Package 'phytools'

Title: Phylogenetic Tools for Comparative Biology (and Other Things)
Description: A wide range of methods for phylogenetic analysis - concentrated in phylogenetic comparative biology, but also including numerous techniques for visualizing, analyzing, manipulating, reading or writing, and even inferring phylogenetic trees. Included among the functions in phylogenetic comparative biology are various for ancestral state reconstruction, model-fitting, and simulation of phylogenies and trait data. A broad range of plotting methods for phylogenies and comparative data include (but are not restricted to) methods for mapping trait evolution on trees, for projecting trees into phenotype space or a onto a geographic map, and for visualizing correlated speciation between trees. Lastly, numerous functions are designed for reading, writing, analyzing, inferring, simulating, and manipulating phylogenetic trees and comparative data. For instance, there are functions for computing consensus phylogenies from a set, for simulating phylogenetic trees and data under a range of models, for randomly or non-randomly attaching species or clades to a tree, as well as for a wide range of other manipulations and analyses that phylogenetic biologists might find useful in their research.
Authors: Liam J. Revell
Maintainer: Liam J. Revell <[email protected]>
License: GPL (>= 2)
Version: 2.3-24
Built: 2024-12-16 19:20:59 UTC
Source: https://github.com/liamrevell/phytools

Help Index

phytools: Phylogenetic Tools for comparative biology (and other things)

Description

phytools provides functions for phylogenetic biology: focused on phylogenetic comparative analysis, but including methods to simulate data and trees, to visualize trees and fitted models, and to analyze and manipulate phylogenetic trees and data.

The complete list of functions can be displayed with library(help=phytools).

The phytools development page is https://github.com/liamrevell/phytools/. More information on phytools can also be found at http://blog.phytools.org or http://www.phytools.org.

If you use phytools (or other packages that depend on phytools) in a publication, please cite it.

The appropriate citation for phytools is listed below or can be obtained using citation("phytools") with the package installed.

Author(s)

Liam J. Revell

Maintainer: Liam J. Revell <[email protected]>

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Add an arrow pointing to a tip or node on the tree

Description

Adds an arrow or a set of arrows to a plotted tree.

Usage

add.arrow(tree=NULL, tip, ...)

Arguments

tree

an object of class "phylo", "contMap", or "densityMap". If not supplied, the function will obtain the last plotted phylogeny from the environmental variable last_plot.phylo.
tip

label of tip or tip or node number; or vector of such values. If tree=NULL then the tip label(s) or node number(s) must be supplied.
...

optional arguments to control the shape and size of the arrow including: its length (arrl) in the units of the plot; the length of the arrowhead (hedl); the total angle between the wings in the arrowhead (angle); the line width for the plotted lines (lwd); the offset from the tip or end of tip label, in character widths (offset); and the color (col).

Details

Trees can be plotted using phytools function plotTree, plotSimmap, contMap, densityMap, and ape S3 method plot.phylo.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

nodelabels

Examples

## show arrows with a black outline
data(anoletree)
plotTree(anoletree,type="fan",fsize=0.7,ftype="i")
add.arrow(anoletree,tip=c("cuvieri","krugi",
    "pulchellus","poncensis","stratulus",
    "evermanni","cooki","cristatellus",
    "gundlachi","occultus"),lwd=5,arrl=1)
add.arrow(anoletree,tip="cuvieri",col="green",
    lwd=3,arrl=1)
add.arrow(anoletree,tip=c("krugi","pulchellus",
    "poncensis"),col="#E4D96F",lwd=3,arrl=1)
add.arrow(anoletree,tip=c("stratulus","evermanni"),
    col="darkgreen",lwd=3,arrl=1)
add.arrow(anoletree,tip=c("cooki","cristatellus",
    "gundlachi"),col="brown",lwd=3,arrl=1)
add.arrow(anoletree,tip="occultus",col="darkgrey",
    lwd=3,arrl=1)
legend(x="topleft",c("crown-giant","grass-bush","trunk-crown","trunk-ground",
    "twig"),pch=22,pt.bg=c("green","#E4D96F","darkgreen",
    "brown","darkgrey"),cex=0.9,
    pt.cex=2,title="PR ecomorphs",bty="n")
par(mar=c(5.1,4.1,4.1,2.1)) ## reset margins to default

Add color bar to a plot

Description

This function adds a color gradient legend to an existing plot.

Usage

add.color.bar(leg, cols, title=NULL, lims=c(0,1), digits=1, prompt=TRUE,
   lwd=4, outline=TRUE, ...)

Arguments

leg

numerical value for the length of the legend.
cols

colors for the legend.
title

text to plot above the bar.
lims

range for the bar.
digits

digits for plotted numbers.
prompt

logical value indicating whether the location of the legend should be obtained interactively.
lwd

width of the plotted bar.
outline

logical value indicated whether or not to outline the plotted color bar with a 1 pt line.
...

optional arguments including: x x-coordinate of the legend (if prompt=FALSE); y y-coordinate of the legend; subtitle optional legend subtitle; direction direction of the color bar (i.e., increase from left to right or from right to left); and fsize, font size for the legend text.

Details

This function was designed to add a color bar to a plot created by plotBranchbyTrait. A color bar can be added by clicking on a location within the plot (when prompt=TRUE) or by setting prompt=FALSE and supplying x & y coordinates for the object.

The function is also used internally by S3 methods plot.contMap and plot.densityMap, as well as by errorbar.contMap.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2013) Two new graphical methods for mapping trait evolution on phylogenies. Methods in Ecology and Evolution, 4, 754-759.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

contMap, densityMap, errorbar.contMap, plotBranchbyTrait

Add tip to all edges in a tree

Description

This function adds a tip to all branches of the tree and returns a a list of trees as an object of class "multiPhylo".

Usage

add.everywhere(tree, tip.name)

Arguments

tree

an object of class "phylo".
tip.name

a string containing the name of the tip to add.

Value

A list of trees as an object of class "multiPhylo". Since the tip can be added to any branch, the length of the list is equal to the number of edges in tree.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

allFurcTrees, exhaustiveMP

Add tips at random to the tree

Description

This function adds new tips at random to a tree with branch lengths.

Usage

add.random(tree, n=NULL, tips=NULL, edge.length=NULL, order=c("random","input"))

Arguments

tree

an object of class "phylo".
n

a number of tips to add to the tree. If NULL, will use length(tips). If tips is specified, then n is also ignored, regardless of its value.
tips

a set of tip names for the added tips. If NULL, names will be supplied
edge.length

terminal edge length for the added tips. If NULL, and is.ultrametric(tree) ==TRUE, then edge lengths will be assigned to keep the tree ultrametric. Note that if edge lengths are assigned and n>1, then the assigned terminal edge lengths are not guaranteed as subsequent random tip addition could occur along the new terminal edge.
order

addition order for the new tips.

Details

If no edge lengths are provided, and the tree is ultrametric, then edge lengths are assigned to keep the tree ultrametric.

The probability that at new tip is added along any branch is directly proportional to the length of the branch.

Note that sometimes the resultant tree plotted with plot.phylo or plotSimmap may display with branches crossing. If so, the tree can be 'untangled' using untangle.

Value

An object of class "phylo".

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

allFurcTrees, add.everywhere

Add legend to stochastically mapped tree

Description

Adds a legend (by default, interactively) to a plotted stochastic character mapped tree.

Usage

add.simmap.legend(leg=NULL, colors, prompt=TRUE, vertical=TRUE, ...)

Arguments

leg

states for the discrete character in the order of colors.
colors

colors for the legend in the order of leg, or, if leg=NULL, named vector of colors in which names(colors are the states of the mapped discrete character.
prompt

logical value indicating whether the location of the legend should be obtained interactively (i.e., by clicking in the plotting area).
vertical

logical value indicating whether to plot the legend vertically (if TRUE) or horizontally.
...

optional arguments including: x x-coordinate of the legend (if prompt=FALSE); y y-coordinate of the legend; and shape which can be shape="square", the default, or shape="circle".

Details

Redundant with legend, which is much more powerful but somewhat more complicated to use.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

plotSimmap

Add species to genus on a phylogeny or bind simulated species subtrees to a backbone genus tree

Description

add.species.to.genus adds an additional species to a genus on a phylogeny.

genus.to.species.tree simulates pure-birth subtrees and then binds them at a random height along the terminal edge leading to each corresponding genus on a genus-level backbone tree.

Usage

add.species.to.genus(tree, species, genus=NULL, where=c("root","random"))
genus.to.species.tree(tree, species)

Arguments

tree

an object of class "phylo". In the case of genus.to.species.tree this should be a genus-level backbone tree.
species

string contain species name in the format "Genus_species" or "Genus species".
genus

for add.species.to.genus, optional argument containing the genus to which species is to be attached. If NULL then genus will be extracted from species.
where

for add.species.to.genus, the location to attach species to the tree. where= "root" will cause the species to be attached to the MRCA of all members of genus. where="random" will cause species to be attached at random to the subtree descended from the MRCA of all members of genus.

Details

For add.species.to.genus, if genus contains only one species and where="root", then species will be attached midway along the branch leading to the one species. If where="random" then species will be added at a random position along the edge.

If genus cannot be found in the tree, then the original tree is returned and a warning printed. If the tree is not ultrametric, then the resultant tree may not contain branch lengths and a warning will be printed.

Note that for some cases in which a tree is read in from file, R may initially think it is ultrametric, but then later (as tips are added) decide that it is not due to rounding of the edge lengths when it was written to file. This can most likely be resolved by using force.ultrametric to coerce the tree to be exactly ultrametric (to the maximum numerical precision permitted by R) before adding tips to the tree.

If genus is non-monophyletic then species will be attached to the most inclusive group containing members of genus and a warning will be printed.

Value

An object of class "phylo".

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

add.random, bind.tip

Computes Akaike weights

Description

Computes Akaike weights based on a set of AIC values.

Usage

aic.w(aic)

Arguments

aic

vector of Akaike Information Criterion (AIC; Akaike, 1974) values for different fitted models. If the vector has names, these names will be inherited by the vector returned by the function.

Details

This function computes Akaike weights from a set of AIC values obtained from fitted models.

It returns an object of class "aic.w" which is just a vector which allows it to be automatically printed with a numerical precision of 8 significant digits.

Value

A vector of Akaike weights.

Author(s)

Liam Revell [email protected]

References

Akaike, H. (1974) A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19, 716-723.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Generate all bi- and multifurcating unrooted trees

Description

This function creates all possible unrooted bi- and multifurcating trees and returns a list of trees as an object of class "multiPhylo".

Usage

allFurcTrees(n, tip.label=NULL, to.plot=TRUE)

Arguments

n

an integer giving the desired number of species.
tip.label

an optional vector of length n containing the tip names.
to.plot

an optional logical value indicating whether or not to plot the trees.

