TipVolatility {Rogue}

Detect rogue taxa using phylogenetic information distance

Description

Calculate the volatility of each tip: namely, the impact on the mean phylogenetic information distance (Smith 2020) between trees when that tip is removed. Effective when the number of trees is small.

Usage

TipVolatility(trees)

Arguments

trees

List of trees to analyse.

Value

TipVolatility() returns a named vector listing the volatility index calculated for each leaf.

References

Smith MR (2020). “Information theoretic Generalized Robinson–Foulds metrics for comparing phylogenetic trees.” Bioinformatics, 36(20), 5007–5013. doi:10.1093/bioinformatics/btaa614.

See Also

Other tip instability functions: TipInstability()

Examples

library("TreeTools", quietly = TRUE)

# Generate some trees with two rogue taxa
trees <- AddTipEverywhere(BalancedTree(8), "Rogue")
trees[] <- lapply(trees, AddTip, "Rogue", "Rogue2")

# Calculate tip volatility
sb <- TipVolatility(trees)

# Use volatility to colour leaves in consensus tree
sbNorm <- 1 + (99 * (sb - min(sb)) / (max(sb - min(sb))))
col <- hcl.colors(128, "inferno")[sbNorm]
plot(consensus(trees), tip.color = col)

# Add a legend for the colour scale used
PlotTools::SpectrumLegend(
  "bottomleft", bty = "n", # Suppress box
  inset = -0.02,           # Avoid overlap
  title = "Volatility",
  legend = signif(seq(max(sb), min(sb), length.out = 4), 3),
  palette = hcl.colors(128, "inferno")
)

# Plot consensus after removing highly volatile taxa
plot(ConsensusWithout(trees, names(sb[sb == max(sb)])))