motifs: Network Motif Analysis

In cograph: Analysis and Visualization of Complex Networks

Network Motif Analysis

Description

Two modes of motif analysis for networks:

• Census (named_nodes = FALSE, default): Counts MAN type frequencies with significance testing. Nodes are exchangeable.

• Instances (named_nodes = TRUE, or use subgraphs()): Lists specific node triples forming each pattern. Nodes are NOT exchangeable.

Usage

motifs(
  x,
  named_nodes = FALSE,
  actor = NULL,
  window = NULL,
  window_type = c("rolling", "tumbling"),
  pattern = c("triangle", "network", "closed", "all"),
  include = NULL,
  exclude = NULL,
  significance = TRUE,
  n_perm = 1000L,
  min_count = if (named_nodes) 5L else NULL,
  edge_method = c("any", "expected", "percent"),
  edge_threshold = 1.5,
  min_transitions = 5,
  top = NULL,
  seed = NULL
)

## S3 method for class 'cograph_motif_result'
plot(
  x,
  type = c("triads", "types", "significance", "patterns"),
  n = 15,
  ncol = 5,
  colors = c("#2166AC", "#B2182B"),
  ...
)

Arguments

x	Input data: a tna object, cograph_network, matrix, igraph, or data.frame (edge list).
named_nodes	Logical. If FALSE (default), performs census (type-level counts). If TRUE, extracts specific node triples (instance-level). subgraphs() is a convenience wrapper that sets this to TRUE.
actor	Character. Column name in the edge list metadata to group by. If NULL (default), auto-detects standard column names (session_id, session, actor, user, participant). If no grouping column found, performs aggregate analysis.
window	Numeric. Window size for windowed analysis. Splits each actor's transitions into windows of this size. NULL (default) means no windowing.
window_type	Character. Window type: "rolling" (default) or "tumbling". Only used when window is set.
pattern	Pattern filter: "triangle" (default), "network", "closed", "all".
include	Character vector of MAN types to include exclusively. Overrides pattern.
exclude	Character vector of MAN types to exclude. Applied after pattern filter.
significance	Logical. Run permutation significance test? Default TRUE.
n_perm	Number of permutations for significance. Default 1000.
min_count	Minimum observed count to include a triad (instance mode only). Default 5 for instances, NULL for census.
edge_method	Method for determining edge presence: "any" (default), "expected", or "percent".
edge_threshold	Threshold for "expected" or "percent" methods. Default 1.5.
min_transitions	Minimum total transitions for a unit to be included. Default 5.
top	Return only the top N results. NULL returns all.
seed	Random seed for reproducibility.
type	Plot type: "triads" (network diagrams), "types" (bar chart), "significance" (z-score plot), "patterns" (abstract MAN diagrams).
n	Number of items to plot. Default 15.
ncol	Number of columns in triad grid. Default 5.
colors	Colors for visualization. Default blue/red.
...	Additional arguments passed to plot helpers.

Details

Detects input type and analysis level automatically. For inputs with individual/group data (tna objects, cograph networks from edge lists with metadata), performs per-group analysis. For aggregate inputs (matrices, igraph), analyzes the single network.

Value

A cograph_motif_result object with:

results

Data frame of results. Census: type, count, (z, p, sig). Instances: triad, type, observed, (z, p, sig).

type_summary

Named counts by MAN type

level

Analysis level: "individual" or "aggregate"

named_nodes

Whether nodes are identified (TRUE) or exchangeable (FALSE)

n_units

Number of units analyzed

params

List of parameters used

See Also

subgraphs(), motif_census(), extract_motifs()

Other motifs: extract_motifs(), extract_triads(), get_edge_list(), motif_census(), plot.cograph_motif_analysis(), plot.cograph_motifs(), subgraphs(), triad_census()

Examples

## Not run: 
# Census from a matrix
mat <- matrix(c(0,3,2,0, 0,0,5,1, 0,0,0,4, 2,0,0,0), 4, 4, byrow = TRUE)
rownames(mat) <- colnames(mat) <- c("Plan","Execute","Monitor","Adapt")
motifs(mat, significance = FALSE)

if (requireNamespace("tna", quietly = TRUE)) {
  # Census from tna object
  Mod <- tna::tna(tna::group_regulation)
  motifs(Mod)

  # Instances: specific node triples
  subgraphs(Mod)
}

## End(Not run)

cograph documentation built on April 1, 2026, 1:07 a.m.