5 \alias{print.prop.part}
6 \alias{summary.prop.part}
8 \title{Tree Bipartition and Bootstrapping Phylogenies}
10 boot.phylo(phy, x, FUN, B = 100, block = 1, trees = FALSE)
11 prop.part(..., check.labels = TRUE)
12 prop.clades(phy, ..., part = NULL)
13 \method{print}{prop.part}(x, ...)
14 \method{summary}{prop.part}(object, ...)
15 \method{plot}{prop.part}(x, barcol = "blue", leftmar = 4, ...)
18 \item{phy}{an object of class \code{"phylo"}.}
19 \item{x}{in the case of \code{boot.phylo}: a taxa (rows) by characters
20 (columns) matrix; this may be presented as a list; in the case of
21 \code{print} and \code{plot}: an object of class \code{"prop.part"}.}
22 \item{FUN}{the function used to estimate \code{phy} (see details).}
23 \item{B}{the number of bootstrap replicates.}
24 \item{block}{the number of columns in \code{x} that will be resampled
25 together (see details).}
26 \item{trees}{a logical specifying whether to return the bootstraped
27 trees (\code{FALSE} by default).}
28 \item{\dots}{either (i) a single object of class \code{"phylo"}, (ii) a
29 series of such objects separated by commas, or (iii) a list
30 containing such objects. In the case of \code{plot} further
31 arguments for the plot (see details).}
32 \item{check.labels}{a logical specifying whether to check the labels
33 of each tree. If \code{FALSE}, it is assumed that all trees have the
34 same tip labels, and that they are in the same order (see details).}
35 \item{part}{a list of partitions as returned by \code{prop.part}; if
36 this is used then \code{\dots} is ignored.}
37 \item{object}{an object of class \code{"prop.part"}.}
38 \item{barcol}{the colour used for the bars displaying the number of
39 partitions in the upper panel.}
40 \item{leftmar}{the size of the margin on the left to display the tip
44 These functions analyse bipartitions found in a series of trees.
46 \code{prop.part} counts the number of bipartitions found in a series
47 of trees given as \code{\dots}.
49 \code{prop.clades} counts the number of times the bipartitions present
50 in \code{phy} are present in a series of trees given as \code{\dots} or
51 in the list previously computed and given with \code{part}.
53 \code{boot.phylo} performs a bootstrap analysis.
56 The argument \code{FUN} in \code{boot.phylo} must be the function used
57 to estimate the tree from the original data matrix. Thus, if the tree
58 was estimated with neighbor-joining (see \code{nj}), one maybe wants
59 something like \code{FUN = function(xx) nj(dist.dna(xx))}.
61 \code{block} in \code{boot.phylo} specifies the number of columns to
62 be resampled altogether. For instance, if one wants to resample at the
63 codon-level, then \code{block = 3} must be used.
65 Using \code{check.labels = FALSE} in \code{prop.part} decreases
66 computing times. This requires that (i) all trees have the same tip
67 labels, \emph{and} (ii) these labels are ordered similarly in all
68 trees (in other words, the element \code{tip.label} are identical in
71 The plot function represents a contingency table of the different
72 partitions (on the \emph{x}-axis) in the lower panel, and their observed
73 numbers in the upper panel. Any further arguments (\dots) are used to
74 change the aspects of the points in the lower panel: these may be
75 \code{pch}, \code{col}, \code{bg}, \code{cex}, etc. This function
76 works only if there is an attribute \code{labels} in the object.
78 The print method displays the partitions and their numbers. The
79 summary method extracts the numbers only.
82 \code{prop.clades} calls internally \code{prop.part} with the option
83 \code{check.labels = TRUE}, which may be very slow. If the trees
84 passed as \code{\dots} fulfills conditions (i) and (ii) above, then it
85 might be faster to first call, e.g., \code{pp <- prop.part(...)}, then
86 use the option \code{part}: \code{prop.clades(phy, part = pp)}.
89 \code{prop.part} returns an object of class \code{"prop.part"} which
90 is a list with an attribute \code{"number"}. The elements of this list
91 are the observed clades, and the attribute their respective
92 numbers. If the default \code{check.labels = FALSE} is used, an
93 attribute \code{"labels"} is added, and the vectors of the returned
94 object contains the indices of these labels instead of the labels
97 \code{prop.clades} and \code{boot.phylo} return a numeric vector
98 which \emph{i}th element is the number associated to the \emph{i}th
99 node of \code{phy}. If \code{trees = TRUE}, \code{boot.phylo} returns
100 a list whose first element (named \code{"BP"}) is like before, and the
101 second element (\code{"trees"}) is a list with the bootstraped
104 \code{summary} returns a numeric vector.
107 Efron, B., Halloran, E. and Holmes, S. (1996) Bootstrap confidence
108 levels for phylogenetic trees. \emph{Proceedings of the National
109 Academy of Sciences USA}, \bold{93}, 13429--13434.
111 Felsenstein, J. (1985) Confidence limits on phylogenies: an approach
112 using the bootstrap. \emph{Evolution}, \bold{39}, 783--791.
114 \author{Emmanuel Paradis \email{Emmanuel.Paradis@mpl.ird.fr}}
116 \code{\link{dist.topo}}, \code{\link{consensus}}, \code{\link{nodelabels}}
120 tr <- nj(dist.dna(woodmouse))
121 ### Are bootstrap values stable?
123 print(boot.phylo(tr, woodmouse, function(xx) nj(dist.dna(xx))))
124 ### How many partitions in 100 random trees of 10 labels?...
125 TR <- replicate(100, rtree(10), FALSE)
126 pp10 <- prop.part(TR)
128 ### ... and in 100 random trees of 20 labels?
129 TR <- replicate(100, rtree(20), FALSE)
130 pp20 <- prop.part(TR)
132 plot(pp10, pch = "x", col = 2)
133 plot(pp20, pch = "x", col = 2)