Details

This function should be used with extreme caution for n greater than about 8, as in this case the number of possible trees is extremely large.

Value

A list of trees as an object of class "multiPhylo".

Author(s)

Liam Revell [email protected]

References

Felsenstein, J. 2004. Inferring Phylogenies. Sinauer.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

add.everywhere, exhaustiveMP

Examples

## compute & plot all bi- and multifurcating
## trees for six taxa
trees<-allFurcTrees(n=6)
par(mfrow=c(16,15))
nulo<-sapply(trees,plot,type="unrooted",
    no.margin=TRUE)
par(mfrow=c(1,1))

Bayesian ancestral character estimation

Description

This function uses Bayesian MCMC to sample from the posterior distribution for the states at internal nodes in the tree.

Usage

anc.Bayes(tree, x, ngen=10000, control=list(), ...)
## S3 method for class 'anc.Bayes'
plot(x, ...)
## S3 method for class 'anc.Bayes'
density(x, ...)

Arguments

tree

an object of class "phylo".
x

a vector of tip values for species; names(x) should be the species names. In the case of the plot and density methods, an object of class "anc.Bayes".
ngen

a integer indicating the number of generations for the MCMC.
control

a list of control parameters containing the following elements: sig2: starting value for σ2\sigma^2 (BM rate); a: starting for the state at the root node; y: starting values for the states at all internal nodes excluding the root (should be labeled with node numbers); pr.mean: means for the prior distributions in the following order - sig2, a, y, note that the prior probability distribution is exponential for sig2 and normal for a and y; pr.var: variances on the prior distributions, same order as pr.mean (but the variance is not used for sig2); prop: variances on the normal proposal distributions in the same order as pr.mean; sample: sample frequency from the MCMC.
...

optional arguments, including to be passed to plot and density methods.

Details

plot.anc.Bayes generates a likelihood profile plot of the MCMC by default, but can also create a profile plot for any of the sampled variables by using the optional argument what. For instance, what=40 (or, equivalently, what="40") will create a profile plot of the MCMC for node 40. Additional arguments are passed to plot.

density.anc.Bayes computes a posterior density from the MCMC sample. Like plot.anc.Bayes takes the optional argument what, but unlike plot.anc.Bayes computes the posterior density for the root node by default. The object computed by this function is of class "density" and can be visualized using plot.density. Burn-in (in generations) can be set using the optional argument burnin, otherwise it will be assumed to be 20

The print and summary methods for this object class also return (invisibly) a vector of estimated ancestral states based on a user-supplied burn-in (or 20% of the number of generations of MCMC, if no burn-in is provided). Burn-in can be specified with the optional argument burnin.

Value

anc.Bayes returns an object of class "anc.Bayes" including at least two components:

mcmc

a data frame with rows ngen/sample+1 containing the posterior sample and likelihoods. Matrix columns are labeled either sig2 or by the node number of the internal node.
tree

our input phylogeny.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

ace, anc.ML, anc.trend, evol.rate.mcmc, fastAnc

Examples

## set seed
set.seed(77)
## load data from Garland et al. (1992)
data(mammal.tree)
data(mammal.data)
## extract character of interest
ln.bodyMass<-log(setNames(mammal.data$bodyMass,
    rownames(mammal.data)))
## run MCMC (should be run at least 1e6 generations)
mcmc<-anc.Bayes(mammal.tree,ln.bodyMass,
    ngen=50000)
print(mcmc,printlen=20) ## estimates
par(mfrow=c(2,1))
plot(mcmc,bty="l",main="Likelihood-profile from MCMC",
    font.main=3) ## likelihood-profile
plot(density(mcmc,what=Ntip(mammal.tree)+1,
    burnin=20000),bty="l",
    main="Posterior density for root state of log(body mass)",
    font.main=3)
par(mfrow=c(1,1)) ## reset par to default

Ancestral character estimation using likelihood

Description

This function estimates the evolutionary parameters and ancestral states for Brownian evolution using likelihood. It is also possible (for model="BM") to allow for missing data for some tip taxa.

Usage

anc.ML(tree, x, maxit=2000, model=c("BM","OU","EB"), ...)

Arguments

tree

an object of class "phylo".
x

a vector of tip values for species; names(x) should be the species names.
maxit

an optional integer value indicating the maximum number of iterations for optimization.
model

model of continuous character evolution on the tree. It's possible that only model="BM" & model="EB" work in the present version as model="OU" has not be thoroughly tested & some bugs were reported for an earlier version.
...

optional arguments.

Details

Because this function relies on a high dimensional numerical optimization of the likelihood function, fastAnc should probably be preferred for most purposes. If using anc.ML, users should be cautious to ensure convergence.

This issue has been ameliorated in phytools >= 0.2-48 by seeding the ML optimization with the result from fastAnc.

For model="EB" this should also not be a problem as the numerical optimization is performed for only sig2 and r, while the ML values of the ancestral states are obtained during every iteration of the optimization algorithmically using the re-rooting method.

Value

An object of class "anc.ML" with at least the following four elements (if not more, depending on model):

sig2

the variance of the BM process.
ace

a vector with the ancestral states.
logLik

the log-likelihood.
convergence

the value of convergence returned by optim (0 is good).

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Schluter, D., Price, T., Mooers, A. O., and Ludwig, D. (1997) Likelihood of ancestor states in adaptive radiation. Evolution 51, 1699-1711.

See Also

ace, anc.Bayes, fastAnc, optim

Examples

## load data from Garland et al. (1992)
data(mammal.tree)
data(mammal.data)
## extract character of interest
ln.bodyMass<-log(setNames(mammal.data$bodyMass,
    rownames(mammal.data)))
## estimate ancestral state under BM model
fit.BM<-anc.ML(mammal.tree,ln.bodyMass)
print(fit.BM)

Ancestral character estimation with a trend

Description

This function estimates the evolutionary parameters and ancestral states for Brownian evolution with a directional trend.

Usage

anc.trend(tree, x, maxit=2000)

Arguments

tree

an object of class "phylo".
x

a vector of tip values for species; names(x) should be the species names.
maxit

an optional integer value indicating the maximum number of iterations for optimization.

Details

Note that this will generally only work and produce sensible results for a phylogeny with some non-contemporaneous tips (i.e., a tree with some fossil species).

The function uses optim with method= "L-BFGS-B" internally; however, optimization is only constrained for the sig2 which must be > 0.

Value

An object of class "anc.trend" with the following components:

ace

a vector with the ancestral states.
mu

a trend parameter per unit time.
sig2

the variance of the BM process, σ2\sigma^2.
logL

the log-likelihood.
convergence

the value of $convergence returned by optim() (0 is good).

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

ace, anc.Bayes, anc.ML, optim

Examples

## simulate tree & data using fastBM with a trend (m!=0)
tree<-rtree(n=26,tip.label=LETTERS)
x<-fastBM(tree,mu=4,internal=TRUE)
a<-x[as.character(1:tree$Nnode+Ntip(tree))]
x<-x[tree$tip.label]
## fit no trend model
fit.bm<-anc.ML(tree,x,model="BM")
print(fit.bm)
## fit trend model
fit.trend<-anc.trend(tree,x)
print(fit.trend)
## compare trend vs. no-trend models & estimates
AIC(fit.bm,fit.trend)
layout(matrix(c(3,4,1,2,5,6),3,2,byrow=TRUE),
    heights=c(1.5,3,1.5),widths=c(3,3))
xlim<-ylim<-range(c(a,fit.bm$ace,
    fit.trend$ace))
plot(a,fit.bm$ace,pch=19,
    col=make.transparent("blue",0.5),
    xlab="true ancestral states",
    ylab="ML estimates",
    main=paste("Comparison of true and estimated",
    "\nstates under a no-trend model"),font.main=3,
    cex.main=1.2,bty="l",cex=1.5,
    xlim=xlim,ylim=ylim)
lines(xlim,ylim,lty="dotted")
plot(a,fit.trend$ace,pch=19,
    col=make.transparent("blue",0.5),
    xlab="true ancestral states",
    ylab="ML estimates",
    main=paste("Comparison of true and estimated",
    "\nstates under a trend model"),font.main=3,
    cex.main=1.2,bty="l",cex=1.5,
    xlim=xlim,ylim=ylim)
lines(xlim,ylim,lty="dotted")
par(mfrow=c(1,1))

Compute marginal or joint ancestral state estimates

Description

By default, ancr computes marginal ancestral states, also known as empirical Bayes posterior probabilities, conditioning on the fitted (or set) model of object.

Can also perform joint ancestral state estimation, if the optional argument type is set to type="joint".

hide.hidden merges hidden states (if any).

Usage

ancr(object, ...)
hide.hidden(object, ...)
## S3 method for class 'ancr'
plot(x, args.plotTree=list(...), args.nodelabels=list(...), ...)

Arguments

object

fitted Mk model (presently object of class "fitMk", "fitpolyMk", and "fitHRM"), or a set of models in the form of a table from anova comparison. For hide.hidden, object of class "ancr".
...

optional arguments.
x

in the case of plot.ancr, an object of class "ancr".
args.plotTree

arguments to be passed to plotTree, in a list.
args.nodelabels

arguments to be passed to nodelabels, in a list.

Details

If the optional argument tips=TRUE, then the matrix returned contains empirical Bayes posterior probabilities (marginal scaled likelihoods) for both tips and internal nodes. Otherwise (the default) only node marginal states are returned.

If the input object is a set of models (in the form of an anova table), then ancr will compute model-averaged marginal ancestral states (for type="marginal", unless the optional argument weighted=FALSE, in which case only the best-supported model is used.

Value

An object of class "ancr". In the case of type="marginal", this object consists of a matrix of marginal (empirical Bayes) probabilities and a likelihood. In the case of type="joint", the object contains a set of most-likely internal node states stored in a data frame.

Author(s)

Liam Revell [email protected]

References

Pagel, M. (1999) The Maximum Likelihood approach to reconstructing ancestral character states of discrete characters on phylogenies. Systematic Biology, 3, 612-622.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

fitMk

Examples

## load tree and data from Revell & Collar (2009)
data(sunfish.tree)
data(sunfish.data)
## extract discrete character (feeding mode)
fmode<-setNames(sunfish.data$feeding.mode,
  rownames(sunfish.data))
## fit ARD model
ard_fmode<-fitMk(sunfish.tree,fmode,model="ARD",
  pi="fitzjohn")
## compute ancestral states
anc_fmode<-ancr(ard_fmode)
## plot the results
par(mfrow=c(2,1))
cols<-setNames(c("blue","red"),levels(fmode))
plot(anc_fmode,
  args.plotTree=list(lwd=2,direction="upwards",
    mar=c(0.1,1.1,2.1,1.1),fsize=0.8),
  args.nodelabels=list(piecol=cols),
  args.tiplabels=list(cex=0.3),
  legend="bottomright")
mtext("a) marginal states under ARD model",adj=0)
## fit ER model
er_fmode<-fitMk(sunfish.tree,fmode,model="ER",
  pi="fitzjohn")
## compare models
aov_fmode<-anova(er_fmode,ard_fmode)
## compute model-averaged ancestral states
anc_fmode_model.averaged<-ancr(aov_fmode)
plot(anc_fmode_model.averaged,
  args.plotTree=list(lwd=2,direction="upwards",
    mar=c(0.1,1.1,2.1,1.1),fsize=0.8),
  args.nodelabels=list(piecol=cols),
  args.tiplabels=list(cex=0.3),
  legend="bottomright")
mtext("b) marginal states model-averaging ER & ARD models",
  adj=0)
par(mar=c(5.1,4.1,4.1,2.1),mfrow=c(1,1))

Ancestral character estimation under the threshold model using Bayesian MCMC

Description

This function uses Bayesian MCMC to estimate ancestral states and thresholds for a discrete character under the threshold model from quantitative genetics (Felsenstein 2012).

