Collections / Spatial transcriptomics of high grade serous ovarian cancers
Spatial transcriptomics of high grade serous ovarian cancers
Ovarian cancer is characterized by extensive genomic instability and intratumoral heterogeneity. In this study, we performed spatial transcriptomics on a cohort of high grade serous ovarian cancer with defined BRCA mutation status to investigate the relationship between genomic alterations, tumor architecture, and the tumor microenvironment.
Datasets38
Size~702 MB
AssayVisium
Samplehuman · ovary
KindReplicates
Download the whole collection
Python · lamindb
import lamindb as ln
import spatialdata as sd
coll = ln.Collection.get(key="geo-gse327312")
coll.ordered_artifacts.df() # the 38 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 · 38
Human ovary
GSM9653311
human ovary ovarian serous adenocarcinoma 12 MB 689 obs silver H&E
TechnologyVisium
Organismhuman
Tissueovary
Conditionovarian serous adenocarcinoma
Obs689
silver H&E
Human ovary
GSM9653291
human ovary ovarian serous adenocarcinoma 21 MB 1,213 obs silver H&E
TechnologyVisium
Organismhuman
Tissueovary
Conditionovarian serous adenocarcinoma
Obs1,213
silver H&E
Human ovary
GSM9653283
human ovary ovarian serous adenocarcinoma 18 MB 810 obs silver H&E
TechnologyVisium
Organismhuman
Tissueovary
Conditionovarian serous adenocarcinoma
Obs810
silver H&E
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