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Visualize multi-way chromatin contacts as hypergraph network

Source: R/AllGenerics.R, R/gghypergraph-methods.R
gghypergraph.Rd

Creates an intuitive ggplot2 visualization of multi-way chromatin contacts from Pore-C or similar long-read technologies. Displays genomic bins as points and multi-way contacts as connecting lines (hyperedges), with line width and color encoding contact properties.

Usage

gghypergraph(x, ...)

# S4 method for class 'MultiWayContacts'
gghypergraph(
  x,
  point_size = 2,
  line_width = 0.3,
  line_alpha = 0.6,
  color_by = "n_multiways",
  palette = "viridis",
  facet_chrom = TRUE,
  weight_normalization = "none"
)

Arguments

x

MultiWayContacts object with selected hyperedges (after running select()).

...

Additional arguments (not used).

point_size

Numeric. Size of genomic bin points (default: 2).

line_width

Numeric. Base line width for hyperedges. Actual width scaled by hyperedge weight (default: 0.3).

line_alpha

Numeric between 0 and 1. Line transparency to reduce overplotting (default: 0.6).

color_by

Character. Variable for line coloring:

  • "n_multiways": Color by contact order (2-way, 3-way, etc.) (default)

  • Other values: Uniform gray coloring

palette

Character. Color palette name:

  • Viridis options: "viridis", "magma", "plasma", "inferno", "cividis"

  • ColorBrewer palettes: "YlOrRd", "Blues", etc.

  • Default: "viridis"

facet_chrom

Logical. Layout strategy:

  • TRUE: Separate facet panel per chromosome (default)

  • FALSE: Composite y-axis with all chromosomes stacked

weight_normalization

Character. Deprecated parameter (weights now set in tidy() method).

Value

A ggplot2 object that can be further customized with additional ggplot2 layers and themes.

Details

Visualization structure

  • X-axis: Hyperedge index (each read/contact)

  • Y-axis: Genomic bin position (genomic coordinate)

  • Points: Individual genomic bins

  • Lines: Connect all bins in a single multi-way contact

  • Line width: Scaled by hyperedge weight

  • Line color: Contact order (number of fragments per read)

Interpretation

  • Vertical lines: Bins contacted by same read

  • Line thickness: Relative importance/weight

  • Color gradient: Contact complexity (darker = higher-order)

  • Patterns reveal genome organization and contact preferences

Prerequisites

Must run complete workflow: import() → build() → tidy() → select() before visualization.

See also

MultiWayContacts(), select(), tidy(), build()

Examples

if (FALSE) { # \dontrun{
# Complete workflow
mc <- MultiWayContacts("sample.pairs.gz", focus = "chr1") |>
  import() |>
  build(bin_size = 1000000L, quantile = 0.85) |>
  tidy(weight_normalization = "log") |>
  select(n_intra = 10, n_inter = 5)

# Basic visualization
gghypergraph(mc)

# Composite layout with custom colors
gghypergraph(mc, facet_chrom = FALSE, palette = "magma")

# Emphasize line patterns
gghypergraph(mc, line_width = 0.5, line_alpha = 0.8, point_size = 3)

# Further customization
gghypergraph(mc) +
  theme_minimal() +
  labs(title = "Multi-way Contacts on Chromosome 1")
} # }