Visualize network with module-environment heatmaps — ggnetview_modularity

Combines ggNetView network visualization with four environmental correlation heatmaps. Module-environment relationships are computed using module eigengenes (recommended) or module relative abundance, then correlated with environmental factors. Links connect module centroids to heatmap diagonals.

Usage

ggnetview_modularity_heatmaps(
  graph_obj,
  env,
  otu_mat,
  env_select = NULL,
  module_index = c("eigengene", "abundance"),
  abundance_type = c("sum", "mean"),
  relation_method = c("correlation", "mantel"),
  cor.method = c("pearson", "kendall", "spearman"),
  cor.use = c("everything", "all", "complete", "pairwise", "na"),
  mantel.method2 = c("pearson", "kendall", "spearman"),
  drop_nonsig = FALSE,
  layout = "gephi",
  layout.module = c("random", "adjacent", "order"),
  orientation = c("top_right", "bottom_right", "top_left", "bottom_left"),
  distance = 3,
  r = 6,
  HeatmapScale = 1,
  SigLineAlpha = 0.5,
  HeatmapLabelSize = 5,
  HeatmapSigSize = 5,
  HeatmapColorBar = NULL,
  HeatmapLabelOrient = 0,
  SigLineWidth = c(0.5, 2),
  SigLineColor = c("#fdbb84", "#d7301f"),
  HeatmapPointSize = 5,
  HeatmapPointFill = "#de77ae",
  HeatmapTileColor = NA,
  HeatmapTileSize = 0,
  ...
)

Arguments

graph_obj: A graph object from build_graph_from_mat or build_graph_from_df.
env: Data frame or matrix of environmental variables (samples as rows).
otu_mat: Numeric matrix. Rows = OTUs/ASVs, columns = samples. Used to compute module eigengenes or module abundance. Must align with graph_obj node names (rownames) and env sample IDs.
env_select: Named list. Column indices or names for each env block. Each block corresponds to one heatmap quadrant. E.g. list(Env01 = 1:5, Env02 = 6:10, Env03 = 11:15, Env04 = 16:20).
module_index: Character. How to represent each module for env correlation: "eigengene" (default, PC1 of module OTUs) or "abundance" (sum/mean of module OTU abundances).
abundance_type: Character. When module_index = "abundance", use "sum" or "mean".
relation_method: "correlation" or "mantel".
cor.method: Correlation method: "pearson", "kendall", "spearman".
cor.use: Handling of missing values in correlation.
mantel.method2: Correlation for Mantel test.
drop_nonsig: Logical. Drop non-significant links from plot.
layout: Character. Layout for ggNetView (e.g. "gephi", "square").
orientation: Character vector. Heatmap quadrants: "top_right", "bottom_right", "top_left", "bottom_left".
distance: Numeric. Gap between the scaled network boundary and the environmental heatmaps.
r: Numeric. Effective radius for scaling the central network.
HeatmapScale: Numeric (default = 1). Global scale factor for the overall heatmap size. Values > 1 enlarge the whole heatmap layout.
SigLineAlpha: Numeric (default = 0.5). Transparency for module–heatmap link lines. Must be between 0 and 1.
SigLineWidth: Numeric vector of length 2 (default = c(0.5, 2)). Min and max line width for module–heatmap links. Line width is mapped from -log10(p-value): smaller p (more significant) → thicker line. E.g. p=0.05→1.3, p=0.01→2, p=0.001→3; values are scaled to this range.
SigLineColor: Character vector of length 2. Colors for link gradient (low and high correlation).
...: Additional arguments passed to layout and network rendering, including: layout, layout.module, shrink, jitter, add_outer, add_group_outer, label (logical or character: module labels in ggNetView style), labelsize, labelsegmentsize, labelsegmentalpha, fill, color, pointsize.

Value

A list: [[1]] ggplot with straight links, [[2]] ggplot with curved links, [[3]] data frame of module-env correlation stats.