Collections / Single cell- Cluster-RNA seq and Spatial Transcriptomics from the trunk of mouse embryos of different genotypes (wild type, Pax2-GFP, Pax2-GFP; Gata3 knockout) and developmental stages (E8.75, E9.5, E11.5) [Spatial Transcriptomics]
Single cell- Cluster-RNA seq and Spatial Transcriptomics from the trunk of mouse embryos of different genotypes (wild type, Pax2-GFP, Pax2-GFP; Gata3 knockout) and developmental stages (E8.75, E9.5, E11.5) [Spatial Transcriptomics]
To study cell heterogeneity and state transitions in the developing urinary tract we performed spatial transcriptomics from the trunk of E9.5 Pax2GFP mouse embryos using the 10X Genomics Visium Spatial Gene Expression protocol
Datasets4
Size~16 MB
AssayVisium
Samplemouse · trunk
KindOther
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Python · lamindb
import lamindb as ln
import spatialdata as sd
coll = ln.Collection.get(key="geo-gse160137")
coll.ordered_artifacts.df() # the 4 members, ordered
# download every member .zarr to the local cache:
paths = [a.cache() for a in coll.ordered_artifacts.all()]
# …or load each straight into memory as a SpatialData object:
sdatas = {a.key: sd.read_zarr(a.cache()) for a in coll.ordered_artifacts.all()} Member datasets · 4
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