PT  - JOURNAL ARTICLE
AU  - Alexis Coullomb
AU  - Vera Pancaldi
TI  - Tysserand - Fast reconstruction of spatial networks from bioimages
AID  - 10.1101/2020.11.16.385377
DP  - 2020 Jan 01
TA  - bioRxiv
PG  - 2020.11.16.385377
4099  - http://biorxiv.org/content/early/2020/11/17/2020.11.16.385377.short
4100  - http://biorxiv.org/content/early/2020/11/17/2020.11.16.385377.full
AB  - Motivation 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.Summary We propose tysserand, a Python library to reconstruct spatial networks from spatially resolved omics experiments. It is intended as a common tool where the bioinformatics community can add new methods to reconstruct networks, choose appropriate parameters, clean resulting networks and pipe data to other libraries.Availability tysserand software and tutorials with a Jupyter notebook to reproduce the results are available at https://github.com/VeraPancaldiLab/tysserandContact vera.pancaldi{at}inserm.frSupplementary information Supplementary data are available at Bioarxiv online.Competing Interest StatementThe authors have declared no competing interest.