Collections / Spatial transcriptomics of triple negative breast cancer
Spatial transcriptomics of triple negative breast cancer
Triple negative breast cancer (TNBC) is an aggressive and clinically challenging subtype of breast cancer. TNBC disporportionately affects African-American (AA) women, but the biological basis of this disparity is not understood. To gain a better understanding of TNBC, particularly in AA patients, we applied spatial transcriptomics to thoroughly characterize gene expression and tissue architecture in TNBC. Our cohort consisted of 22 patients, 15 of whom were AA, and 7 who were Caucasian. We obtained 2 sections from each patient's tumor (except for patient 19) for a total of 43 samples.
Datasets43
Size~1.1 GB
AssayVisium
Samplehuman · breast
KindOther
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Python · lamindb
import lamindb as ln
import spatialdata as sd
coll = ln.Collection.get(key="geo-gse210616")
coll.ordered_artifacts.df() # the 43 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 · 43
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