Collections / Spatial transcriptomics reveals C10 tumor transcriptomic changes generated by Smarta cell transfer

Spatial transcriptomics reveals C10 tumor transcriptomic changes generated by Smarta cell transfer

To elucidate how antigen-specific CD4 T cells indirectly repress tumor growth independently of other lymphocytes, we first sought to gain insight into the changes they induced in the tumor micro-environment (TME) using the 10x Genomics Visium technology

Datasets2
Size~278 MB
AssayVisium
Samplemouse · lung
KindOther
PMID:42313973 ↗
Python · lamindb
import lamindb as ln
import spatialdata as sd

coll = ln.Collection.get(key="geo-gse254861")
coll.ordered_artifacts.df()                 # the 2 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()}
Open in Vitessce
Visium
Mouse lung
GSM8059173
mouse lung 179 MB 7,088 obs bronze H&E
TechnologyVisium
Organismmouse
Tissuelung
Size179 MB
Obs7,088
Magnificationother · 6.397 µm/px
bronze H&E Open in Vitessce
Open in Vitessce
Visium
Mouse lung
GSM8059174
mouse lung 99 MB 3,480 obs bronze H&E
TechnologyVisium
Organismmouse
Tissuelung
Size99 MB
Obs3,480
Magnificationother · 5.941 µm/px
bronze H&E Open in Vitessce

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