Collections / Spatial transcriptome sequencing of primary nasopharyngeal carcinoma tissues
Spatial transcriptome sequencing of primary nasopharyngeal carcinoma tissues
Understanding of the spatial architecture of the primary NPC microenvironment as well as the co-localization and cell-cell communication between tumor and immune cells
Datasets2
Size~44.4 MB
AssayVisium
Samplehuman · nasopharynx
KindOther
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Python · sddb client
from sddb import Catalog
cohort = Catalog().collection("geo-gse200310")
cohort.members # the 2 datasets as a table
print(cohort.licenses()) # check the terms before you download
sdatas = cohort.to_dict() # {uid: SpatialData}, cached locally
# or keep the .zarr files in a folder of your choice:
# sdatas = cohort.to_dict(dest="data/") Python · lamindb
Needs pip install lamindb and network access to the Lamin database, which is limited during the alpha. If it fails, use the Client tab.
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
coll = db.Collection.get(key="geo-gse200310")
coll.ordered_artifacts.to_dataframe() # the 2 members, ordered
# download every member .zarr to the local cache:
paths = [a.cache() for a in coll.ordered_artifacts.all()] Shell
# sddb client: download every member .zarr into data/
sddb-cli download --collection geo-gse200310 --dest data/ Licenses: 2 NCBI GEO policy
Member datasets · 2
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