Plate IV.296 · Publications
Squidpy: a scalable framework for spatial single cell analysis
Preprint in bioRxiv, 20 February 2021.
Abstract
Spatial omics data are advancing the study of tissue organization and cellular communication at an unprecedented scale. Here, we present Squidpy, a Python framework that brings together tools from omics and image analysis to enable scalable description of spatial molecular data, such as transcriptome or multivariate proteins. Squidpy provides both infrastructure and numerous analysis methods that allow to efficiently store, manipulate and interactively visualize spatial omics data.
Cite
@misc{palla2021squidpy,
title = {{Squidpy: a scalable framework for spatial single cell analysis}},
author = {Palla, Giovanni and Spitzer, Hannah and Klein, Michal and Fischer, David and Schaar, Anna Christina and Kuemmerle, Louis Benedikt and Rybakov, Sergei and Ibarra, Ignacio L. and Holmberg, Olle and Virshup, Isaac and Lotfollahi, Mohammad and Richter, Sabrina and Theis, Fabian J.},
howpublished = {bioRxiv},
publisher = {openRxiv},
year = {2021},
month = feb,
doi = {10.1101/2021.02.19.431994},
url = {https://doi.org/10.1101/2021.02.19.431994},
note = {Preprint}
}