Usage

ancThresh(tree, x, ngen=100000, sequence=NULL, method="mcmc", 
   model=c("BM","OU","lambda"), control=list(), ...)

Arguments

tree

phylogenetic tree.
x

a named vector containing discrete character states; or a matrix containing the tip species, in rows, and probabilities of being in each state, in columns.
ngen

number of generations to run the MCMC.
sequence

assumed ordering of the discrete character state. If not supplied and x is a vector then numerical/alphabetical order is assumed; if not supplied and x is a matrix, then the column order of x is used.
method

only method currently available is "mcmc".
model

model for the evolution of the liability. Options are "BM" (Brownian motion, the default), "OU" (Ornstein-Uhlenbeck), or "lambda" (the λ\lambda model).
control

list containing the following elements: sample, the sampling interval; propliab variance of the proposal distribution for liabilities; propthresh variance on the proposal distribution for the thresholds; propalpha variance on the proposal distribution for alpha (for model="OU"); pr.anc prior probability distribution on the ancestral states for each node, in a matrix - not all nodes need to be supplied; pr.th prior density on the thresholds; burnin number of generations to exclude for burn-in when plotting posterior probabilities on the tree; plot logical value indicating whether or not to plot the posterior probabilities; print logical value indicating whether or not to print the state of the MCMC; piecol colors for the posterior probabilities plotted as pie charts at internal nodes; and tipcol which indicates whether the tip colors should be based on the input data ("input") or sampled tip liabilities ("estimated"). These will only differ if there is uncertainty in the tip states.
...

additional arguments to be passed to plotThresh (called internally).

Details

According to the threshold model from evolutionary quantitative genetics, values for our observed discrete character are determined by an unseen continuous trait, normally referred to as liability. Every time the value for liability crosses a threshold, the observed discrete character changes in state.

Felsenstein (2012) first had the insight that this model could be used to study the evolution of discrete character traits on a reconstructed phylogenetic tree.

This function uses Bayesian MCMC to sample ancestral liabilities and thresholds for a discrete character evolution under the threshold model.

print and plot S3 methods are now available for the object class "ancThresh".

Value

This function returns an object of class "ancThresh" containing the posterior sample from our analysis, along with other components.

Author(s)

Liam Revell [email protected]

References

Felsenstein, J. (2012) A comparative method for both discrete and continuous characters using the threshold model. American Naturalist, 179, 145-156.

Revell, L. J. (2014) Ancestral character estimation under the threshold model from quantitative genetics. Evolution, 68, 743-759.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

anc.Bayes, threshBayes

Examples

## Not run: 
## load data from Revell & Collar (2009)
data(sunfish.tree)
data(sunfish.data)
## extract character of interest
fmode<-setNames(sunfish.data$feeding.mode,
    rownames(sunfish.data))
## run MCMC
mcmc<-ancThresh(sunfish.tree,fmode,ngen=1000000)
## plot results
plot(mcmc,mar=c(0.1,0.1,4.1,0.1))
title(main="Posterior probabilities for node states",
    font.main=3)
## End(Not run)

Phylogenetic datasets

Description

Various phylogenetic datasets for comparative analysis.

Usage

data(anole.data)
data(anoletree)
data(ant.geog)
data(ant.tree)
data(bat.tree)
data(bat_virus.data)
data(betaCoV.tree)
data(bonyfish.data)
data(bonyfish.tree)
data(butterfly.data)
data(butterfly.tree)
data(cordylid.data)
data(cordylid.tree)
data(darter.tree)
data(eel.data)
data(eel.tree)
data(elapidae.tree)
data(flatworm.data)
data(flatworm.tree)
data(liolaemid.tree)
data(mammal.data)
data(mammal.geog)
data(mammal.tree)
data(primate.data)
data(primate.tree)
data(salamanders)
data(sunfish.data)
data(sunfish.tree)
data(tortoise.geog)
data(tortoise.tree)
data(tropidurid.data)
data(tropidurid.tree)
data(vertebrate.data)
data(vertebrate.tree)
data(wasp.data)
data(wasp.trees)
data(whale.tree)

Format

anoletree is an object of class "simmap". anole.data is a data frame.

ant.tree is an object of class "phylo". ant.geog is a vector.

bat.tree and betaCoV.tree are objects of class "phylo". bat_virus.data is a data frame.

bonyfish.tree is an object of class "phylo". bonyfish.data is a data frame.

butterfly.tree is an object of class "phylo". butterfly.data is a data frame.

cordylid.tree is an object of class "phylo". cordylid.data is a data frame.

darter.tree is an object of class "phylo".

eel.tree is an object of class "phylo". eel.data is a data frame.

elapidae.tree is an object of class "phylo".

flatworm.tree is an object of class "phylo". flatworm.data is a data frame.

liolaemid.tree is an object of class "phylo". liolaemid.data is a data frame.

mammal.tree is an object of class "phylo". mammal.data is a data frame. mammal.geog is a numerical matrix.

primate.tree is an object of class "phylo". primate.data is a data frame.

salamanders is an object of class "phylo".

sunfish.tree is an object of class "simmap". sunfish.data is a data frame.

tortoise.tree is an object of class "phylo". tortoise.geog is a data frame.

tropidurid.tree is an object of class "simmap". tropidurid.data is a data frame.

vertebrate.tree is an object of class "phylo". vertebrate.data is a data frame.

wasp.trees is an object of class "multiPhylo". wasp.data is a data frame.

whale.tree is an object of class "phylo".

Details

anoletree is a phylogeny of Greater Antillean anole species with a mapped discrete character - ecomorph class. anole.data is a data frame of morphological characters. Data and tree are from Mahler et al. (2010).

ant.tree is a phylogeny containing 84 species of fungus farming attine ants. ant.geog is a vector containing biogegraphic information for the species of the tree. Both the phylogeny and biogeographic information were originally published by Branstetter et al. (2017).

bat.tree is a ML phylogeny of bats from the families Mormoopidae, Molossidae, and Phyllostomidae, based on GenBank accession numbers reported in Caraballo (2022) and estimated using phangorn. betaCoV.tree is a ML phylogenetic tree of betacoronaviruses based on GenBank accession numbers reported in Caraballo (2022) and estimated using phangorn. bat_virus.data is an association table of host and virus from Caraballo (2022).

butterfly.tree and butterfly.data are a phylogeny and dataset of habitat use in Mycalesina butterflies from Halali et al. (2020). The phylogeny of that study was adapted from one originally published by Brattstrom et al. (2020).

bonyfish.tree and bonyfish.data are a phylogeny and dataset of spawning mode and parental care in bony fishes from Benun Sutton and Wilson (2019). Their phylogenetic tree was adapted from a tree originally published by Betancur-R et al. (2017)

cordylid.tree and cordylid.data are a phylogeny and dataset of morphological traits for three different principal components axes from Broeckhoven et al. (2016).

darter.tree is a phylogeny of 201 species of darter fish (Etheostomatinae) from Near et al. (2011).

eel.tree and eel.data are a phylogeny and dataset of feeding mode and maximum total length from 61 species of elopomorph eels from Collar et al. (2014).

elapidae.tree is a reconstructed phylogeny containing 175 species of snakes of the family Elapidae from Lee et al. (2016).

flatworm.tree and flatworm.data are a phylogeny and dataset of habitat preferences for flatworms from Benitez-Alvarez et al. (2020). flatworm.tree has been made ultrametric using penalized likelihood.

liolaemid.tree and liolaemid.data are a phylogenetic tree and phenotypic trait dataset of lizards from the family Liolaemidae from Esquerre et al. (2019).

mammal.tree and mammal.data are the phylogeny and dataset for mammal body size and home range size from Garland et al. (1992). mammal.geog is a matrix containing geographic coordinates for various of the species in mammal.tree pulled from citizen science observations registered on the iNaturalist web platform.

primate.tree and primate.data are a phylogeny and phenotypic trait dataset from Kirk and Kay (2004).

salamanders is a phylogeny of Plethodon salamanders from Highton and Larson (1979). According to Wikipedia, the genus Plethodon contains 55 species in total.

sunfish.tree and sunfish.data are the phylogeny and dataset for Centrarchidae and buccal morphology (respectively) from Revell and Collar (2009).

tortoise.tree and tortoise.geog are a phylogeny and dataset of geographic coordinates for Galapagos tortoises. The geographic locality information was approximated from Figure 1 of Poulakakis et al. (2020), and the tree was estimated from nucleotide sequence data published with the same study.

tropidurid.tree and tropidurid.data are the phylogeny and bivariate quantitative trait dataset of tropidurid lizards from Revell et al. (2022).

vertebrate.tree is a time-calibrated phylogeny of vertebrates and vertebrate.data is a dataset of phenotypic traits. The phylogeny is from http://www.timetree.org/ (Hedges et al. 2006).

wasp.trees and wasp.data are the phylogeny and host-parasite associations from Lopez-Vaamonde et al. (2001).

whale.tree is a phylogeny of cetaceans originally published in Steeman et al. (2009).

Source

Benitez-Alvarez, L., A. Maria Leal-Zanchet, A. Oceguera-Figueroa, R. Lopes Ferreira, D. de Medeiros Bento, J. Braccini, R. Sluys, and M. Riutort (2020) Phylogeny and biogeography of the Cavernicola (Platyhelminthes: Tricladida): Relicts of an epigean group sheltering in caves? Molecular Phylogenetics and Evolution, 145, 106709.

Benun Sutton, F., and A. B. Wilson (2019) Where are all the moms? External fertilization predicts the rise of male parental care in bony fishes. Evolution, 73, 2451-2460.

Betancur-R, R., E. O. Wiley, G. Arratia, A. Acero, N. Bailly, M. Miya, G. Lecointre, and G. Orti (2017) Phylogenetic classification of bony fishes. BMC Ecology and Evolution, 17, 162.

