dist.hamming

0th

Percentile

Pairwise Distances from Sequences

dist.hamming, dist.ml and dist.logDet compute pairwise distances for an object of class phyDat. dist.ml uses DNA / AA sequences to compute distances under different substitution models.

Keywords
cluster
Usage
dist.hamming(x, ratio = TRUE, exclude = "none")

dist.ml(x, model = "JC69", exclude = "none", bf = NULL, Q = NULL, k = 1L, shape = 1, ...)

dist.logDet(x)

Arguments
x

An object of class phyDat

ratio

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

exclude

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

model

One of "JC69", "F81" or one of 17 amino acid models see details.

bf

A vector of base frequencies.

Q

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

k

Number of intervals of the discrete gamma distribution.

shape

Shape parameter of the gamma distribution.

Further arguments passed to or from other methods.

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 frequencies can be supplied.

The "F81" model uses empirical base frequencies, the "JC69" equal base frequencies. This is even the case if the data are not nucleotides.

Value

an object of class dist

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.

Jukes TH and Cantor CR (1969). Evolution of Protein Molecules. New York: Academic Press. 21--132.

See Also

For more distance methods for nucleotide data see dist.dna and dist.p for pairwise polymorphism p-distances. writeDist for export and import distances.

Aliases
  • dist.hamming
  • dist.ml
  • dist.logDet
Examples
# NOT RUN {
data(Laurasiatherian)
dm1 <- dist.hamming(Laurasiatherian)
tree1 <- NJ(dm1)
dm2 <- dist.logDet(Laurasiatherian)
tree2 <- NJ(dm2)
treedist(tree1,tree2)
# JC model
dm3 <- dist.ml(Laurasiatherian)
tree3 <- NJ(dm3)
treedist(tree1,tree3)
# F81 + Gamma
dm4 <- dist.ml(Laurasiatherian, model="F81", k=4, shape=.4)
tree4 <- NJ(dm4)
treedist(tree1,tree4)
treedist(tree3,tree4)

# }
Documentation reproduced from package phangorn, version 2.5.5, License: GPL (>= 2)

Community examples

Looks like there are no examples yet.