Human skin of body
GSM8983043
human skin of body 12.6 MB 2,581 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismhuman
Tissueskin of body
Spots2,581
bronze H&E NCBI GEO policy
Collections / Targeting circulating mechanoresponsive monocytes and macrophages to reduce fibrosis
Targeting circulating mechanoresponsive monocytes and macrophages to reduce fibrosis
We performed single-cell RNA sequencing on skin, wounded tissue, or wounded tissue subjected to mechanical strain. Wounds could be treated with focal adhesion kinase inhibitor (FAKI) hydrogels or in mice with FAK knocked out in the myeloid cells.
Datasets2
Size~20.6 MB
AssayVisium
Samplehuman · skin of body
KindOther
Download the whole collection
Python · sddb client
from sddb import Catalog
cohort = Catalog().collection("geo-gse297064")
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-gse297064")
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-gse297064 --dest data/Licenses: 2 NCBI GEO policy
Member datasets · 2
Human skin of body
GSM8983044
human skin of body 8.0 MB 943 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismhuman
Tissueskin of body
Spots943
bronze H&E NCBI GEO policy
Cite this collection
No linked publication found — please cite the data source.