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bootstrap.pml

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, ...)

bootstrap.phyDat(x, FUN, bs = 100, multicore = FALSE, mc.cores = NULL,
  jumble = TRUE, ...)

Arguments

x

an object of class pml or phyDat.

bs

number of bootstrap samples.

trees

return trees only (default) or whole pml objects.

multicore

logical, whether models should estimated in parallel.

mc.cores

The number of cores to use during bootstrap. Only supported on UNIX-alike systems.

...

further parameters used by optim.pml or plot.phylo.

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)

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

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)

phangorn

Phylogenetic Reconstruction and Analysis

v2.7.0
GPL (>= 2)
Authors
Klaus Schliep [aut, cre] (<https://orcid.org/0000-0003-2941-0161>), Emmanuel Paradis [aut] (<https://orcid.org/0000-0003-3092-2199>), Leonardo de Oliveira Martins [aut] (<https://orcid.org/0000-0001-5247-1320>), Alastair Potts [aut], Tim W. White [aut], Cyrill Stachniss [ctb], Michelle Kendall [ctb], Keren Halabi [ctb], Richel Bilderbeek [ctb], Kristin Winchell [ctb], Liam Revell [ctb], Mike Gilchrist [ctb], Jeremy Beaulieu [ctb], Brian O'Meara [ctb], Long Qu [ctb]
Initial release

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