Collections / Visium Spatial transcriptomics analysis of human primary colorectal cancer
Visium Spatial transcriptomics analysis of human primary colorectal cancer
To reveal the spatial distribution and the difference gene expression pattern of cancer cells in colorectal cancer, Visium spatial transcriptomics of four CRC patients was applied
Datasets4
Size~240 MB
AssayVisium
Samplehuman · colorectum
KindReplicates
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Python · sddb client
from sddb import Catalog
cohort = Catalog().collection("geo-gse226997")
cohort.members # the 4 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-gse226997")
coll.ordered_artifacts.to_dataframe() # the 4 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-gse226997 --dest data/ Licenses: 4 NCBI GEO policy
Member datasets · 4
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