Collections / Fragment-sequencing unveils local tissue microenvironments at single cell resolution

Fragment-sequencing unveils local tissue microenvironments at single cell resolution

The spatial organization of cells within tissues is tightly linked to their biological function. Yet, methods to probe the entire transcriptome of multiple native tissue microenvironments at single cell resolution are lacking. Here, we introduce fragment-sequencing, a method that enables the transcriptomic characterization of single cells within spatially distinct tissue niches. Fragment-sequencing of the mouse metastatic liver revealed previously uncharacterized zonated genes and ligand-receptor interactions enriched in the different hepatic microenvironments and the metastatic niche.

Datasets2
Size~61.6 MB
AssayVisium
Samplemouse · liver
KindOther
Flag a data issue
PMID:38012149 ↗
Download the whole collection
Python · sddb client 
from sddb import Catalog

cohort = Catalog().collection("geo-gse216189")
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="geo-gse216189")
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 geo-gse216189 --dest data/
Install (Python 3.12+) Docs →

Licenses: 2 NCBI GEO policy

Member datasets · 2
Open in Vitessce
Visium
Mouse liver
GSM6661400
mouse liver 30.8 MB 3,751 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismmouse
Tissueliver
Size30.8 MB
Spots3,751
Magnificationother · 4.176 µm/px
bronze H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Mouse liver
GSM6661401
mouse liver 30.8 MB 3,606 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismmouse
Tissueliver
Size30.8 MB
Spots3,606
Magnificationother · 3.764 µm/px
bronze H&E NCBI GEO policy Open in Vitessce

Cite this collection

doi.org/10.1038/s41467-023-43005-8 ↗
BibTeX 
@article{Handler_2023,
  title = {Fragment-sequencing unveils local tissue microenvironments at single-cell resolution},
  volume = {14},
  ISSN = {2041-1723},
  url = {http://dx.doi.org/10.1038/s41467-023-43005-8},
  DOI = {10.1038/s41467-023-43005-8},
  number = {1},
  journal = {Nature Communications},
  publisher = {Springer Science and Business Media LLC},
  author = {Handler, Kristina and Bach, Karsten and Borrelli, Costanza and Piscuoglio, Salvatore and Ficht, Xenia and Acar, Ilhan E. and Moor, Andreas E.},
  year = {2023},
  month = Nov
}