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Network Motif Analysis

Source: R/motifs.R
motif_census.Rd

Analyze recurring subgraph patterns (motifs) in networks and test their statistical significance against null models.

Usage

motif_census(
  x,
  size = 3,
  n_random = 100,
  method = c("configuration", "gnm"),
  directed = NULL,
  seed = NULL
)

# S3 method for class 'cograph_motifs'
print(x, ...)

Arguments

x

A matrix, igraph object, or cograph_network

size

Motif size: 3 (triads) or 4 (tetrads). Default 3.

n_random

Number of random networks for null model. Default 100.

method

Null model method: "configuration" (preserves degree) or "gnm" (preserves edge count). Default "configuration".

directed

Logical. Treat as directed? Default auto-detected.

seed

Random seed for reproducibility

Value

A cograph_motifs object containing:

  • counts: Motif counts in observed network

  • null_mean: Mean counts in random networks

  • null_sd: Standard deviation in random networks

  • z_scores: Z-scores (observed - mean) / sd

  • p_values: Two-tailed p-values

  • significant: Logical vector (|z| > 2)

  • size: Motif size (3 or 4)

  • directed: Whether network is directed

  • n_random: Number of random networks used

See also

motifs() for the unified API, extract_motifs() for detailed triad extraction, plot.cograph_motifs() for plotting

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

Examples

# Create a directed network
mat <- matrix(c(
  0, 1, 1, 0,
  0, 0, 1, 1,
  0, 0, 0, 1,
  1, 0, 0, 0
), 4, 4, byrow = TRUE)

# Analyze triadic motifs
m <- motif_census(mat)
print(m)
#> Network Motif Analysis
#> Size: 3-node motifs (directed) | Null: configuration (n=100)
#> 
#>  motif count null_mean   null_sd    z_score     p_value significant
#>    003     0      0.00 0.0000000  0.0000000 1.000000000       FALSE
#>    012     0      0.00 0.0000000  0.0000000 1.000000000       FALSE
#>    102     0      0.19 0.3942772 -0.4818944 0.629880957       FALSE
#>   021D     0      0.00 0.0000000  0.0000000 1.000000000       FALSE
#>   021U     0      0.77 0.8628705 -0.8923703 0.372194475       FALSE
#>   021C     0      0.48 0.7847022 -0.6116970 0.540738243       FALSE
#>   111D     0      0.12 0.3265986 -0.3674235 0.713303174       FALSE
#>   111U     2      0.20 0.6030227  2.9849623 0.002836133        TRUE
#>   030T     0      0.06 0.2386833 -0.2513792 0.801520967       FALSE
#>   030C     0      0.44 0.7563869 -0.5817128 0.560760120       FALSE
#>    201     0      0.00 0.0000000  0.0000000 1.000000000       FALSE
#>   120D     2      0.23 0.6171783  2.8678907 0.004132182        TRUE
#>   120U     0      0.18 0.3861229 -0.4661728 0.641091822       FALSE
#>   120C     0      0.03 0.1714466 -0.1749816 0.861094100       FALSE
#>    210     0      0.00 0.0000000  0.0000000 1.000000000       FALSE
#>    300     0      0.00 0.0000000  0.0000000 1.000000000       FALSE
#> 
#> Over-represented: 2 | Under-represented: 0
plot(m)