Collections / 10x-xenium-human-lung-cancer-post-xenium-technote

10x-xenium-human-lung-cancer-post-xenium-technote

Datasets2
Size~23.0 GB
Assay10x Xenium
Samplehuman · lung
KindOther
Flag a data issue
Python · sddb client
from sddb import Catalog

cohort = Catalog().collection("10x-xenium-human-lung-cancer-post-xenium-technote")
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="10x-xenium-human-lung-cancer-post-xenium-technote")
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 10x-xenium-human-lung-cancer-post-xenium-technote --dest data/

Licenses: 2 CC BY 4.0

Open in Vitessce
10x Xenium
Human lung
xenium-human-lung-cancer-post-xenium-technote__human-lung-cancer-ffpe
human lung lung cancer 6.3 GB 278,659 cells silver H&E
Technology10x Xenium
Organismhuman
Tissuelung
Conditionlung cancer
Size6.3 GB
Cells278,659
Magnification40x · 0.012 µm/px
silver H&E Open in Vitessce
Open in Vitessce
10x Xenium
Human lung
xenium-human-lung-cancer-post-xenium-technote__prime-human-lung-cancer-ffpe
human lung lung cancer 16.6 GB 278,328 cells silver H&E
Technology10x Xenium
Organismhuman
Tissuelung
Conditionlung cancer
Size16.6 GB
Cells278,328
Magnification40x · 0.010 µm/px
silver H&E Open in Vitessce