Coccidioidomycosis, or Valley Fever, is a lung disease caused by inhaling Coccidioides fungi, prevalent in the Southwestern U.S., Mexico, and parts of Central and South America. Climate change is contributing to the spread of this disease. Many cases are asymptomatic, some are often misdiagnosed, and a small subset can progress to severe illness. To better understand lung responses during late Coccidioides infection, we used 10x Visium spatial transcriptomics. We analyzed non-infected lung (D0) and infected lung at 14 days post-infection (D14).
from sddb import Catalog
cohort = Catalog().collection("geo-gse274767")
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/")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-gse274767")
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()]# sddb client: download every member .zarr into data/
sddb-cli download --collection geo-gse274767 --dest data/Licenses: 2 NCBI GEO policy
@article{Davalos_2025,
title = {Spatiotemporal analysis of lung immune dynamics in lethal
<i>Coccidioides posadasii</i>
infection},
volume = {16},
ISSN = {2150-7511},
url = {http://dx.doi.org/10.1128/mbio.02562-24},
DOI = {10.1128/mbio.02562-24},
number = {5},
journal = {mBio},
publisher = {American Society for Microbiology},
author = {Davalos, Oscar A. and Sebastian, Aimy and Leon, Nicole F. and Rangel, Margarita V. and Miranda, Nadia and Murugesh, Deepa K. and Phillips, Ashlee M. and Hoyer, Katrina K. and Hum, Nicholas R. and Loots, Gabriela G. and Weilhammer, Dina R.},
editor = {Shlezinger, Neta},
year = {2025},
month = May
}