pegas (version 1.3)

mst: Minimum Spanning Tree and Network

Description

Computes a minimum spanning tree using Kruskal's algorithm, the minimum spanning network using Bandelt et al.'s algorithm, or the randomized minimum spanning tree (Paradis 2018).

Usage

mst(d)
msn(d)
rmst(d, B = NULL, stop.criterion = NULL, iter.lim = 1000,
     quiet = FALSE)

Value

an object of class "haploNet".

Arguments

d

a distance matrix, either as an object of class "dist", or a (square symmetric) matrix.

B

number of randomizations.

stop.criterion

the stopping criterion if B is not given (see details).

iter.lim

the maximum number of iterations.

quiet

a logical value specifying whether to indicate progress of calculations.

Author

Emmanuel Paradis

Details

For the RMST, the calculations stop when no new links are found after a number of successive iterations specified by stop.criterion. By default, this number is ceiling(sqrt(n)) where n is the number of observations. This criterion is ignored if B is given, or if n < 6 in which case complete enumeration is done. In all cases, no more than iter.lim iterations are done.

References

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

Kruskal, J. B., Jr. (1956) On the shortest spanning subtree of a graph and the traveling salesman problem. Proceedings of the American Mathematical Society, 7, 48--50.

Paradis, E. (2018) Analysis of haplotype networks: the randomized minimum spanning tree method. Methods in Ecology and Evolution, 9, 1308--1317. DOI: 10.1111/2041-210X.12969.

See Also

haploNet, mjn

Examples

data(woodmouse)
d <- dist.dna(woodmouse, "n")
(r <- mst(d))
plot(r)

## a case where the RMST and the MJN are identical:
x <- c(">A", "TAAGTGCAT", ">B", "TAAATGCAT", ">C", "TAGGTGCAT", ">D", "TAAGTACAT",
       ">E", "TAAGTGTAT", ">F", "TAAGTACAC", ">G", "TAAGTACGT", ">H", "CAAGTACAC",
       ">I", "CAAGCACAC", ">J", "CAAGTACAT", ">K", "CGAGTACAT", ">L", "TAAGTACGC",
       ">M", "CAAGCACAT")
fl <- tempfile()
cat(x, file = fl, sep = "\n")
x <- read.dna(fl, "f")
tr <- rmst(dist.dna(x, "n"))
ts <- mjn(x)
stopifnot(all.equal(tr, ts))
unlink(fl)