Hyperpathway transforms pathway enrichment analysis results into network-based visualizations, suggesting new insights in omics data interpretation.
Pathway enrichment analysis (PEA) is fundamental for interpreting omics signatures. Standard PEA practice reduces results to tabular significance lists, where complex systems‑biology insights reside undisclosed. Here, we present Hyperpathway, an open-access network-based visualization webtool for PEA’s results interpretation. Given a table of statistically significant pathways and enriched molecules, Hyperpathway transforms this tabular information into a pathway–molecule bipartite network. Then it embeds the network into a two-dimensional hyperbolic disk, providing a holistic geometric representation of the nodes hierarchical organization along the radial coordinates, and the nodes similarity patterns along the angular coordinates. On genomic, metabolomic, and lipidomic datasets, Hyperpathway allows a deeper understanding of the interplay between pathways and their molecular components, facilitating the visualization and identification of latent functional systems biology modules not readable in conventional PEA tabular outputs. By bridging statistical enrichment analysis with network geometry, Hyperpathway advances pathway analysis from a list-based to a systems-level visualization paradigm.
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Abdelhamid et al. (2025) studied this question.
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