Provides a unified, reproducible framework for analyzing and visualizing complex biological, ecological, and microbial association networks.
Includes tools for building correlation and co-occurrence networks via WGCNA, SpiecEasi, SparCC, and standard correlation methods (Pearson, Spearman, Kendall).
Computes node-level and network-level topological metrics, including robustness analyses.
Offers a large family of deterministic layout generators built on ggraph and ggplot2 (bipartite, tripartite, quadripartite, pentapartite, circular-modules, petal, diamond, heart, star, and more), all with reproducible seeds.
Ships 18 example datasets covering OTU tables, taxonomy tables, environmental metadata, PPI networks, and modularity examples.