Collections / Spatial proteogenomics reveals distinct and evolutionarily-conserved hepatic macrophage niches (spatial)
Spatial proteogenomics reveals distinct and evolutionarily-conserved hepatic macrophage niches (spatial)
Analysis of CITE-seq data , Nuclei RNA-seq data and single cell RNA-seq data on CD45+ and CD45- cells isolated from the livers of mice fed a standard diet (SD) or western diet (WD; fat, cholesterol and sugar), from healthy and steatotic human livers, from hamster liver, pig liver, chicken liver, monkey liver and zebrafish liver. We also performed Spatial Transcriptomics analysis on heatlhy mouse livers, NAFLD mouse livers, healthy human livers and steatotic human livers.
Datasets15
Size~383 MB
AssayVisium
Samplemouse · multiple
KindComparison
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Python · sddb client
from sddb import Catalog
cohort = Catalog().collection("geo-gse192741")
cohort.members # the 15 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-gse192741")
coll.ordered_artifacts.to_dataframe() # the 15 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-gse192741 --dest data/ Licenses: 15 NCBI GEO policy
Member datasets · 15
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