phangorn (version 1.99-1)

dist.hamming: Pairwise Distances from Sequences

Description

dist.hamming and dist.logDet compute pairwise distances for an object of class phyDat. dist.ml fits distances for nucleotide and amino acid models.

Usage

dist.hamming(x, ratio = TRUE, exclude="none")
dist.logDet(x)
dist.ml(x, model="JC69", exclude="none", bf=NULL, Q=NULL, ...)

Arguments

x

An object of class phyDat

ratio

Compute uncorrected ('p') distance or character difference.

model

One of "JC69" or one of 17 amino acid models see details.

exclude

One of "none", "all", "pairwise" indicating whether to delete the sites with missing data (or ambigious states). The default is handle missing data as in pml.

bf

A vector of base frequencies.

Q

A vector containing the lower triangular part of the rate matrix.

...

Further arguments passed to or from other methods.

Value

• an object of class dist

Details

So far 17 amino acid models are supported ("WAG", "JTT", "LG", "Dayhoff", "cpREV", "mtmam", "mtArt", "MtZoa", "mtREV24", "VT","RtREV", "HIVw", "HIVb", "FLU", "Blossum62", "Dayhoff_DCMut" and "JTT_DCMut") and additional rate matrices and frequences can be supplied.

References

Lockhart, P. J., Steel, M. A., Hendy, M. D. and Penny, D. (1994) Recovering evolutionary trees under a more realistic model of sequence evolution. Molecular Biology and Evolution, 11, 605--602.

See Also

For more distance methods for nucleotide data see dist.dna

Examples

data(Laurasiatherian)
dm1 <- dist.hamming(Laurasiatherian)
tree1 <- NJ(dm1)
dm2 <- dist.logDet(Laurasiatherian)
tree2 <- NJ(dm2)
treedist(tree1,tree2)