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HAT: Hypergraph analysis toolbox

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Listed:
  • Joshua Pickard
  • Can Chen
  • Rahmy Salman
  • Cooper Stansbury
  • Sion Kim
  • Amit Surana
  • Anthony Bloch
  • Indika Rajapakse

Abstract

Recent advances in biological technologies, such as multi-way chromosome conformation capture (3C), require development of methods for analysis of multi-way interactions. Hypergraphs are mathematically tractable objects that can be utilized to precisely represent and analyze multi-way interactions. Here we present the Hypergraph Analysis Toolbox (HAT), a software package for visualization and analysis of multi-way interactions in complex systems.Author summary: Classical networks typically focus on pairwise interactions and may overlook the intricate higher-order, multi-way interactions that occur among groups of nodes within a network. Our research has delved into the structural and dynamic characteristics of hypergraphs, which can effectively capture multi-way network interactions across various domains and data types. In this article, we introduce the Hypergraph Analysis Toolbox (HAT), a software package encompassing a range of techniques to identify, investigate, and visualize multi-way interactions in biological data.

Suggested Citation

  • Joshua Pickard & Can Chen & Rahmy Salman & Cooper Stansbury & Sion Kim & Amit Surana & Anthony Bloch & Indika Rajapakse, 2023. "HAT: Hypergraph analysis toolbox," PLOS Computational Biology, Public Library of Science, vol. 19(6), pages 1-7, June.
    • Handle: RePEc:plo:pcbi00:1011190
    DOI: 10.1371/journal.pcbi.1011190
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    1. Drezner, Zvi, 1995. "Multirelation -- a correlation among more than two variables," Computational Statistics & Data Analysis, Elsevier, vol. 19(3), pages 283-292, March.
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