Collections / Multi-omics analysis identifies erythroid cells as the major population in mouse placentas expressing the MHC class II antigen presentation, chemokine, and antibacterial immune response genes [Spatial Transcriptomics]
Multi-omics analysis identifies erythroid cells as the major population in mouse placentas expressing the MHC class II antigen presentation, chemokine, and antibacterial immune response genes [Spatial Transcriptomics]
Pregnancy is one of the most important processes for mammals, which is deeply controlled by the immune system. We performed spatial transcriptomics to profile mouse placentas from semi-allogeneic and syngeneic pregnancies at E12.5 to elucidate differences between these types of pregnancies. Our analysis showed that erythroid cells were the major immunoregulatory population in both types of pregnancies.
Datasets3
Size~97.8 MB
AssayVisium
Samplemouse · placenta
KindOther
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Python · sddb client
from sddb import Catalog
cohort = Catalog().collection("geo-gse289170")
cohort.members # the 3 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-gse289170")
coll.ordered_artifacts.to_dataframe() # the 3 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-gse289170 --dest data/ Licenses: 3 NCBI GEO policy
Member datasets · 3
Cite this collection
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