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ggNetView manual documentation

1 ggNetView manual documentation

1.1 Introdution

Network analysis has been widely applied in the life sciences, microbiology, ecology, and agronomy to quantify interactions among genes, proteins, metabolites, microorganisms, and environmental factors. These interactions collectively shape the functioning of biological and ecological systems. Despite its broad adoption, existing tools often face limitations in flexibility, customization, reproducibility, and the generation of publication-ready figures.

To address these challenges, ggNetView was developed as an R package that integrates ggplot2, ggraph, and tidygraph within the Grammar of Graphics framework, enabling fully reproducible and highly customizable network visualizations. The package provides deterministic layout algorithms, comprehensive topological analyses, modular coloring schemes, hierarchical annotations, and consistent theming, ensuring standardized and interpretable graphical output.

Although initially designed for applications in soil science and microbial ecology, ggNetView is broadly applicable to network analyses in molecular biology, including WGCNA and protein–protein interaction (PPI) networks. By lowering technical barriers in network construction and visualization, ggNetView enables researchers across disciplines to efficiently produce reproducible, publication-quality network figures.

1.2 Installation

Step1: install CRAN dependencies

cran_pkgs <- c(
  "boot", "dplyr", "FNN", "future", "future.apply",
  "ggforce", "ggnewscale", "ggplot2", "ggraph", "ggrepel",
  "Hmisc", "huge", "igraph", "magrittr", "MASS",
  "Matrix", "patchwork", "progressr", "psych", "purrr",
  "qgraph", "Rcpp", "RcppArmadillo", "readr", "rlang",
  "scales", "scatterpie", "stringr", "tibble", "tidygraph",
  "tidyr", "vegan", "VGAM", "WGCNA"
)

new_pkgs <- cran_pkgs[!cran_pkgs %in% installed.packages()[, "Package"]]
if (length(new_pkgs)) install.packages(new_pkgs)

Step2: (optional) install suggested packages

These packages are not required for the core functionality, but enable additional features (e.g. dynamic tree cut, node influence, vignettes, tests):

install.packages(c("dynamicTreeCut", "influential",
                   "knitr", "rmarkdown",
                   "RobustRankAggreg", "testthat"))

Step3: install ggNetView from GitHub

# install.packages("devtools")
devtools::install_github("Jiawang1209/ggNetView")

1.3 Citation

If you use ggNetView in your research, please cite:

Yue Liu, Chao Wang (2025). ggNetView: An R package for complex biological and ecological network analysis and visualization. R package version 0.1.0. 
https://github.com/Jiawang1209/ggNetView

1.4 Source Code

The source code for ggNetView is available in the ggNetView repository.

https://github.com/Jiawang1209/ggNetView