Branstetter, M. G., A. Jesovnik, J. Sosa-Calvo, M. W. Lloyd, B. C. Faircloth, S. G. Brady, and T. R. Schultz (2017) Dry habitats were crucibles of domestication in the evolution of agriculture in ants. Proceedings of the Royal Society B, 284, 20170095.

Brattstrom, O., K. Aduse-Poku, E. van Bergen, V. French, and P. M. Brakefield (2020) A release from developmental bias accelerates morphological diversification in butterfly eyespots. Proceedings of the National Academy of Sciences, 177, 27474-27480.

Broeckhoven, C., G. Diedericks, C. Hui, B. G. Makhubo, P. le Fras N. Mouton (2016) Enemy at the gates: Rapid defensive trait diversification in an adaptive radiation of lizards. Evolution, 70, 2647-2656.

Caraballo, D. A. (2022) Cross-species transmission of bat coronaviruses in the Americas: Contrasting patterns between alphacoronavirus and betacoronavirus. Microbiology Spectrum, 10, e01411-22.

Collar, D. C., P. C. Wainwright, M. E. Alfaro, L. J. Revell, and R. S. Mehta (2014) Biting disrupts integration to spur skull evolution in eels. Nature Communications, 5, 5505.

Esquerre, D., D. Ramirez-Alvarez, C. J. Pavon-Vazquez, J. Troncoso-Palacios, C. F. Garin, J. S. Keogh, and A. D. Leache (2019) Speciation across mountains: Phylogenomics, species delimitation and taxonomy of the Liolaemus leopardinus clade (Squamata, Liolaemidae). Molecular Phylogenetics and Evolution, 139, 106524.

Garland, T., Jr., P. H. Harvey, and A. R. Ives (1992) Procedures for the analysis of comparative data using phylogenetically independent contrasts. Systematic Biology, 41, 18-32.

Kirk, E. C., and R. F. Kay (2004) The evolution of high visual acuity in the Anthropoidea. In: Ross, C. F., Kay R. F. (Eds), Anthropoid Origins. Developments in Primatology: Progress and Prospects, 539-602. Springer, Boston, MA.

Halali, S., E. van Bergen, C. J. Breuker, P. M. Brakefield, and O. Brattstrom (2020) Seasonal environments drive convergent evolution of a faster pace-of-life in tropical butterflies. Ecology Letters, 24, 102-112.

Hedges, S. B., J. Dudley, and S. Kumar (2006) TimeTree: A public knowledgebase of divergence times among organisms. Bioinformatics, 22, 2971-2972.

Highton, R., and A. Larson (1979) The genetic relationships of the salamanders of the genus Plethodon. Systematic Zoology, 28, 579-599.

Lee, M. S. Y., K. L. Saunders, B. King, and A. Palci (2016) Diversification rates and phenotypic evolution in venomous snakes (Elapidae). Royal Society Open Science, 3, 150277.

Lopez-Vaamonde, C., J. Y. Rasplus, G. D. Weiblen, and J. M. Cook (2001) Molecular phylogenies of fig wasps: Partial cocladogenesis of pollinators and parasites. Molecular Phylogenetics and Evolution, 21, 55-71.

Mahler, D. L, L. J. Revell, R. E. Glor, and J. B. Losos (2010) Ecological opportunity and the rate of morphological evolution in the diversification of Greater Antillean anoles. Evolution, 64, 2731-2745.

Near, T. J., C. M. Bossu, G. S. Bradburd, R. L. Carlson, R. C. Harrington, P. R. Hollingsworth Jr., B. P. Keck, and D. A. Etnier. (2011) Phylogeny and temporal diversification of darters (Percidae: Etheostomatinae). Systematic Biology, 60, 565-595.

Poulakakis, N., J. M. Miller, E. L. Jensen, L. B. Beheregaray, M. A. Russello, S. Glaberman, J. Boore, and A. Caccone. (2020) Colonization history of Galapagos giant tortoises: Insights from mitogenomes support the progression rule. Journal of Zoological Systematics and Evolutionary Research, 58, 1262-1275.

Revell, L. J., and D. C. Collar (2009) Phylogenetic analysis of the evolutionary correlation using likelihood. Evolution, 63, 1090-1100.

Revell, L. J., K. S. Toyama, and D. L. Mahler (2022) A simple hierarchical model for heterogeneity in the evolutionary correlation a phylogenetic tree. PeerJ, 10, e13910.

Steeman, M. E., M. B. Hebsgaard, R. E. Fordyce, S. Y. W. Ho, D. L. Rabosky, R. Nielsen, C. Rahbek, H. Glenner, M. V. Sorensen, and E. Willerslev (2009) Radiation of extant cetaceans driven by restructuring of the oceans. Systematic Biology, 58, 573-585.

Compute the parsimony score

Description

Plots a phylogeny in a silly, ANSI graphics style.

Usage

ansi_phylo(tree, vertical=c("|","-"), ...)

Arguments

tree

object of class "phylo".
vertical

character for vertical lines
...

optional arguments.

Value

A plotted tree.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

plotTree, splinePhylogram

Examples

data(salamanders)
ansi_phylo(salamanders)
par(mar=c(5.1,4.1,4.1,2.1))

Applies the branch lengths of a reference tree to a target

Description

Applies the branch lengths of a reference tree to a target.

Usage

applyBranchLengths(tree, edge.length)

Arguments

tree

target tree.
edge.length

number of digits for rounding. Passed to round.

Details

This function applies the set of branch lengths from a reference tree to a target tree while reconciling any mappings (as in read.simmap) with the new branch lengths.

Value

An object of class "phylo" or "simmap".

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Conversion to object of class "multiPhylo"

Description

This function converts between object classes.

Usage

as.multiPhylo(x, ...)
## S3 method for class 'multiSimmap'
as.multiPhylo(x, ...)
## S3 method for class 'phylo'
as.multiPhylo(x, ...)

Arguments

x

object to be converted to "multiPhylo". Presently an object of class "multiSimmap", or an object of class "phylo". In the latter case an object of class "multiPhylo" with length 1 is generated.
...

optional arguments.

Value

An object of class "multiPhylo".

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Convert a fitted Mk model to a Q-matrix

Description

Extracts a Q-matrix from a fitted Mk model.

Usage

as.Qmatrix(x, ...)
## S3 method for class 'fitMk'
as.Qmatrix(x, ...)
## S3 method for class 'Qmatrix'
plot(x, ...)
## S3 method for class 'Qmatrix'
print(x, ...)

Arguments

x

fitted Mk model. (For instance, an object of class "fitMk".) In the case of print.Qmatrix, an object of class "Qmatrix".
...

optional arguments.

Details

This function extracts a Q-matrix (in the form of an object of class "Qmatrix") from a fitted Mk model.

Value

An object of class "Qmatrix".

plot.Qmatrix invisibly returns the coordinates of vertices of the plotted Q-matrix.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

fitMk

Average the posterior rates

Description

Internal function for posterior.evolrate.

Usage

ave.rates(tree, shift, tips, sig1, sig2, ave.shift, showTree=TRUE)

Arguments

tree

a tree.
shift

the shift point for this sample.
tips

tip names tipward of shift.
sig1

σ12\sigma_1^2.
sig2

σ22\sigma_2^2.
ave.shift

average shift from all samples.
showTree

logical value indicating whether to plot the rate-stretched tree.

Value

A list of the rates.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

evol.rate.mcmc, minSplit, posterior.evolrate

Compute an average tree from a set of trees and related operations

Description

Compute average trees or consensus trees by various criteria.

Usage

averageTree(trees, start=NULL, method="quadratic.path.difference",
   tol=1e-12, quiet=FALSE, ...)
ls.consensus(trees, start=NULL, tol=1e-12, quiet=FALSE, ...)
minTreeDist(tree, trees, method="quadratic.path.difference", ...)

Arguments

trees

object of class "multiPhylo".
tree

object of class "phylo". For minTreeDist the tree on which to find the edge lengths that minimize the distance to the phylogenies in trees.
start

starting tree for optimization.
method

distance criterion for minimization. Options are "symmetric.difference", "branch.score.difference", "path.difference", and "quadratic.path.difference".
tol

tolerance value for optimization.
quiet

logical value indicating whether to run "quietly" or not.
...

other arguments to be passed internally.

Details

The function averageTree tries to find the (hypothetical) tree topology and branch lengths that has a minimum distance to all the trees in an input set, according to some user-specified tree distance measure.

The function ls.consensus computes the least-squares consensus tree (Lapointe & Cucumel, 1997) from a set of input trees.

Finally, the function minTreeDist finds the tree in the input set that is a minimum distance to all the other trees in the set. (This contrasts with averageTree which can return a tree not in the input set.)

Value

An object of class "phylo" with edge lengths.

Author(s)

Liam Revell [email protected]

References

Lapointe, F.-J., G. Cucumel (1997) The average consensus procedure: Combination of weighted trees containing identical or overlapping sets of taxa. Systematic Biology, 46, 306-312.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Convert object of class "birthdeath" to raw birth & death rates

Description

Converts an object of class "birthdeath" (from birthdeath) to a vector with the ML birth & death rates.

Usage

bd(x)

Arguments

x

object of class "birthdeath".

Details

This is now somewhat obsolete as phytools now contains functions to fit birth-death and pure-birth diversification models from trees (fit.bd and fit.yule) that also take into account incomplete sampling fraction.

Value

A vector.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

birthdeath, fit.bd, fit.yule

Attaches a new tip to a tree

Description

Adds a new tip to the tree.

Usage

bind.tip(tree, tip.label, edge.length=NULL, where=NULL, position=0,
   interactive=FALSE, ...)

Arguments

tree

receptor tree.
tip.label

a string containing the species name for the new tip.
edge.length

edge length for the new tip (a scalar).
where

node number to attach new tip. If position>0 then then tip will be attached rootward of the specified node. Node numbers can also be tips, in which case the new tip will be added along the terminal edge. To find out the tip number for given species with name "species" type: which(tree$tip.label=="species").
position

distance rootward of the node to add the new tip.
interactive

logical value indicating whether or not the species should be added interactively. (Defaults to FALSE.)
...

arguments to be passed to plotTree (for interactive=TRUE.)

Details

If the tree is ultrametric and no branch length is specified, then edge.length is scaled so that the tree remains ultrametric after the new tip is added.

Wrapper function for ape bind.tree. Note that interactive=TRUE works only for right-facing phylograms.

Value

An object of class "phylo".

