Collections / Spatial transcriptomic sequencing data of human small cell lung cancer
Spatial transcriptomic sequencing data of human small cell lung cancer
Small cell lung cancer is a lung tumor with extremely poor prognosis, and its tumor heterogeneity and unique microenvironment remain unclear. This study aimed to reveal the early tumorigenesis and microenvironment of small cell lung cancer by performing idle transcriptomic sequencing of patients' small cell lung cancer tissues.
Datasets4
Size~176 MB
AssayVisium
Samplehuman · lung
KindOther
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Python · lamindb
import lamindb as ln
import spatialdata as sd
coll = ln.Collection.get(key="geo-gse263196")
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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