To define the cellular composition and spatial architecture of the tumor micoenvironment, we combined single-cell RNA-sequencing, spatial transcriptomics, and multiplexed ion-beam imaging from 10 patient cutaneous squamous cell carcinoma tumors and site-matched normal skin
from sddb import Catalog
cohort = Catalog().collection("geo-gse144239")
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/")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-gse144239")
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()]# sddb client: download every member .zarr into data/
sddb-cli download --collection geo-gse144239 --dest data/Licenses: 4 NCBI GEO policy
@article{Ji_2020,
title = {Multimodal Analysis of Composition and Spatial Architecture in Human Squamous Cell Carcinoma},
volume = {182},
ISSN = {0092-8674},
url = {http://dx.doi.org/10.1016/j.cell.2020.05.039},
DOI = {10.1016/j.cell.2020.05.039},
number = {2},
journal = {Cell},
publisher = {Elsevier BV},
author = {Ji, Andrew L. and Rubin, Adam J. and Thrane, Kim and Jiang, Sizun and Reynolds, David L. and Meyers, Robin M. and Guo, Margaret G. and George, Benson M. and Mollbrink, Annelie and Bergenstråhle, Joseph and Larsson, Ludvig and Bai, Yunhao and Zhu, Bokai and Bhaduri, Aparna and Meyers, Jordan M. and Rovira-Clavé, Xavier and Hollmig, S. Tyler and Aasi, Sumaira Z. and Nolan, Garry P. and Lundeberg, Joakim and Khavari, Paul A.},
year = {2020},
month = July,
pages = {497–514.e22}
}