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Examples

set.seed(123)
par(mfrow=c(3,1))
## generate tree
tree<-pbtree(b=0.1, n=10)
## plot original tree
plotTree(tree,mar=c(2.1,0.1,2.1,0.1))
axisPhylo()
mtext("a)",adj=0)
## add an extant tip ("t_extant") sister to taxon 't5'
## with divergence time of 4.5 Ma
node <- which(tree$tip.label=="t5")
tree <- bind.tip(tree, tip.label="t_extant",
  where=node, position=4.5)
# plot to see the result
plotTree(tree,mar=c(2.1,0.1,2.1,0.1))
axisPhylo()
mtext("b)",adj=0)
## add an extinct tip ("t_extinct") sister to 't2' with
## divergence time of 7.8 Ma and duration (edge length) of
## 3.3 Ma
node <- which(tree$tip.label=="t2")
tree <- bind.tip(tree, tip.label="t_extinct", where=node,
  position=7.8, edge.length=3.3)
## plot to see the result
plotTree(tree,mar=c(2.1,0.1,2.1,0.1))
axisPhylo()
mtext("c)",adj=0)
par(mar=c(5.1,4.1,4.1,2.1),mfrow=c(1,1))

Binds two trees of class "simmap"

Description

This function grafts tree y onto tree x at node where.

Usage

bind.tree.simmap(x, y, where="root")

Arguments

x

an object of class "simmap". (The receptor tree.)
y

an object of class "simmap". (The tree being grafted.)
where

node number to attach new tip, or the root node if where="root".

Details

This function wraps around bind.tree for objects of class "simmap"; however it presently only allows y to be grafted at a node of x and it does not allow y to possess a root edge.

Value

An object of class "simmap".

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Simulates and visualizes discrete-time Brownian evolution on a phylogeny

Description

Conducts a discrete-time Brownian motion simulation on an input tree, plots the outcome, and returns the tip and internal node states to the user as a named vector.

Usage

bmPlot(tree, type="BM", anc=0, sig2=1/1000, ngen=1000, ...)

Arguments

tree

a phylogenetic tree in "phylo" format.
type

the type of plot to create. See Description.
anc

the ancestral value for the root node.
sig2

the BM rate (variance of the Brownian evolution process), σ2\sigma^2.
ngen

number of generations for the simulation: will rescale the tree to this total length.
...

arguments to be passed to different methods.

Details

The function will first rescale and round the branch lengths to integer length, if they are not already in integer values. If integer branch lengths are provided, the user should also set ngen to be equal to the total height of the tree in generations (and thus avoid rescaling).

For type="threshold" the visualization is of the threshold model (Felsenstein 2012), in which the evolving character is liability and the segments of evolution are colored by their value for the threshold trait. If type="threshold" is used, the function requires at least one addition input: thresholds, a vector containing the ordered thresholds between states. The user can also provide the colors for plotting in colors. Note that one more color than threshold should be provided as one threshold implies two states; two thresholds, three states; etc. If no value for colors is provided, the function will recycle a set of four colors up to the number of times required by thresholds. Finally, the optional argument return.tree=TRUE will tell the function to return a list with the tip and note states and an object of class "phylo" with (for type="threshold"), the state for the threshold model through time mapped on the branches of the tree in discrete time.

Value

This function conducts and plots discrete time Brownian simulation and returns a vector containing the simulated states at internal nodes and tips of the tree.

It also returns, by default (although this can be turned off) a tree with the branch lengths in discrete time and with a mapped discrete character (for type="threshold").

Author(s)

Liam Revell [email protected]

References

Felsenstein, J. (2012) A comparative method for both discrete and continuous characters using the threshold model. American Naturalist, 179, 145-156.

Revell, L. J. (2014) Ancestral character estimation under the threshold model from quantitative genetics. Evolution, 68, 743-759.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

fastBM, pbtree, phenogram, threshBayes

Examples

set.seed(999)
## plot BM simulation on 12 taxon tree
tree<-pbtree(n=12)
par(mfrow=c(1,2),mar=c(5.1,4.1,4.1,0.1))
x<-bmPlot(tree,bty="l")
plotTree(tree,direction="upwards",
    mar=c(5.1,0.1,4.1,1.1),ftype="off")
## reset par to default values
par(mfrow=c(1,1),mar=c(5.1,4.1,4.1,2.1))
## plot simulation of a threshold character
par(mfrow=c(1,2),mar=c(5.1,4.1,4.1,0.1))
tt<-bmPlot(tree,type="threshold",thresholds=c(0,1,2),
    bty="l")
plot(tt$tree,direction="upwards",
    mar=c(5.1,0.1,4.1,1.1),ftype="off",
    colors=setNames(c("black","red","blue"),
    letters[1:3]),lwd=3)
## reset par to default values
par(mfrow=c(1,1),mar=c(5.1,4.1,4.1,2.1))

Fits bounded and wrapped Brownian motion models

Description

Fits a bounded Brownian motion model using the discrete approximation of Boucher & Demery (2016).

Usage

bounded_bm(tree, x, lims=NULL, ...)

Arguments

tree

object of class "phylo".
x

continuous character data in a vector.
lims

bounds. If NULL will be set to three times the observed range of the trait. (This is designed to be an effectively "unbounded" null model.)
...

optional arguments.

Details

Optional arguments.

Value

An object of class "bounded_bm".

Author(s)

Liam Revell [email protected]

References

Boucher, F. C., and V. Demery (2016) Inferring bounded evolution in phenotypic characters from phylogenetic comparative data. Systematic Biology, 65, 651-661.

Juhn, M., K. Martinet, F. Boucher, A. Schultz, L. Harmon, K. Burns, and M. Alfaro (In review) A wrapped Brownian motion model for the evolution of color.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

fitMk, fitmultiBM, fitThresh

Animation of branching random diffusion

Description

This function creates an animation of branching random diffusion (i.e., Brownian motion evolution with speciation).

Usage

branching.diffusion(sig2=1, b=0.0023, time.stop=1000, ylim=NULL, 
   smooth=TRUE, pause=0.02, record=NULL, path=NULL, ...)

Arguments

sig2

variance of BM process, σ2\sigma^2.
b

birthrate for branching process.
time.stop

number of generations to run.
ylim

y limits (for plotting).
smooth

no longer used.
pause

pause (in s) between generations.
record

filename for video file output (no video if NULL).
path

full path to file for video rendering. (By default branching.diffusion will look for the executable ffmpeg.exe in the directory C:/Program Files/ffmpeg/bin, even though this will not make sense on non-Windows machines.)
...

optional arguments.

Details

For animation to be recorded to file, the function requires the package animation as well as a video renderer.

Value

An animated plot and (optionally) a recorded video file.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

bmPlot, fastBM

Likelihood test for rate variation in a continuous trait

Description

Fits a multi-rate Brownian motion evolution model using maximum likelihood.

Usage

brownie.lite(tree, x, maxit=2000, test="chisq", nsim=100, se=NULL, ...)

Arguments

tree

a phylogenetic tree either as an object of class "phylo" or "simmap". (See read.simmap, make.simmap, or paintSubTree for more details about the latter object class.)
x

a vector of tip values for species. names(x) should be the species names.
maxit

an optional integer value indicating the maximum number of iterations for optimization - may need to be increased for large trees.
test

an optional string indicating the method for hypothesis testing - options are "chisq" or "simulation".
nsim

number of simulations (only used if test="simulation").
se

a vector containing the standard errors for each estimated mean in x.
...

optional arguments.

Details

This function takes an object of class "phylo" or class "simmap" with a mapped binary or multi-state trait (see read.simmap) and data for a single continuously valued character. It then fits the Brownian rate variation ("noncensored") model of O'Meara et al. (2006; Evolution). This is also the basic model implemented in Brian O'Meara's Brownie software.

Sampling error in the estimation of species means can also be accounted for by assigning the vector se with the species specific sampling errors for x.

Value

An object of class "brownie.lite" containing the following elements:

sig2.single

is the rate, σ2\sigma^2, for a single-rate model. This is usually the "null" model.
a.single

is the estimated state at the root node for the single rate model.
var.single

variance on the single rate estimator - obtained from the Hessian.
logL1

log-likelihood of the single-rate model.
k1

number of parameters in the single rate model (always 2).
sig2.multiple

is a length p (for p rates) vector of BM rates (σ12\sigma_1^2, σ22\sigma_2^2, and so on) from the multi-rate model.
a.multiple

is the estimated state at the root node for the multi-rate model.
var.multiple

p x p variance-covariance matrix for the p rates - the square-roots of the diagonals should give the standard error for each rate.
logL.multiple

log-likelihood of the multi-rate model.
k2

number of parameters in the multi-rate model (p+1).
P.chisq

P-value for a likelihood ratio test against the χ2\chi^2 distribution; or
P.sim

P-value for a likelihood ratio test against a simulated null distribution.
convergence

logical value indicating if the likelihood optimization converged.

Author(s)

Liam Revell [email protected]

References

O'Meara, B. C., C. Ane, M. J. Sanderson, and P. C. Wainwright (2006) Testing for different rates of continuous trait evolution using likelihood. Evolution, 60, 922-933.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

brownieREML, evol.vcv, ratebytree

Examples

## load data from Revell & Collar (2009)
data(sunfish.tree)
data(sunfish.data)
## extract character of interest
buccal.length<-setNames(sunfish.data$buccal.length,
    rownames(sunfish.data))
## fit model
multiBM.fit<-brownie.lite(sunfish.tree,
    buccal.length)
print(multiBM.fit)

REML version of brownie.lite

Description

Fits a multi-rate Brownian motion evolution model using REML. (See brownie.lite for more details.)

Usage

brownieREML(tree, x, maxit=2000, ...)

Arguments

tree

an object of class "phylo" or "simmap". (See read.simmap and make.simmap for more information about the latter object class.)
x

a vector of tip values for species. names(x) should be the species names.
maxit

an optional integer value indicating the maximum number of iterations for optimization - may need to be increased for large trees.
...

optional arguments.

Details

This function takes an object of class "phylo" or an object of class "simmap" with a mapped binary or multi-state trait (see read.simmap) and data for a single continuously valued character. It then uses restricted maximum likelihood (REML) to fit the Brownian rate variation ("noncensored") model of O'Meara et al. (2006; Evolution). This function is similar to brownie.lite but uses REML (which is faster and unbiased) instead of ML. REML optimization takes advantage of Felsenstein's (1985) contrasts algorithm.

Value

An object of class "brownieREML" containing the following components:

sig2.single

is the rate, σ2\sigma^2, for a single rate model - this is usually the "null" model.
logL1

log-likelihood of the single-rate model.
sig2.multiple

is a length p (for p rates) vector of BM rates (σ12\sigma_1^2, σ22\sigma_2^2, and so on) from the multi-rate model.
logL2

log-likelihood of the multi-rate model.
convergence

numerical value from optim.

Author(s)

Liam Revell [email protected]

References

Felsenstein, J. (1985) Phylogenies and the comparative method. American Naturalist, 125, 1-15.

