pic

0th

Percentile

Phylogenetically Independent Contrasts

Compute the phylogenetically independent contrasts using the method described by Felsenstein (1985).

Keywords
regression
Usage
pic(x, phy, scaled = TRUE, var.contrasts = FALSE)
Arguments
x
a numeric vector.
phy
an object of class "phylo".
scaled
logical, indicates whether the contrasts should be scaled with their expected variances (default to TRUE).
var.contrasts
logical, indicates whether the expected variances of the contrasts should be returned (default to FALSE).
Details

If x has names, its values are matched to the tip labels of phy, otherwise its values are taken to be in the same order than the tip labels of phy.

The user must be careful here since the function requires that both series of names perfectly match, so this operation may fail if there is a typing or syntax error. If both series of names do not match, the values in the x are taken to be in the same order than the tip labels of phy, and a warning message is issued.

Value

  • either a vector of phylogenetically independent contrasts (if var.contrasts = FALSE), or a two-column matrix with the phylogenetically independent contrasts in the first column and their expected variance in the second column (if var.contrasts = TRUE). If the tree has node labels, these are used as labels of the returned object.

References

Felsenstein, J. (1985) Phylogenies and the comparative method. American Naturalist, 125, 1--15.

See Also

read.tree, compar.gee, compar.lynch, pic.ortho, varCompPhylip

Aliases
  • pic
Examples
### The example in Phylip 3.5c (originally from Lynch 1991)
cat("((((Homo:0.21,Pongo:0.21):0.28,",
   "Macaca:0.49):0.13,Ateles:0.62):0.38,Galago:1.00);",
   file = "ex.tre", sep = "")
tree.primates <- read.tree("ex.tre")
X <- c(4.09434, 3.61092, 2.37024, 2.02815, -1.46968)
Y <- c(4.74493, 3.33220, 3.36730, 2.89037, 2.30259)
names(X) <- names(Y) <- c("Homo", "Pongo", "Macaca", "Ateles", "Galago")
pic.X <- pic(X, tree.primates)
pic.Y <- pic(Y, tree.primates)
cor.test(pic.X, pic.Y)
lm(pic.Y ~ pic.X - 1) # both regressions
lm(pic.X ~ pic.Y - 1) # through the origin
unlink("ex.tre") # delete the file "ex.tre"
Documentation reproduced from package ape, version 2.7-3, License: GPL (>= 2)

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