
==== Front
ArXiv
ArXiv
arxiv
ArXiv
2331-8422
Cornell University

arXiv:2409.09469v1
2409.09469
1
preprint
Article
Hyperedge Representations with Hypergraph Wavelets: Applications to Spatial Transcriptomics
Sun Xingzhi
Xu Charles
Rocha João F.
Liu Chen
Hollander-Bodie Benjamin
Goldman Laney
DiStasio Marcello
Perlmutter Michael
Krishnaswamy Smita
14 9 2024
arXiv:2409.09469v1https://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License, which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use.
http://arxiv.org/abs/2409.09469v1
nihpp-2409.09469v1.pdf
In many data-driven applications, higher-order relationships among multiple objects are essential in capturing complex interactions. Hypergraphs, which generalize graphs by allowing edges to connect any number of nodes, provide a flexible and powerful framework for modeling such higher-order relationships. In this work, we introduce hypergraph diffusion wavelets and describe their favorable spectral and spatial properties. We demonstrate their utility for biomedical discovery in spatially resolved transcriptomics by applying the method to represent disease-relevant cellular niches for Alzheimer's disease.
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pmc
