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Biological network analysis has become an important approach for investigating interactions among microorganisms, genes, proteins, and environmental variables across ecology, microbiology, and molecular biology. In practice, however, turning an inferred network into a clear figure and a full set of downstream topology and module analyses remains laborious, because the required steps are spread across several packages and are often finished by hand in a graphics editor. In response to these challenges, we have developed ggNetView, an R package that provides a complete analytical workflow. Its upstream step constructs networks from a variety of data sources, and its downstream steps encompass topology analysis, module analysis, and network visualization. The package utilizes a unified graph object, offers functions for geometric layout construction and annotation, and enables different types of networks to share a consistent set of aesthetic mappings. Beyond visualization, ggNetView enables comparison of similar modules across multiple networks and supports association analysis of the entire network and its subnetworks with environmental variables to help identify candidate modules associated with environmental variables. ggNetView has been applied to microbiome co‐occurrence, WGCNA‐derived co‐expression, and protein–protein interaction networks. Across repeated runs with the same graph object and parameters, node coordinates are reproduced. The package is freely available at https://github.com/Jiawang1209/ggNetView .
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Liu et al. (2026) studied this question.
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