Collections / Single Cell and Spatial Analysis of Human Squamous Cell Carcinoma [ST]
Single Cell and Spatial Analysis of Human Squamous Cell Carcinoma [ST]
To define the cellular composition and spatial architecture of the tumor micoenvironment, we combined single-cell RNA-sequencing, spatial transcriptomics, and multiplexed ion-beam imaging from 10 patient cutaneous squamous cell carcinoma tumors and site-matched normal skin
Datasets4
Size~64 MB
AssayVisium
Samplehuman · skin of body
KindReplicates
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Python · lamindb
import lamindb as ln
import spatialdata as sd
coll = ln.Collection.get(key="geo-gse144239")
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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