from sddb import Catalog
cohort = Catalog().collection("doi-10-1126-science-aav9776")
cohort.members # the 302 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/")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="doi-10.1126/science.aav9776")
coll.ordered_artifacts.to_dataframe() # the 302 members, ordered
# download every member .zarr to the local cache:
paths = [a.cache() for a in coll.ordered_artifacts.all()]# sddb client: download every member .zarr into data/
sddb-cli download --collection doi-10-1126-science-aav9776 --dest data/Licenses: 302 CC BY-NC-SA 4.0
@article{Maniatis_2019,
title = {Spatiotemporal dynamics of molecular pathology in amyotrophic lateral sclerosis},
volume = {364},
ISSN = {1095-9203},
url = {http://dx.doi.org/10.1126/science.aav9776},
DOI = {10.1126/science.aav9776},
number = {6435},
journal = {Science},
publisher = {American Association for the Advancement of Science (AAAS)},
author = {Maniatis, Silas and Äijö, Tarmo and Vickovic, Sanja and Braine, Catherine and Kang, Kristy and Mollbrink, Annelie and Fagegaltier, Delphine and Andrusivová, Žaneta and Saarenpää, Sami and Saiz-Castro, Gonzalo and Cuevas, Miguel and Watters, Aaron and Lundeberg, Joakim and Bonneau, Richard and Phatnani, Hemali},
year = {2019},
month = Apr,
pages = {89–93}
}