Abstract
Summary Networks provide a powerful framework to analyze spatial omics experiments. However, we lack tools that integrate several methods to easily reconstruct networks for further analyses with dedicated libraries. In addition, choosing the appropriate method and parameters can be challenging.
We propose tysserand, a Python library to reconstruct spatial networks from spatially resolved omics experiments. It is intended as a common tool to which the bioinformatics community can add new methods to reconstruct networks, choose appropriate parameters, clean resulting networks and pipe data to other libraries.
Availability and implementation tysserand software and tutorials with a Jupyter notebook to reproduce the results are available at https://github.com/VeraPancaldiLab/tysserand
Supplementary information Supplementary data are available at Bioarxiv online.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
Contact: alexis.coullomb{at}inserm.fr, vera.pancaldi{at}inserm.fr
- definition of a quality of reconstructed networks - comparison of quality of reconstructed networks for tysserand's and PySAL's methods on simulated and real data - addition of utilities to facilitate interactive visualization, creation and modification of networks on bioimages with the napari library