https://github.com/cran/ape
Tip revision: 015cfe4351eae636bc568b44393cc53e4e91f46c authored by Emmanuel Paradis on 28 May 2015, 00:00:00 UTC
version 3.3
version 3.3
Tip revision: 015cfe4
boot.phylo.Rd
\name{boot.phylo}
\alias{boot.phylo}
\alias{prop.part}
\alias{prop.clades}
\alias{print.prop.part}
\alias{summary.prop.part}
\alias{plot.prop.part}
\title{Tree Bipartition and Bootstrapping Phylogenies}
\description{
These functions analyse bipartitions found in a series of trees.
\code{prop.part} counts the number of bipartitions found in a series
of trees given as \code{\dots}. If a single tree is passed, the
returned object is a list of vectors with the tips descending from
each node (i.e., clade compositions indexed by node number).
\code{prop.clades} counts the number of times the bipartitions present
in \code{phy} are present in a series of trees given as \code{\dots} or
in the list previously computed and given with \code{part}.
\code{boot.phylo} performs a bootstrap analysis.
}
\usage{
boot.phylo(phy, x, FUN, B = 100, block = 1,
trees = FALSE, quiet = FALSE, rooted = FALSE)
prop.part(..., check.labels = TRUE)
prop.clades(phy, ..., part = NULL, rooted = FALSE)
\method{print}{prop.part}(x, ...)
\method{summary}{prop.part}(object, ...)
\method{plot}{prop.part}(x, barcol = "blue", leftmar = 4, col = "red", ...)
}
\arguments{
\item{phy}{an object of class \code{"phylo"}.}
\item{x}{in the case of \code{boot.phylo}: a taxa (rows) by characters
(columns) matrix; in the case of \code{print} and \code{plot}: an
object of class \code{"prop.part"}.}
\item{FUN}{the function used to estimate \code{phy} (see details).}
\item{B}{the number of bootstrap replicates.}
\item{block}{the number of columns in \code{x} that will be resampled
together (see details).}
\item{trees}{a logical specifying whether to return the bootstraped
trees (\code{FALSE} by default).}
\item{quiet}{a logical: a progress bar is displayed by default.}
\item{rooted}{a logical specifying whether the trees should be treated
as rooted or not (the default).}
\item{\dots}{either (i) a single object of class \code{"phylo"}, (ii) a
series of such objects separated by commas, or (iii) a list
containing such objects. In the case of \code{plot} further
arguments for the plot (see details).}
\item{check.labels}{a logical specifying whether to check the labels
of each tree. If \code{FALSE}, it is assumed that all trees have the
same tip labels, and that they are in the same order (see details).}
\item{part}{a list of partitions as returned by \code{prop.part}; if
this is used then \code{\dots} is ignored.}
\item{object}{an object of class \code{"prop.part"}.}
\item{barcol}{the colour used for the bars displaying the number of
partitions in the upper panel.}
\item{leftmar}{the size of the margin on the left to display the tip
labels.}
\item{col}{the colour used to visualise the bipartitions.}
}
\details{
The argument \code{FUN} in \code{boot.phylo} must be the function used
to estimate the tree from the original data matrix. Thus, if the tree
was estimated with neighbor-joining (see \code{nj}), one maybe wants
something like \code{FUN = function(xx) nj(dist.dna(xx))}.
\code{block} in \code{boot.phylo} specifies the number of columns to
be resampled altogether. For instance, if one wants to resample at the
codon-level, then \code{block = 3} must be used.
Using \code{check.labels = FALSE} in \code{prop.part} decreases
computing times. This requires that (i) all trees have the same tip
labels, \emph{and} (ii) these labels are ordered similarly in all
trees (in other words, the element \code{tip.label} are identical in
all trees).
The plot function represents a contingency table of the different
partitions (on the \emph{x}-axis) in the lower panel, and their observed
numbers in the upper panel. Any further arguments (\dots) are used to
change the aspects of the points in the lower panel: these may be
\code{pch}, \code{col}, \code{bg}, \code{cex}, etc. This function
works only if there is an attribute \code{labels} in the object.
The print method displays the partitions and their numbers. The
summary method extracts the numbers only.
}
\note{
\code{prop.clades} calls internally \code{prop.part} with the option
\code{check.labels = TRUE}, which may be very slow. If the trees
passed as \code{\dots} fulfills conditions (i) and (ii) above, then it
might be faster to first call, e.g., \code{pp <- prop.part(...)}, then
use the option \code{part}: \code{prop.clades(phy, part = pp)}.
You have to be careful that by default \code{prop.clades} considers
the trees as unrooted and this may result in spurious results if the
trees are rooted (see examples).
}
\value{
\code{prop.part} returns an object of class \code{"prop.part"} which
is a list with an attribute \code{"number"}. The elements of this list
are the observed clades, and the attribute their respective
numbers. If the default \code{check.labels = FALSE} is used, an
attribute \code{"labels"} is added, and the vectors of the returned
object contains the indices of these labels instead of the labels
themselves.
\code{prop.clades} and \code{boot.phylo} return a numeric vector
which \emph{i}th element is the number associated to the \emph{i}th
node of \code{phy}. If \code{trees = TRUE}, \code{boot.phylo} returns
a list whose first element (named \code{"BP"}) is like before, and the
second element (\code{"trees"}) is a list with the bootstraped
trees.
\code{summary} returns a numeric vector.
}
\references{
Efron, B., Halloran, E. and Holmes, S. (1996) Bootstrap confidence
levels for phylogenetic trees. \emph{Proceedings of the National
Academy of Sciences USA}, \bold{93}, 13429--13434.
Felsenstein, J. (1985) Confidence limits on phylogenies: an approach
using the bootstrap. \emph{Evolution}, \bold{39}, 783--791.
}
\author{Emmanuel Paradis}
\seealso{
\code{\link{as.bitsplits}}, \code{\link{dist.topo}},
\code{\link{consensus}}, \code{\link{nodelabels}}
}
\examples{
data(woodmouse)
f <- function(x) nj(dist.dna(x))
tr <- f(woodmouse)
### Are bootstrap values stable?
for (i in 1:5)
print(boot.phylo(tr, woodmouse, f, quiet = TRUE))
### How many partitions in 100 random trees of 10 labels?...
TR <- rmtree(100, 10)
pp10 <- prop.part(TR)
length(pp10)
### ... and in 100 random trees of 20 labels?
TR <- rmtree(100, 20)
pp20 <- prop.part(TR)
length(pp20)
plot(pp10, pch = "x", col = 2)
plot(pp20, pch = "x", col = 2)
set.seed(1)
tr <- rtree(10) # rooted by default
prop.clades(tr, tr) # clearly wrong
prop.clades(tr, tr, rooted = TRUE)
tr <- rtree(10, rooted = FALSE)
prop.clades(tr, tr) # correct
}
\keyword{manip}
\keyword{htest}