phangorn (version 2.1.1)

ancestral.pml: Ancestral character reconstruction.

Description

Marginal reconstruction of the ancestral character states.

Usage

ancestral.pml(object, type = c("marginal", "ml", "bayes"))
ancestral.pars(tree, data, type = c("MPR", "ACCTRAN"), cost = NULL)
pace(tree, data, type = c("MPR", "ACCTRAN"), cost = NULL)
plotAnc(tree, data, i, col=NULL, cex.pie=par("cex"), pos="bottomright", ...)

Arguments

object

an object of class pml

tree

a tree, i.e. an object of class pml

data

an object of class phyDat

type

method used to assign characters to internal nodes, see details.

i

plots the i-th character of the data.

col

a vector containing the colors for all possible states.

cex.pie

a numeric defining the size of the pie graphs

pos

a character string defining the position of the legend

cost

A cost matrix for the transitions between two states.

...

Further arguments passed to or from other methods.

Value

An object of class "phyDat", containing the ancestral states of all nodes.

Details

The argument "type" defines the criterion to assign the internal nodes. For ancestral.pml so far "ml" and (empirical) "bayes" and for ancestral.pars "MPR" and "ACCTRAN" are possible.

With parsimony reconstruction one has to keep in mind that there will be often no unique solution.

For further details see vignette("Ancestral").

References

Felsenstein, J. (2004). Inferring Phylogenies. Sinauer Associates, Sunderland.

Swofford, D.L., Maddison, W.P. (1987) Reconstructing ancestral character states under Wagner parsimony. Math. Biosci. 87: 199--229

Yang, Z. (2006). Computational Molecular evolution. Oxford University Press, Oxford.

See Also

pml, parsimony, ace, root

Examples

example(NJ)
fit = pml(tree, Laurasiatherian)
anc.ml = ancestral.pml(fit, type = "ml")
anc.p = ancestral.pars(tree, Laurasiatherian)
## Not run: 
# require(seqLogo)
# seqLogo( t(subset(anc.ml, 48, 1:20)[[1]]), ic.scale=FALSE)
# seqLogo( t(subset(anc.p, 48, 1:20)[[1]]), ic.scale=FALSE)
# ## End(Not run)
plotAnc(tree, anc.ml, 1)