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Pairwise Distances from Sequences

Source: R/distSeq.R
dist.hamming.Rd

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.

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.

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", "Blosum62", "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.

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.

McGuire, G., Prentice, M. J. and Wright, F. (1999). Improved error bounds for genetic distances from DNA sequences. Biometrics, 55, 1064–1070.

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.

Author

Klaus Schliep klaus.schliep@gmail.com

Examples


data(Laurasiatherian)
dm1 <- dist.hamming(Laurasiatherian)
tree1 <- NJ(dm1)
dm2 <- dist.logDet(Laurasiatherian)
tree2 <- NJ(dm2)
treedist(tree1,tree2)
#>      symmetric.difference   branch.score.difference           path.difference 
#>                4.00000000                0.05705091               30.95157508 
#> quadratic.path.difference 
#>                0.80097967 
# JC model
dm3 <- dist.ml(Laurasiatherian)
tree3 <- NJ(dm3)
treedist(tree1,tree3)
#>      symmetric.difference   branch.score.difference           path.difference 
#>                 6.0000000                 0.0412520                30.3644529 
#> quadratic.path.difference 
#>                 0.6106899 
# F81 + Gamma
dm4 <- dist.ml(Laurasiatherian, model="F81", k=4, shape=.4)
tree4 <- NJ(dm4)
treedist(tree1,tree4)
#>      symmetric.difference   branch.score.difference           path.difference 
#>                12.0000000                 0.1356107                40.7676342 
#> quadratic.path.difference 
#>                 2.0709714 
treedist(tree3,tree4)
#>      symmetric.difference   branch.score.difference           path.difference 
#>                8.00000000                0.09494752               39.52214569 
#> quadratic.path.difference 
#>                1.46345381