Collections / A single-cell transcriptomic analysis of endometriosis

A single-cell transcriptomic analysis of endometriosis

Datasets2
Size~1.1 GB
AssayVisium
Samplehuman · uterus
KindPublication
Flag a data issue
10.1038/s41588-022-01254-1 ↗
Download the whole collection
Python · sddb client 
from sddb import Catalog

cohort = Catalog().collection("doi-10-1038-s41588-022-01254-1")
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/")
Install (Python 3.12+) Docs →
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="doi-10.1038/s41588-022-01254-1")
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()]
Install (Python 3.12+) Docs →
Shell 
# sddb client: download every member .zarr into data/
sddb-cli download --collection doi-10-1038-s41588-022-01254-1 --dest data/
Install (Python 3.12+) Docs →

Licenses: 2 CC BY-NC-SA 4.0

About the study

Single-cell transcriptomic analysis of endometriosis.

Read the abstract at the source →
Member datasets · 2
Open in Vitessce
Visium
Human uterus
NCBI690
human uterus endometriosis 596 MB 1,960 spots silver H&E
TechnologyVisium
Organismhuman
Tissueuterus
Conditionendometriosis
Size596 MB
Spots1,960
Magnification20x · 0.503 µm/px
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human uterus
NCBI691
human uterus endometriosis 537 MB 1,388 spots silver H&E
TechnologyVisium
Organismhuman
Tissueuterus
Conditionendometriosis
Size537 MB
Spots1,388
Magnification20x · 0.504 µm/px
silver H&E Open in Vitessce

Cite this collection

doi.org/10.1038/s41588-022-01254-1 ↗
BibTeX 
@article{Fonseca_2023,
  title = {Single-cell transcriptomic analysis of endometriosis},
  volume = {55},
  ISSN = {1546-1718},
  url = {http://dx.doi.org/10.1038/s41588-022-01254-1},
  DOI = {10.1038/s41588-022-01254-1},
  number = {2},
  journal = {Nature Genetics},
  publisher = {Springer Science and Business Media LLC},
  author = {Fonseca, Marcos A. S. and Haro, Marcela and Wright, Kelly N. and Lin, Xianzhi and Abbasi, Forough and Sun, Jennifer and Hernandez, Lourdes and Orr, Natasha L. and Hong, Jooyoon and Choi-Kuaea, Yunhee and Maluf, Horacio M. and Balzer, Bonnie L. and Fishburn, Aaron and Hickey, Ryan and Cass, Ilana and Goodridge, Helen S. and Truong, Mireille and Wang, Yemin and Pisarska, Margareta D. and Dinh, Huy Q. and EL-Naggar, Amal and Huntsman, David G. and Anglesio, Michael S. and Goodman, Marc T. and Medeiros, Fabiola and Siedhoff, Matthew and Lawrenson, Kate},
  year = {2023},
  month = Jan,
  pages = {255–267}
}