O'Meara, B. C., C. Ane, M. J. Sanderson, and P. C. Wainwright (2006) Testing for different rates of continuous trait evolution using likelihood. Evolution, 60, 922-933.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

brownie.lite, evol.vcv, evol.rate.mcmc, ratebytree

Examples

## load data from Revell & Collar (2009)
data(sunfish.tree)
data(sunfish.data)
## extract character of interest
gape.width<-setNames(sunfish.data$gape.width,
    rownames(sunfish.data))
## fit model
multiBM.reml<-brownieREML(sunfish.tree,
	gape.width)
print(multiBM.reml)

Add labels to subtrees of a plotted phylogeny

Description

This function adds clade labels to a plotted tree.

Usage

cladelabels(tree=NULL, text, node, offset=NULL, wing.length=NULL, cex=1,
   orientation="vertical")
arc.cladelabels(tree=NULL, text, node=NULL, ln.offset=1.02,
   lab.offset=1.06, cex=1, orientation="curved", stretch=1, ...)

Arguments

tree

an object of class "phylo". If not supplied, the function will obtain the last plotted phylogeny from the environmental variable last_plot.phylo.
text

desired clade label text.
node

node number for the most recent common ancestor of members of the clade. For arc.cladelabels this defaults to NULL which means that the node of the clade to be labeled should be specified interactively (that is, by clicking on the graphical device).
offset

offset (as a multiplier of character width) for the label. Defaults to offset=1 if tree is supplied or offset=8 otherwise.
wing.length

length of the wings to add to the top & bottom of the label bar (in character widths).
cex

character expansion factor.
orientation

orientation of the text. Can be orientation = "vertical" (the default) or "horizontal".
ln.offset

line offset (as a function of total tree height) for arc.cladelabels.
lab.offset

label offset for arc.cladelabels.
stretch

argument for arc.cladelabels to be passed to arctext.
...

optional arguments for arc.cladelabels.

Details

cladelabels presently works only for rightward facing plotted phylogenies - but no warning will be returned if your tree does not conform to this requirement!

arc.cladelabels is designed to do a similar thing to cladelabels, but for plotted fan trees. This function checks to ensure that the most recently plotted tree was plotted with type="fan" style.

Author(s)

Liam Revell [email protected]

References

Paradis, E., J. Claude, and K. Strimmer (2004) APE: Analyses of phylogenetics and evolution in R language. Bioinformatics, 20, 289-290.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

nodelabels

Collapse a subtree to a star phylogeny

Description

Collapses a subtree to a star.

Usage

collapse.to.star(tree, node)

Arguments

tree

an object of class "phylo".
node

node for the clade to be collapsed.

Details

If the tree has edge lengths, the function will keep the tips at the same height above the root as in the original tree.

If node is the global root of the tree a star phylogeny will be created.

Value

An object of class "phylo".

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

splitTree, starTree

Interactive tree visualizer

Description

Function creates an interactive visualization of collapsing & expanding clades on the tree.

Usage

collapseTree(tree, ...)

Arguments

tree

an object of class "phylo".
...

optional arguments. These mostly match the arguments of plotSimmap, but also include the argument drop.extinct=TRUE which will (if the input tree is ultrametric) drop any 'extinct' lineages from the tree that is returned by the function.

Details

Function first plots a fan style tree, and then the user collapses node on the tree by clicking on them. Collapsed nodes are collapsed to the common ancestor of the clade. Nodes that have been collapsed can also be expanded by clicking. Right-click (or select Finish button in RStudio) to end.

Note, for the animation to work probably when run in the RStudio IDE the "zoom" level should be set to 100%.

Value

Returns the final plotted tree.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

plotTree, plotSimmap

Examples

## Not run: 
data(liolaemid.tree)
pruned<-collapseTree(liolaemid.tree,fsize=0.5)
## End(Not run)

Compares two chronograms with precisely matching nodes in a visual manner

Description

Creates a visual comparison of two chronograms that differ in edge lengths but not topology.

Usage

compare.chronograms(t1, t2, ...)

Arguments

t1

object of class "phylo".
t2

object of class "phylo" that matches t1 precisely in topology & node rotations, but differs in edge lengths.
...

optional arguments.

Details

This function plots two trees, with semi-transparent colors by default, & uses arrows to highlight differences in depth of corresponding nodes between the trees.

Value

Function creates a plot.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Compute consensus edges for a tree under some criterion

Description

Computes consensus edge lengths from a set of input trees using multiple methods.

Usage

consensus.edges(trees, method=c("mean.edge","least.squares"), ...)

Arguments

trees

object of class "multiPhylo" in which the trees must have edge lengths. This could be, for instance, a sample from the posterior distribution of trees in a Bayesian analysis.
method

method for computing the edge lengths. Could be the mean of all trees in which the edge is present, or it could be the least-squares edge lengths computed on the mean patristic distance matrices from the input phylogenies in trees. Note that in the latter case the phangorn function nnls.tree is used and the option rooted will be set to is.rooted(tree) for the consensus tree.
...

optional arguments, the most popular of which is consensus.tree - a user supplied consensus tree. Another optional argument for method="mean.edge" is if.absent which tells the function how to include absent edges in the computation of average edge lengths. Possible values are "zero" (the default) or "ignore".

Value

An object of class "phylo" with edge lengths.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Map continuous trait evolution on the tree

Description

Projects the observed and reconstructed values of a continuous trait onto the edges of a tree using a color gradient.

Usage

contMap(tree, x, res=100, fsize=NULL, ftype=NULL, lwd=4, legend=NULL,
   lims=NULL, outline=TRUE, sig=3, type="phylogram", direction="rightwards", 
   plot=TRUE, ...)
## S3 method for class 'contMap'
plot(x, ...)
errorbar.contMap(obj, ...)

Arguments

tree

object of class "phylo".
x

a numerical vector of phenotypic trait values for species. names(x) should contain the species names and match tree$tip.label. Or, for plot.contMap, an object of class "contMap".
res

resolution for gradient plotting. Larger numbers (to a point) indicate a finer (smoother) gradient.
fsize

relative font size - can be a vector of length 2 in which the first element gives the font size for the tip labels & the second element giving the font size for the legend.
ftype

font type - see options in plotSimmap. As with fsize, this can be a vector with the second element giving font type for the legend.
lwd

line width for branches. Can be a single integer number or a vector. In the latter case, the second number will be taken to be the desired legend width.
legend

if FALSE no legend is plotted; if a numeric value, it gives the length of the legend in units of branch length. Default is 0.5 times the total tree length.
lims

range for the color map. By default, this will be c(min(x),max(x)), and should always include this range.
outline

logical value indicating whether or not to outline the branches of the tree in black.
sig

the number of decimal places to show on the legend limits.
type

type of plot desired. Options are "phylogram" for a rightward square phylogram; and "fan" for a circular phylogram.
direction

plotting direction for type="phylogram".
plot

logical value indicating whether or not to plot the tree. If plot=FALSE then an object of class "contMap" will be returned without plotting.
obj

object of class "contMap".
...

optional arguments for plot.contMap which include all the arguments of contMap except for tree, x, res, and lims. Also method, "fastAnc", "anc.ML", or "user" (for user-supplied states) specifying which function to use for ancestral state estimation; hold specifies whether or not to hold output to graphical device before plotting (defaults to hold=TRUE); and anc.states a vector containing some or multiple ancestral user-supplied ancestral states at nodes. Some other plotting arguments, such as xlim and ylim, may also work. Optional arguments for errorbar.contMap include x, a vector containing the original trait values mapped onto the tree (otherwise these will be obtained from obj), scale.by.ci, a logical argument (defaulting to TRUE) that determines whether or not the length of the error bars will be scaled by the CI width, and lwd, which determines the line width of the plotted error bars.

Details

Function plots a tree with a mapped continuous character.

The mapping is accomplished by estimating states at internal nodes using ML with fastAnc, and then interpolating the states along each edge using equation [2] of Felsenstein (1985). This makes these interpolated values equal to the maximum likelihood estimates under a Brownian evolutionary process.

The default color palette is not recommended as it is not colorblind friendly and does not render well into gray scale; however, this can be updated using the helper function setMap.

errorbar.contMap adds error bars to an existing plot.

Value

Plots a tree. An object of class "contMap" is returned invisibly.

errorbar.contMap adds colorful error bars to a plotted tree.

Author(s)

Liam Revell [email protected]

References

Felsenstein, J. (1985) Phylogenies and the comparative method. American Naturalist, 125, 1-15.

Revell, L. J. (2013) Two new graphical methods for mapping trait evolution on phylogenies. Methods in Ecology and Evolution, 4, 754-759.

Revell, L. J. (2014) Graphical methods for visualizing comparative data on phylogenies. Chapter 4 in Modern phylogenetic comparative methods and their application in evolutionary biology: Concepts and practice (L. Z. Garamszegi ed.), pp. 77-103.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Revell, L. J., K. Schliep, E. Valderrama, and J. E. Richardson (2018) Graphs in phylogenetic comparative analysis: Anscombe's quartet revisited. Methods in Ecology and Evolution, 9, 2145-2154.

See Also

anc.ML, densityMap, fastAnc, plotSimmap

Examples

## load data from Garland et al. (1992)
data(mammal.tree)
data(mammal.data)
## extract character of interest
ln.bodyMass<-log(setNames(mammal.data$bodyMass,
    rownames(mammal.data)))
## create "contMap" object
mammal.contMap<-contMap(mammal.tree,
    ln.bodyMass,plot=FALSE,res=200)
## change color scheme
mammal.contMap<-setMap(mammal.contMap,
    c("white","#FFFFB2","#FECC5C","#FD8D3C",
    "#E31A1C"))
plot(mammal.contMap,fsize=c(0.7,0.8),
    leg.txt="log(body mass)")
par(mar=c(5.1,4.1,4.1,2.1)) ## reset margins to default

Creates a co-phylogenetic plot

Description

Visualize co-phylogenetic trees by multiple methods.

Usage

cophylo(tr1, tr2, assoc=NULL, rotate=TRUE, ...)
## S3 method for class 'cophylo'
plot(x, ...)
cotangleplot(tr1, tr2, type=c("cladogram","phylogram"),
   use.edge.length=TRUE, tangle=c("both","tree1","tree2"), ...)

