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Plot concordance table

Source: R/Concordance.R
ConcordanceTable.Rd

ConcordanceTable() plots a concordance table (Smith 2026) .

Usage

ConcordanceTable(
  tree,
  dataset,
  Col = QACol,
  largeClade = 0,
  xlab = "Edge",
  ylab = "Character",
  normalize = TRUE,
  plot = TRUE,
  marginSize = 0L,
  ...
)

Arguments

tree

A tree of class phylo.

dataset

A phylogenetic data matrix of phangorn class phyDat, whose names correspond to the labels of any accompanying tree. Perhaps load into R using ReadAsPhyDat(). Additive (ordered) characters can be handled using Decompose().

Col

Function that takes vectors amount and quality and returns a vector of colours. QCol colours by data quality (concordance); QACol by quality and amount of information.

largeClade

Integer; if greater than 1, vertical lines will be drawn at edges whose descendants are both contain more than largeClade leaves.

xlab

Character giving a label for the x axis.

ylab

Character giving a label for the y axis.

normalize

Controls how the expected mutual information (the zero point of the scale) is determined.

  • FALSE: no chance correction; MI is scaled only by its maximum.

  • TRUE: subtract the analytical expected MI for random association.

  • <integer>: subtract an empirical expected MI estimated from that number of random trees.

In all cases, 1 corresponds to the maximal attainable MI for the pair (hBest), and 0 corresponds to the chosen expectation.

plot

Logical specifying whether to draw the plot.

marginSize

Integer scalar or vector controlling summary margin strips. If a scalar (length 1) and greater than zero, both a left strip and a bottom strip are added, each marginSize grid cells wide/tall. If a vector (length > 1), each entry controls one side following the usual par(mar) order — c(bottom, left, top, right) — where a positive value enables that strip with the given width/height and NA or 0 suppresses it. Currently only the bottom (entry 1) and left (entry 2) strips are implemented; further entries are accepted but ignored. The left strip is coloured by the characterwise concordance (weighted mean across edges); the bottom strip by the edgewise concordance (weighted mean across characters). One blank cell separates each strip from the main grid.

...

Arguments to abline, to control the appearance of vertical lines marking important edges.

Value

ConcordanceTable() invisibly returns an named list containing:

  • "info": The amount of information in each character-edge pair, in bits;

  • "relInfo": The information, normalized to the most information-rich pair;

  • "quality": The normalized mutual information of the pair;

  • "col": The colours used to plot the table.

References

Smith MR (2026). “Which characters support which clades? Exploring the distribution of phylogenetic signal using mutual information.” Systematic Biology, Under review.

See also

Other split support functions: JackLabels(), Jackknife(), MaximizeParsimony(), MostContradictedFreq(), PresCont(), SiteConcordance

Examples

# Load data and tree
data("congreveLamsdellMatrices", package = "TreeSearch")
dataset <- congreveLamsdellMatrices[[1]][, 1:20]
tree <- referenceTree

# Plot tree and identify nodes
library("TreeTools", quietly = TRUE)
plot(tree)
nodeIndex <- as.integer(rownames(as.Splits(tree)))
nodelabels(seq_along(nodeIndex), nodeIndex, adj = c(2, 1),
           frame = "none", bg = NULL)
QALegend(where = c(0.1, 0.4, 0.1, 0.3))


# View information shared by characters and edges
ConcordanceTable(tree, dataset, largeClade = 3, col = 2, lwd = 3,
                 marginSize = 1:4)
axis(1)
axis(2)


# Visualize dataset
image(t(`mode<-`(PhyDatToMatrix(dataset), "numeric")), axes = FALSE,
      xlab = "Leaf", ylab = "Character")