MPR: Most Parsimonious Reconstruction

In ape: Analyses of Phylogenetics and Evolution

Most Parsimonious Reconstruction

Description

This function does ancestral character reconstruction by parsimony as described in Hanazawa et al. (1995) and modified by Narushima and Hanazawa (1997).

Usage

MPR(x, phy, outgroup)

Arguments

x	a vector of integers.
phy	an object of class "phylo"; the tree must be unrooted and fully dichotomous.
outgroup	an integer or a character string giving the tip of phy used as outgroup.

Details

Hanazawa et al. (1995) and Narushima and Hanazawa (1997) used Farris's (1970) and Swofford and Maddison's (1987) framework to reconstruct ancestral states using parsimony. The character is assumed to take integer values. The algorithm finds the sets of values for each node as intervals with lower and upper values.

It is recommended to root the tree with the outgroup before the analysis, so plotting the values with nodelabels is simple.

Value

a matrix of integers with two columns named “lower” and “upper” giving the lower and upper values of the reconstructed sets for each node.

Author(s)

Emmanuel Paradis

References

Farris, J. M. (1970) Methods for computing Wagner trees. Systematic Zoology, 19, 83–92.

Hanazawa, M., Narushima, H. and Minaka, N. (1995) Generating most parsimonious reconstructions on a tree: a generalization of the Farris–Swofford–Maddison method. Discrete Applied Mathematics, 56, 245–265.

Narushima, H. and Hanazawa, M. (1997) A more efficient algorithm for MPR problems in phylogeny. Discrete Applied Mathematics, 80, 231–238.

Swofford, D. L. and Maddison, W. P. (1987) Reconstructing ancestral character states under Wagner parsimony. Mathematical Biosciences, 87, 199–229.

See Also

ace, root, nodelabels

Examples

## the example in Narushima and Hanazawa (1997):
tr <- read.tree(text = "(((i,j)c,(k,l)b)a,(h,g)e,f)d;")
x <- c(1, 3, 0, 6, 5, 2, 4)
names(x) <- letters[6:12]
(o <- MPR(x, tr, "f"))
plot(tr)
nodelabels(paste0("[", o[, 1], ",", o[, 2], "]"))
tiplabels(x[tr$tip.label], adj = -2)
## some random data:
x <- rpois(30, 1)
tr <- rtree(30, rooted = FALSE)
MPR(x, tr, "t1")

ape documentation built on May 29, 2024, 10:50 a.m.