Arguments

tr1

object of class "phylo".
tr2

object of class "phylo".
assoc

matrix containing the tip labels in tr1 to match to the tip labels in tr2. Note that not all labels in either tree need to be included; and, furthermore, one label in tr1 can be matched with more than one label in tr2, or vice versa.
rotate

logical argument indicating whether nodes on both trees should be rotated to attempt to match in vertical position.
x

in the case of plot.cophylo, an object of class "cophylo" to be plotted.
type

for cotangleplot, the tree plotting style.
use.edge.length

for cotangleplot, a logical value indicating whether or not to plot trees with edge lengths.
tangle

for cotangleplot, whether to tangle the left tree, the right tree, or both.
...

optional arguments to be passed to tipRotate, or, in the case of plot.cophylo, to the internally used tree plotting function, phylogram. phylogram takes similar arguments to plotSimmap, such as fsize, ftype, lwd, and pts, though not all options from plotSimmap and plotTree are available. If fsize is supplied as a vector, different size fonts for the left & right facing trees may be used. In addition, the optional argument scale.bar, which should be a vector containing the lengths of the scale bars desired for the right & left trees, will add scale bars to the plot when supplied to plot.cophylo. If either tree contains polytomies, the cophylo argument rotate.multi should be set to TRUE. If curved linking lines are desired, the plot.cophylo argument link.type should be set to "curved". Other arguments for the plot method include link.col, link.lty, and link.lwd, which can be supplied as a scalar or a vector in which the order of the elements corresponds to the order of the associations in assoc. Finally, edge.col, a list consisting of two vectors (left and right) can be used to specify the edge colors of the two left & right plotted trees. Note that the edge order is the same as in the rotated trees, assuming that a rotation has been performed on x.

Details

cophylo an object of class "cophylo" or, in the case of plot.cophylo, plots that object. The function can (optionally) first attempt to rotate the nodes of both trees to optimize vertical matching of tips.

If no matrix of associations, assoc, is provided, then cophylo will look for exact matches of tip labels between trees.

cotangleplot creates a co-phylogenetic plot in which the edges of the matched trees are crossing and is designed to be used only on phylogenies with matching tip labels.

Value

An object of class "cophylo" which includes the following components or a pair of plotted facing phylogenies with links between tips as specified in assoc.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

cophyloplot, plotSimmap

Examples

## load data from Lopez-Vaamonde et al. (2001)
data(wasp.trees)
data(wasp.data)
## create co-phylogenetic object
wasp.cophylo<-cophylo(wasp.trees[[1]],wasp.trees[[2]],
    assoc=wasp.data)
## plot co-phylogenies
plot(wasp.cophylo,link.type="curved",link.lwd=4,
     link.lty="solid",link.col=make.transparent("red",
     0.25))
par(mar=c(5.1,4.1,4.1,2.1))

Conducts a statistical test of cospeciation between two trees

Description

Test for cospeciation based on tree distance.

Usage

cospeciation(t1, t2, distance=c("RF","SPR"),
   method=c("simulation","permutation"), assoc=NULL,
   nsim=100, ...)
## S3 method for class 'cospeciation'
plot(x, ...)
## S3 method for class 'cospeciation'
print(x, ...)

Arguments

t1

object of class "phylo".
t2

object of class "phylo".
distance

distance method to compare trees.
method

method to use (simulation of pure-birth trees, or permutation of tip labels on a fixed tree) to obtain a null distribution of tree distances via distance.
assoc

matrix containing the tip labels in t1 to match to the tip labels in t2. Note that not all labels in either tree need to be included; however, unlike cophylo, one label in t1 cannot be matched with more than one label in t2, nor vice versa. If NULL then an exact match of tip labels will be sought.
nsim

number of simulations or permutations.
x

for plot and print methods, an object of class "cospeciation".
...

optional arguments.

Details

This function conducts a test for cospeciation based on tree distance, applying a distance metric selected by the user.

Note that this method should be prone to be quite liberal as the null hypothesis is no similarity whatsoever between the two trees!

Value

An object of class "cospeciation", which includes the test-statistic, the null distribution, and a p-value for the test of the null hypothesis of no topological similarity between the two trees.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

cophylo

Examples

## load data from Lopez-Vaamonde et al. (2001)
data(wasp.trees)
data(wasp.data)
## test for cospeciation
wasp.cosp<-cospeciation(wasp.trees[[1]],wasp.trees[[2]],
    assoc=wasp.data)
print(wasp.cosp)
plot(wasp.cosp)
title(main=paste("Simulated distribution of RF distances\n",
    "between unassociated trees"),font.main=3)

Counts the number of character changes on a object of class "simmap" or "multiSimmap"

Description

Count the number of changes of different types on a stochastically mapped trees or set of trees (objects of class "simmap" or "multiSimmap").

Usage

countSimmap(tree, states=NULL, message=TRUE)

Arguments

tree

an object of class "simmap" or "multiSimmap".
states

optional argument with the states for the mapped character. If not provided, these will be computed from the tree. This is useful if averaging across many trees, some of which may lack certain states.
message

optional logical argument indicating whether or not to return an informative message about the function output.

Details

This function takes a tree or a set of trees with a mapped discrete character (that is, an object of class "simmap" or "multiSimmap"), and computes the total number of character changes as well as the number of character changes between all states.

Value

A list with up to three elements: N is an integer value giving the total number of character changes on the tree; Tr gives the number of of transitions between row and column states (or a matrix containing both N and the transitions between states, in rows, for an object of class "multiPhylo"); and (optionally) message contains an explanatory message about the function output.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Examples

## load data from Revell & Collar (2009)
data(anoletree)
anoletree
countSimmap(anoletree)

Generates (or simulates) a 'changes through time' plot from a set of stochastic map character histories

Description

Create a 'changes through time' plot from a "multiSimmap" object.

Usage

ctt(trees, segments=20, ...)
sim.ctt(tree, Q, anc=NULL, nmaps=100, ...)
sim.multiCtt(tree, Q, anc=NULL, nmaps=100, nsim=100, ...)

Arguments

trees

an object of class "multiSimmap".
segments

number of segments to break up the history of the tree.
tree

for sim.ctt, an object of class "phylo".
Q

for sim.ctt, a transition matrix to use for simulation.
anc

ancestral state at the root node for simulation.
nmaps

number of stochastic maps per simulation.
nsim

for sim.multiCtt only, the number of simulations to run.
...

optional arguments.

Details

This function generates a 'changes through time' plot in the style of a lineage-through-time (LTT) plot. It shows the mean rate or the mean number of changes per unit time from a set of stochastic character map trees.

Value

An object of class "ctt" or "multiCtt".

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

ltt

Computes a posterior distribution for the number and types of changes on the tree

Description

S3 methods to summarize the results of one or more stochastic maps.

Usage

## S3 method for class 'multiSimmap'
density(x, ...)
## S3 method for class 'changesMap'
plot(x, ...)

Arguments

x

object of class "multiSimmap" (see make.simmap), or, in the case plot.changesMap, an object of class "changesMap" produced via a call to density.multiSimmap.
...

optional arguments. For density.multiSimmap these consist of bw (bandwidth) & method ("changes", "densityMap", or "timings").

Details

density.multiSimmap method="changes" (the default) results in a posterior distribution of the number & types of changes on the tree.

If the package coda has been installed, then the function HPD.interval is used to compute a 95% high probability density interval for the number of changes of each type on the tree. Otherwise, the central 95% of the posterior sample is returned as an estimate of the 95% HPD interval for each change type.

The method also computes the full posterior density for each change type using a bandwidth specified by the user.

method="densityMap" computes a standard "densityMap" object, and thus only permits binary characters.

plot.changesMap plots the posterior density returned by density.multiSimmap for method= "changes".

Value

For method="changes" density.multiSimmap returns an object of class "changesMap".

For method="densityMap" density.multiSimmap returns an object of class "densityMap".

plot.changesMap generates a plot.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Plot posterior density of stochastic mapping on a tree

Description

Visualize posterior probability density from stochastic mapping using a color gradient on the tree.

Usage

densityMap(trees, res=100, fsize=NULL, ftype=NULL, lwd=3, check=FALSE,
   legend=NULL, outline=FALSE, type="phylogram", direction="rightwards",
   plot=TRUE, ...)
## S3 method for class 'densityMap'
plot(x, ...)

Arguments

trees

set of phylogenetic trees in a modified "multiPhylo" object. Values for a two-state discrete character are mapped on the tree. See make.simmap and read.simmap for details.
res

resolution for gradient plotting. Larger numbers indicate a finer (smoother) gradient.
fsize

relative font size - can be a vector with the second element giving the font size for the legend.
ftype

font type - see options in plotSimmap. As with fsize, can be a vector with the second element giving font type for the legend.
lwd

line width for branches. If a vector of two elements is supplied, the second element will be taken to be the desired width of the legend bar.
check

check to make sure that the topology and branch lengths of all phylogenies in trees are equal.
legend

if FALSE no legend is plotted; if a numeric value, it gives the length of the legend in units of branch length. Default is 0.5 times the total tree length.
outline

logical value indicating whether or not to outline the branches of the tree in black.
type

type of plot desired. Options are "phylogram" for a rightward square phylogram; and "fan" for a circular phylogram.
plot

logical value indicating whether or not to plot the tree. If plot=FALSE then an object of class "densityMap" will be returned without plotting.
direction

plotting direction for type="phylogram".
x

for plot.densityMap, an object of class "densityMap".
...

optional arguments for plot.densityMap. These include all the arguments of densityMap except trees and res. Additional optional arguments include mar (margins), offset (tip label offset: in units of the edge length or character widths, as in plotSimmap), and hold (whether or not to use dev.hold to hold output to graphical device before plotting; defaults to hold=TRUE). Also, the argument states can be used to 'order' the states on the probability axis (that is, which state should correspond to a posterior probability of 0 or 1). Some other plotting arguments, such as xlim and ylim, may also work.

Details

Function plots a tree with the posterior density for a mapped character from stochastic character mapping on the tree. Since the mapped value is the probability of being in state "1", only binary [0,1] characters are allowed.

Value

Plots a tree and returns an object of class "densityMap" invisibly.

Author(s)

Liam Revell [email protected]

References

Bollback, J. P. (2006) Stochastic character mapping of discrete traits on phylogenies. BMC Bioinformatics, 7, 88.

Huelsenbeck, J. P., R. Neilsen, and J. P. Bollback (2003) Stochastic mapping of morphological characters. Systematic Biology, 52, 131-138.

Revell, L. J. (2013) Two new graphical methods for mapping trait evolution on phylogenies. Methods in Ecology and Evolution, 4, 754-759.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

make.simmap, plotSimmap, read.simmap

Examples

## Not run: 
## load tree and data from Revell & Collar (2009)
data(sunfish.tree)
data(sunfish.data)
## extract discrete character (feeding mode)
fmode<-setNames(sunfish.data$feeding.mode,
     rownames(sunfish.data))
## do stochastic mapping
smap.trees<-make.simmap(sunfish.tree,fmode,model="ER",
     nsim=100)
## compute "densityMap" object
sunfish.dmap<-densityMap(smap.trees,plot=FALSE,
	res=50) ## res should be higher
## plot density map
plot(sunfish.dmap,lwd=5,outline=TRUE)
par(mar=c(5.1,4.1,4.1,2.1)) ## reset margins to default
## End(Not run)

Plots a posterior sample of trees

Description

Functions plots a posterior sample of trees, including with mapped discrete characters.

make.transparent is used internally and converts a color to transparent with a certain user-specified alpha level.

