ggClusterNet v.2.00 (2025.2)

Since the last version release in 2022, ggClusterNet has emerged as a critical resource for microbiome research, enabling microbial co-occurrence network analysis and visualization in over 200 studies (Google Scholar citations). To address emerging challenges in microbiome studies, including multi-factor experimental designs, multi-treatment, and multi-omics data, we present a comprehensive upgrade with the following four components: 1) We recommended and designed a microbial co-occurrence network analysis pipeline incorporating network computation and visualization (Pearson/Spearman/SparCC correlations), topological characterization of network and node properties, multi-network structure comparison and statistical testing, exploration of network stability (robustness), and identification and analysis of network modules; 2) Developed microbial network mining functions for multi-factor, multi-treatment, and spatiotemporal-scale analysis, such as Facet. Network(), module.compare.m.ts(), Robustness.Random.removal.ts(), etc.; 3) Developed functions for microbial and multi-factor interaction analysis, along with versatile visualization layout algorithms, such as MatCorPlot2(), Miccorplot3(), cor_link3(), matcorplotj(), and two.cor(); 4) Developed functions for cross-domain and multi-omics integrated network analysis, including corBionetwork.st(), and developed a comprehensive suite of visualization layout algorithms specifically designed for exploring complex relationships in these networks, such as model_maptree2(), model_Gephi.3(), cir.squ(), and cir.maptree2(). Collectively, the latest updates to ggClusterNet 2.0 empower researchers to explore complex network interactions with enhanced capabilities, offering a robust, efficient, user-friendly, reproducible, and visually versatile tool for microbial co-occurrence networks and associated indicator correlation patterns. The ggClusterNet 2.0 R package is open-source and freely accessible on GitHub (https://github.com/taowenmicro/ggClusterNet).