Collections / Spatial component of: CELSR3 deficiency leads to tic-related behaviors and dopaminergic alterations in the striatum
Spatial component of: CELSR3 deficiency leads to tic-related behaviors and dopaminergic alterations in the striatum
The gene CELSR3 (cadherin EGF LAG seven‐pass-G‐type receptor 3) has been recently recognized as a high-confidence risk factor for tic disorders (TD). Celsr3 mutant mice displayed tic-like grooming stereotypies and jerks, as well as sensorimotor gating deficits, which were opposed by TD therapies. Spatial transcriptomic analyses revealed that Celsr3 mutants featured abnormalities of the extracellular matrix in the striatum. Notably, there are alterations in collagen and extracellular organization.
Datasets4
Size~432 MB
AssayVisium
Samplemouse · brain
KindComparison
Download the whole collection
Python · sddb client
from sddb import Catalog
cohort = Catalog().collection("geo-gse280709")
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-gse280709")
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-gse280709 --dest data/ Licenses: 4 NCBI GEO policy
Member datasets · 4
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