Phylogenetically Independent Contrasts
Compute the phylogenetically independent contrasts using the method described by Felsenstein (1985).
pic(x, phy, scaled = TRUE, var.contrasts = FALSE, rescaled.tree = FALSE)
- a numeric vector.
- an object of class
- logical, indicates whether the contrasts should be
scaled with their expected variances (default to
- logical, indicates whether the expected
variances of the contrasts should be returned (default to
- logical, if
TRUEthe rescaled tree is returned together with the main results.
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
The user must be careful here since the function requires that both
series of names perfectly match. 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.
- 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.
rescaled.tree = TRUE, a list is returned with two elements named ``contr'' with the above results and ``rescaled.tree'' with the tree and its rescaled branch lengths (see Felsenstein 1985).
Felsenstein, J. (1985) Phylogenies and the comparative method. American Naturalist, 125, 1--15.
### 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"