Mouse tendon
GSM6661595
mouse tendon 11.8 MB 824 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismmouse
Tissuetendon
Spots824
Magnificationother · 3.847 µm/px
bronze H&E NCBI GEO policy
Collections / Defining the spatial-molecular map of fibrotic tendon healing and the drivers of Scleraxis-lineage cell fate and function
Defining the spatial-molecular map of fibrotic tendon healing and the drivers of Scleraxis-lineage cell fate and function
Spatial transcriptomic analysis of murine FDL tendons following acute injury and repair to evaluate spatiotemporal programming of tendon healing
Datasets8
Size~119 MB
AssayVisium
Samplemouse · tendon
KindTime course
Download the whole collection
Python · sddb client
from sddb import Catalog
cohort = Catalog().collection("geo-gse216214")
cohort.members # the 8 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-gse216214")
coll.ordered_artifacts.to_dataframe() # the 8 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-gse216214 --dest data/Licenses: 8 NCBI GEO policy
Member datasets · 8
Mouse tendon
GSM6661597
mouse tendon 23.2 MB 1,495 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismmouse
Tissuetendon
Spots1,495
Magnificationother · 3.338 µm/px
bronze H&E NCBI GEO policy
Mouse tendon
GSM6661598
mouse tendon 23.1 MB 1,706 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismmouse
Tissuetendon
Spots1,706
Magnificationother · 3.352 µm/px
bronze H&E NCBI GEO policy
Mouse tendon
GSM6661599
mouse tendon 12.5 MB 875 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismmouse
Tissuetendon
Spots875
Magnificationother · 3.808 µm/px
bronze H&E NCBI GEO policy
Mouse tendon
GSM6661594
mouse tendon 13.5 MB 1,025 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismmouse
Tissuetendon
Spots1,025
Magnificationother · 3.341 µm/px
bronze H&E NCBI GEO policy
Mouse tendon
GSM6661593
mouse tendon 5.8 MB 650 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismmouse
Tissuetendon
Spots650
Magnificationother · 3.842 µm/px
bronze H&E NCBI GEO policy
Mouse tendon
GSM6661596
mouse tendon 16.4 MB 1,017 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismmouse
Tissuetendon
Spots1,017
bronze H&E NCBI GEO policy
Mouse tendon
GSM6661600
mouse tendon 12.4 MB 873 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismmouse
Tissuetendon
Spots873
Magnificationother · 3.353 µm/px
bronze H&E NCBI GEO policy
Cite this collection
doi.org/10.1016/j.celrep.2022.111706 ↗ BibTeX
@article{Ackerman_2022,
title = {Defining the spatial-molecular map of fibrotic tendon healing and the drivers of Scleraxis-lineage cell fate and function},
volume = {41},
ISSN = {2211-1247},
url = {http://dx.doi.org/10.1016/j.celrep.2022.111706},
DOI = {10.1016/j.celrep.2022.111706},
number = {8},
journal = {Cell Reports},
publisher = {Elsevier BV},
author = {Ackerman, Jessica E. and Best, Katherine T. and Muscat, Samantha N. and Pritchett, Elizabeth M. and Nichols, Anne E.C. and Wu, Chia-Lung and Loiselle, Alayna E.},
year = {2022},
month = Nov,
pages = {111706}
}