pegas (version 1.3)

mjn: Median-Joining Network

Description

This function computes the median-joining network (MJN) as described by Bandelt et al. (1999).

Usage

mjn(x, epsilon = 0, max.n.cost = 10000, prefix = "median.vector_",
    quiet = FALSE)
# S3 method for mjn
plot(x, shape = c("circles", "diamonds"),
      bg = c("green", "slategrey"), labels = FALSE, ...)

Value

an object of class c("mjn", "haploNet") with an extra attribute (data) containing the original data together with the median vectors.

Arguments

x

a matrix (or data frame) of DNA sequences or binary 0/1 data; an object of class "mjn" for plot.

epsilon

tolerance parameter.

max.n.cost

the maximum number of costs to be computed.

prefix

the prefix used to label the median vectors.

quiet

a logical value; by default, the progress of the calculatins is printed.

shape, bg

the default shapes and colours for observed haplotypes and median vectors.

labels

by default, the labels of the haplotypes are printed.

...

other arguments passed to plot.haploNet.

Author

Emmanuel Paradis

Details

MJN is a network method where unobserved sequences (the median vectors) are reconstructed and included in the final network. Unlike mst, rmst, and msn, mjn works with the original sequences, the distances being calculated internally using a Hamming distance method (with dist(x, "manhattan") for binary data or dist.dna(x, "N") for DNA sequences).

The parameter epsilon controls how the search for new median vectors is performed: the larger this parameter, the wider the search (see the example with binary data).

If the sequences are very divergent, the search for new median vectors can take a very long time. The argument max.n.cost controls how many such vectors are added to the network (the default value should avoid the function to run endlessly).

The arguments shape and bg must be of length two (unlike in plot.haploNet). It is possible to have more flexibility when plotting the MJN by changing its class, for instance with the output in the examples below: class(nt0) <- "haplotNet".

References

Bandelt, H. J., Forster, P. and Rohl, A. (1999) Median-joining networks for inferring intraspecific phylogenies. Molecular Biology and Evolution, 16, 37--48.

See Also

haploNet, mst

Examples

## data in Table 1 of Bandelt et al. (1999):
x <- c(0, 0, 0, 0, 0, 0, 0, 0, 0,
       1, 1, 1, 1, 0, 0, 0, 0, 0,
       1, 0, 0, 0, 1, 1, 1, 0, 0,
       0, 1, 1, 1, 1, 1, 0, 1, 1)
x <- matrix(x, 4, 9, byrow = TRUE)
rownames(x) <- LETTERS[1:4]
(nt0 <- mjn(x))
(nt1 <- mjn(x, 1))
(nt2 <- mjn(x, 2))
plot(nt0)

if (FALSE) {
## same like in Fig. 4 of Bandelt et al. (1999):
plotNetMDS(nt2, dist(attr(nt2, "data"), "manhattan"), 3)
}

## data in Table 2 of Bandelt et al. (1999):
z <- list(c("g", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a", "a"),
          c("a", "g", "g", "a", "a", "a", "a", "a", "a", "a", "a", "a"),
          c("a", "a", "a", "g", "a", "a", "a", "a", "a", "a", "g", "g"),
          c("a", "a", "a", "a", "g", "g", "a", "a", "a", "a", "g", "g"),
          c("a", "a", "a", "a", "a", "a", "a", "a", "g", "g", "c", "c"),
          c("a", "a", "a", "a", "a", "a", "g", "g", "g", "g", "a", "a"))
names(z) <- c("A1", "A2", "B1", "B2", "C", "D")
z <- as.matrix(as.DNAbin(z))
(ntz <- mjn(z, 2))

if (FALSE) {
## same like in Fig. 5 of Bandelt et al. (1999):
plotNetMDS(ntz, dist.dna(attr(ntz, "data"), "N"), 3)
}