bronze NCBI GEO policy

TechnologyStereo-seq

Organismhuman

Tissueovary

Size352 MB

Obs91,519

bronze NCBI GEO policy

Stereo-seq

Human ovary

GSM8263825

human ovary 143 MB 50,340 obs bronze NCBI GEO policy

TechnologyStereo-seq

Organismhuman

Tissueovary

Size143 MB

Obs50,340

bronze NCBI GEO policy

Stereo-seq

Human ovary

GSM8263824

human ovary 205 MB 61,577 obs bronze NCBI GEO policy

TechnologyStereo-seq

Organismhuman

Tissueovary

Size205 MB

Obs61,577

bronze NCBI GEO policy

Stereo-seq

Human ovary

GSM8263823

human ovary 148 MB 78,790 obs bronze NCBI GEO policy

TechnologyStereo-seq

Organismhuman

Tissueovary

Size148 MB

Obs78,790

bronze NCBI GEO policy