Collections / Integrating spatial gene expression and breast tumour morphology via deep learning
Integrating spatial gene expression and breast tumour morphology via deep learning
Datasets84
Size~13 GB
Assayspatial transcriptomics
Samplemultiple · multiple
KindComparison
Download the whole collection
Python · lamindb
import lamindb as ln
import spatialdata as sd
coll = ln.Collection.get(key="doi-10.1126/science.aaf2403")
coll.ordered_artifacts.df() # the 84 members, ordered
# download every member .zarr to the local cache:
paths = [a.cache() for a in coll.ordered_artifacts.all()]
# …or load each straight into memory as a SpatialData object:
sdatas = {a.key: sd.read_zarr(a.cache()) for a in coll.ordered_artifacts.all()} About the study
Visualization and analysis of gene expression in tissue sections by spatial transcriptomics.
Read the abstract at the source →Member datasets · 84
Human breast
SPA75
human breast invasive ductal breast carcinoma 90 MB 284 obs silver H&E
Technologyspatial transcriptomics
Organismhuman
Tissuebreast
Conditioninvasive ductal breast carcinoma
Obs284
silver H&E
Cite this collection
doi.org/10.1126/science.aaf2403 ↗ BibTeX
@article{St_hl_2016,
title = {Visualization and analysis of gene expression in tissue sections by spatial transcriptomics},
volume = {353},
ISSN = {1095-9203},
url = {http://dx.doi.org/10.1126/science.aaf2403},
DOI = {10.1126/science.aaf2403},
number = {6294},
journal = {Science},
publisher = {American Association for the Advancement of Science (AAAS)},
author = {Ståhl, Patrik L. and Salmén, Fredrik and Vickovic, Sanja and Lundmark, Anna and Navarro, José Fernández and Magnusson, Jens and Giacomello, Stefania and Asp, Michaela and Westholm, Jakub O. and Huss, Mikael and Mollbrink, Annelie and Linnarsson, Sten and Codeluppi, Simone and Borg, Åke and Pontén, Fredrik and Costea, Paul Igor and Sahlén, Pelin and Mulder, Jan and Bergmann, Olaf and Lundeberg, Joakim and Frisén, Jonas},
year = {2016},
month = July,
pages = {78–82}
}