pic: Phylogenetically Independent Contrasts

Description

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

Usage

pic(x, phy, scaled = TRUE, var.contrasts = FALSE)

Arguments

a numeric vector.

phy

an object of class "phylo".

scaled

logical, indicates whether the contrasts should be scaled with their expected variance (default to TRUE).

var.contrasts

logical, indicates whether the expected variance of the contrasts should be returned (default to FALSE).

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).

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.

References

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

Examples

Run this code

### 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"

Run the code above in your browser using DataLab

Last chance! 50% off unlimited learning