phangorn (version 1.5-0)

hadamard: Hadamard Matrices and Fast Hadamard Multiplication

Description

A collection of functions to perform Hadamard conjugation.

Usage

hadamard(x)
fhm(v)
h2st(obj, eps=0.001)
h4st(obj, levels = c("a","c","g","t"))
write.nexus.splits(obj, file="", weights=NULL)

Arguments

x

a vector of length $2^n$, where n is an integer.

v

a vector of length $2^n$, where n is an integer.

obj

a data.frame or character matrix, typical a sequence alignment.

eps

Threshold value for splits.

levels

levels of the sequences.

file

a file name.

weights

Edge weights.

Value

• hadamard returns a Hadamard matrix. fhm returns the fast Hadamard multiplication.

Details

h2st and h4st perform Hadamard conjugation for 2-state (binary, RY-coded) or 4-state (DNA/RNA) data. write.nexus.splits writes splits returned from h2st or distanceHadamard to a nexus file, which can be processed by Spectronet or Splitstree.

References

Hendy, M.D. (1989). The relationship between simple evolutionary tree models and observable sequence data. Systematic Zoology, 38 310--321. Hendy, M. D. and Penny, D. (1993). Spectral Analysis of Phylogenetic Data. Journal of Classification, 10, 5--24. Hendy, M. D. (2005). Hadamard conjugation: an analytical tool for phylogenetics. In O. Gascuel, editor, Mathematics of evolution and phylogeny, Oxford University Press, Oxford Waddell P. J. (1995). Statistical methods of phylogenetic analysis: Including hadamard conjugation, LogDet transforms, and maximum likelihood. PhD thesis.

See Also

distanceHadamard, lento, plot.networx

Examples

H = hadamard(3)
v = 1:8
Hfhm(v)

data(yeast)
dat = as.character(yeast)
# RY-coding
dat2 = dat
dat2[dat=="a" | dat=="g"] = "r"
dat2[dat=="c" | dat=="t"] = "y"
dat2 = phyDat(dat2, type="USER", levels=c("r","y"), ambiguity=NULL)
fit2 = h2st(dat2)
lento(fit2)

# write.nexus.splits(fit2, file = "test.nxs")
# read this file into Spectronet or Splitstree to show the network
dat4 = phyDat(dat, type="USER", levels=c("a","c", "g", "t"), ambiguity=NULL)
fit4 = h4st(dat4)

par(mfrow=c(3,1))
lento(fit4[[1]], main="Transversion")
lento(fit4[[2]], main="Transition 1")
lento(fit4[[3]], main="Transition 2")