Plot a chord diagram of modification co-occurrence.

Display a circlize chord diagram showing significant pairwise modification co-occurrence (odds ratios) for a single sample. Chords are colored by direction: positive odds ratios (co-occurring modifications) vs. negative (mutually exclusive). Chord width reflects the magnitude of the log odds ratio.

Usage

plot_chord_or(
  odds_data,
  or_col = "log_odds_ratio",
  or_cutoff = 1,
  p_col = "p_value",
  p_cutoff = 0.01,
  min_obs = 100,
  positive_color = "#D55E00",
  negative_color = "#0072B2",
  sprinzl_coords = NULL,
  mods = NULL,
  title = NULL,
  transparency = 0.4
)

Arguments

odds_data: A tibble of odds ratio data with columns pos1, pos2, log_odds_ratio (or column specified by or_col), p_value (or column specified by p_col), and total_obs.
or_col: Column name (string) for the odds ratio value. Default "log_odds_ratio".
or_cutoff: Minimum absolute value of or_col for a chord to be drawn. Default 1.0.
p_col: Column name (string) for the p-value. Default "p_value".
p_cutoff: Maximum p-value for a chord to be drawn. Default 0.01.
min_obs: Minimum number of observations (total_obs) for a pair to be included. Default 100.
positive_color: Color for positive odds ratios (co-occurrence). Default "#D55E00" (vermillion).
negative_color: Color for negative odds ratios (exclusion). Default "#0072B2" (blue).
sprinzl_coords: An optional tibble from read_sprinzl_coords() used to order sectors by Sprinzl position and color by structural region.
mods: An optional tibble of modification annotations (e.g., from fetch_modomics_mods()) with columns pos and mod1. When provided along with sprinzl_coords, modification positions are highlighted as an annotation ring.
title: Optional plot title.
transparency: Transparency for chord colors (0 = opaque, 1 = fully transparent). Default 0.4.

Value

invisible(NULL). Called for its side effect of producing a base graphics plot.

Examples

# \donttest{
path <- clover_example(
  "ecoli/summary/tables/wt-15-ctl-01/wt-15-ctl-01.odds_ratios.tsv.gz"
)
or_data <- read_odds_ratios(path)
or_data <- dplyr::filter(or_data, ref == "host-tRNA-Glu-TTC-1-1")
plot_chord_or(or_data)

# }