bootstrap.pml {phangorn} | R Documentation |
Bootstrap
Description
bootstrap.pml
performs (non-parametric) bootstrap analysis and
bootstrap.phyDat
produces a list of bootstrapped data sets.
plotBS
plots a phylogenetic tree with the bootstrap values assigned
to the (internal) edges.
Usage
bootstrap.pml(x, bs = 100, trees = TRUE, multicore = FALSE,
mc.cores = NULL, tip.dates = NULL, ...)
bootstrap.phyDat(x, FUN, bs = 100, multicore = FALSE, mc.cores = NULL,
jumble = TRUE, ...)
Arguments
x |
an object of class |
bs |
number of bootstrap samples. |
trees |
return trees only (default) or whole |
multicore |
logical, whether models should estimated in parallel. |
mc.cores |
The number of cores to use during bootstrap. Only supported on UNIX-alike systems. |
tip.dates |
A named vector of sampling times associated to the tips/sequences. Leave empty if not estimating tip dated phylogenies. |
... |
further parameters used by |
FUN |
the function to estimate the trees. |
jumble |
logical, jumble the order of the sequences. |
Details
It is possible that the bootstrap is performed in parallel, with help of the multicore package. Unfortunately the multicore package does not work under windows or with GUI interfaces ("aqua" on a mac). However it will speed up nicely from the command line ("X11").
Value
bootstrap.pml
returns an object of class multi.phylo
or a list where each element is an object of class pml
. plotBS
returns silently a tree, i.e. an object of class phylo
with the
bootstrap values as node labels. The argument BStrees
is optional and
if not supplied the tree with labels supplied in the node.label
slot.
Author(s)
Klaus Schliep klaus.schliep@gmail.com
References
Felsenstein J. (1985) Confidence limits on phylogenies. An approach using the bootstrap. Evolution 39, 783–791
Lemoine, F., Entfellner, J. B. D., Wilkinson, E., Correia, D., Felipe, M. D., De Oliveira, T., & Gascuel, O. (2018). Renewing Felsenstein’s phylogenetic bootstrap in the era of big data. Nature, 556(7702), 452–456.
Penny D. and Hendy M.D. (1985) Testing methods evolutionary tree construction. Cladistics 1, 266–278
Penny D. and Hendy M.D. (1986) Estimating the reliability of evolutionary trees. Molecular Biology and Evolution 3, 403–417
See Also
optim.pml
, pml
,
plot.phylo
, maxCladeCred
nodelabels
,consensusNet
and
SOWH.test
for parametric bootstrap
Examples
## Not run:
data(Laurasiatherian)
dm <- dist.hamming(Laurasiatherian)
tree <- NJ(dm)
# NJ
set.seed(123)
NJtrees <- bootstrap.phyDat(Laurasiatherian,
FUN=function(x)NJ(dist.hamming(x)), bs=100)
treeNJ <- plotBS(tree, NJtrees, "phylogram")
# Maximum likelihood
fit <- pml(tree, Laurasiatherian)
fit <- optim.pml(fit, rearrangement="NNI")
set.seed(123)
bs <- bootstrap.pml(fit, bs=100, optNni=TRUE)
treeBS <- plotBS(fit$tree,bs)
# Maximum parsimony
treeMP <- pratchet(Laurasiatherian)
treeMP <- acctran(treeMP, Laurasiatherian)
set.seed(123)
BStrees <- bootstrap.phyDat(Laurasiatherian, pratchet, bs = 100)
treeMP <- plotBS(treeMP, BStrees, "phylogram")
add.scale.bar()
# export tree with bootstrap values as node labels
# write.tree(treeBS)
## End(Not run)