Usage

densityTree(trees, colors="blue", alpha=NULL, method="plotTree", 
   fix.depth=FALSE, use.edge.length=TRUE, compute.consensus=TRUE, 
   use.gradient=FALSE, show.axis=TRUE, ...)
make.transparent(color, alpha)

Arguments

trees

an object of class "multiPhylo" or "multiSimmap".
colors

a color or a named vector of colors in which names correspond to mapped states in an object of class "multiSimmap".
alpha

transparency level for plotted trees which is passed to internally used function, make.transparent. (0 is fully transparent, which 1 is fully opaque.) By default will be one divided by the number of trees.
method

plotting method to be used internally. Can be "plotTree" or "plotSimmap".
fix.depth

logical value indicating whether or not to plot trees with a fixed depth or to permit plotted trees to have different depths.
use.edge.length

logical value indicating whether to use the edge lengths of the input tree. Defaults to use.edge.length=TRUE unless any input tree edge lengths are NULL.
compute.consensus

logical value indicating whether or not to use the tip order from a consensus tree. (Defaults to compute.consensus=TRUE Defaulted to FALSE in earlier version of this function.)
use.gradient

logical value indicating whether to plot all trees slightly offset using a rainbow color gradient. (Defaults to use.gradient=FALSE.)
show.axis

logical value indicating whether or not to include a horizontal axis in the plot.
...

arguments to be passed to plotTree or plotSimmap. Some may be ignored if they are incompatible with the method.
color

in make.transparent, the color (or colors in a vector) to render transparent.

Value

Function creates a plot.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Summarizes a stochastic mapped tree or set of trees

Description

Summarizes the result of one or more stochastic maps.

Usage

describe.simmap(tree, ...)
## S3 method for class 'simmap'
summary(object, ...)
## S3 method for class 'multiSimmap'
summary(object, ...)
## S3 method for class 'describe.simmap'
plot(x, ...)

Arguments

tree

a single tree or a set of trees as an object of class "simmap" or "multiSimmap", respectively.
object

object of class "simmap" or "multiSimmap".
x

for S3 plot method, an object of class "describe.simmap".
...

optional arguments which include: plot, a logical value indicating whether or not to plot the posterior probabilities at nodes (default is plot=FALSE); check.equal, a logical value indicating whether or not to check if all trees are equal using all.equal.phylo (default is check.equal=FALSE); and message, a logical indicating whether or not to print an informative message to the screen (default is message=TRUE).

Value

An object of class "describe.simmap" with the following elements:

count

a matrix containing the number and types of transitions for each tree, if tree is an object of class "multiSimmap".
times

a matrix containing the times spend in each state on each tree.
ace

the posterior probabilities of each node being in each state, if tree is an object of class "multiSimmap".
legend

a vector containing the plot legend, if plot=TRUE.

if class(tree)="simmap" then the function simply returns the results of countSimmap combined with the states at each node of the tree and a matrix containing the total and relative times spent in each state on the tree.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Collapse or resolve polytomies in a tree with a character painted on the edges

Description

Collapses or resolves polytomies in special types of phylogenetic trees. (See di2multi and multi2di.)

Usage

## S3 method for class 'simmap'
di2multi(phy, ...)
## S3 method for class 'simmap'
multi2di(phy, ...)
## S3 method for class 'multiSimmap'
di2multi(phy, ...)
## S3 method for class 'multiSimmap'
multi2di(phy, ...)
## S3 method for class 'contMap'
di2multi(phy, ...)
## S3 method for class 'contMap'
multi2di(phy, ...)
## S3 method for class 'densityMap'
di2multi(phy, ...)
## S3 method for class 'densityMap'
multi2di(phy, ...)

Arguments

phy

object of class "simmap", "multiSimmap", "contMap", or "densityMap" containing a character mapped onto the edges of a tree or set of trees.
...

optional arguments: tol, length below which edges should be treated as having zero length; and random, specifying whether to resolve polytomies randomly (if TRUE) or in the order in which they are encountered.

Details

The method di2multi collapses branches of zero length (or, more specifically, branches with length shorter than tol) to create a polytomy in a tree or set of trees.

The method multi2di resolves polytomies by adding branches of zero length (while preserving the mappings) in a tree or set of trees.

This methods should theoretically behave similarly to di2multi and multi2di from the ape package.

Value

An object of class "simmap", "multiSimmap", "contMap", or "densityMap", depending on the class of phy.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

contMap, densityMap, di2multi, make.simmap, multi2di, read.simmap

Creates a phylogenetic dot plot

Description

Creates a plot in which different sized dots/circles represent different tip values for a quantitative trait.

Usage

dotTree(tree, x, legend=TRUE, method="plotTree", standardize=FALSE, ...)
dot.legend(x, y, min, max, Ntip, length=5, prompt=FALSE, method="plotTree", 
   ...)

Arguments

tree

an object of class "phylo".
x

vector of trait values; or a matrix. If x is a vector it must have names that correspond to the tip labels of tree. If x is a matrix (and it probably should be a matrix, not a data frame) then the row names of the matrix should correspond to the tip labels of the phylogeny. In the case of dot.legend, the x coordinate of the legend.
legend

logical value indicating whether or not a legend should be plotted.
method

tree plotting method to be used internally. Will switch to method="phylogram" if the number of traits is greater than one. For dot.legend, it should be the method that was used for the plot.
standardize

a logical value indicating whether or not to standardize x, or each column of x, to have a mean of zero & variance of one prior to analysis.
y

y coordinate of the legend.
min

minimum value for dot.legend.
max

maximum value for dot.legend.
Ntip

number of tips in the plotted tree for dot.legend.
length

length of legend.
prompt

logical value indicating whether or not to prompt for legend position.
...

optional arguments. In the case of dotTree, these will be passed to plotTree or a different internally used plotting function for method="phylogram". See phylo.heatmap for more detail on these arguments. Other option for dotTree also include data.type ("continuous" or "discrete"), colors, length, for data type "continuous" the length of the legend in terms of plotted circles, x.space, the spacing of the columns in the plotted data matrix, and leg.space, the spacing of the legend dots (again, for data.type="continuous" only).

Value

Function creates a plot.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Examples

## load data from Garland et al. (1992)
data(mammal.tree)
data(mammal.data)
## log-transform trait data
log.mammal<-log(mammal.data)
## plot dotTree
dotTree(mammal.tree,log.mammal,fsize=0.7,
    standardize=TRUE,length=10)
par(mar=c(5.1,4.1,4.1,2.1)) ## reset margins to default

Drop a clade from a tree

Description

Internal function for posterior.evolrate.

Usage

drop.clade(tree, tip)

Arguments

tree

object of class "phylo".
tip

set of tips in a clade.

Details

Function drops the clade containing the species in tip.

Probably should not use unless you know what you're doing.

Value

An object of class "phylo".

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Drop all the leaves (tips) from a tree

Description

Drops all the leaves from a tree, leaving behind only the structure leading to internal nodes.

Usage

drop.leaves(tree, ...)

Arguments

tree

object of class "phylo".
...

optional arguments. Presently includes only the logical value keep.tip.labels which tells the function how to labels the tips on the reduced tree.

Value

An object of class "phylo".

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Drop tip or tips from an object of class "contMap" or "densityMap"

Description

Drops one or multiple tips from an object of class "contMap" or "densityMap".

Usage

## S3 method for class 'contMap'
drop.tip(phy, tip, ...)
## S3 method for class 'densityMap'
drop.tip(phy, tip, ...)
## S3 method for class 'contMap'
keep.tip(phy, tip, ...)
## S3 method for class 'densityMap'
keep.tip(phy, tip, ...)

Arguments

phy

an object of class "contMap" or "densityMap".
tip

name or names of species to be dropped or kept.
...

optional arguments to be passed to drop.tip.simmap.

Details

These functions are equivalent to drop.tip and keep.tip in the ape package, but for objects of class "contMap" and "densityMap".

For more information about objects of class "contMap" or "densityMap", please refer to the documentation pages for contMap or densityMap, respectively.

Value

An object of class "contMap" or "densityMap".

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

contMap, densityMap, drop.tip, drop.tip.simmap, keep.tip

Drop or keep tip or tips from an object of class "multiSimmap"

Description

This function drops or keeps one or multiple tips from all the trees of an object of class "multiSimmap".

Usage

## S3 method for class 'multiSimmap'
drop.tip(phy, tip, ...)
## S3 method for class 'multiSimmap'
keep.tip(phy, tip, ...)

Arguments

phy

an object of class "multiSimmap".
tip

name or names of species to be dropped, in a vector.
...

optional arguments to be passed to drop.tip.simmap. Most optional arguments work, with the exception of interactive=TRUE which will return an error.

Details

Equivalent to drop.tip and keep.tip in ape.

This function merely wraps drop.tip.simmap.

Value

An object of class "multiSimmap".

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

drop.tip, drop.tip.multiPhylo, drop.tip.simmap

Drop tips or extract clade from tree with mapped discrete character

Description

This function drops one or multiple tips from an object of class "simmap".

Usage

## S3 method for class 'simmap'
drop.tip(phy, tip, ...)
## S3 method for class 'simmap'
keep.tip(phy, tip, ...)
extract.clade.simmap(tree, node)

Arguments

phy

an object of class "simmap".
tip

name or names of species to be dropped (or kept).
node

node number for the root node of the clade to be extracted.
...

optional arguments. Currently the logical argument untangle which if set to TRUE will call untangle before returning the "simmap" object to the user.
tree

for extract.clade.simmap, an object of class "simmap".

Details

Equivalent to drop.tip and keep.tip but for a tree with a mapped discrete character.

extract.clade.simmap is functionally equivalent to extract.clade but preserves discrete character mappings on the tree.

Following drop.tip in ape, the returned tree is always in "cladewise" order.

Value

A modified object of class "phylo" containing the elements maps and $mapped.edge with the time spent in each state along each edge of the tree.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

drop.tip, extract.clade, make.simmap, read.simmap, sim.history

Conducts correlational D-test from stochastic mapping

Description

Conducts the 'D-test' of Huelsenbeck et al. (2003).

Usage

Dtest(t1, t2, nsim=100, ...)

Arguments

t1

set of stochastic map trees (i.e., object of class "multiSimmap" for character 1. Note that t1 and t2 should be of the same length.
t2

set of stochastic map trees (i.e., object of class "multiSimmap" for character 2. Note that t1 and t2 should be of the same length.
nsim

number of simulations to use in the test.
...

arguments to be passed internally to make.simmap. Note that (for now) these must be the same for both t1 and t2 (that is to say, we are not able to assume different trait evolution models for each tree).

Details

Note that this function has been included without much testing, and so the user should be wary.

Value

An object of class "Dtest".

Author(s)

Liam Revell [email protected]

References

Huelsenbeck, J. P., R. Neilsen, and J. P. Bollback (2003) Stochastic mapping of morphological characters. Systematic Biology, 52, 131-138.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

make.simmap, map.overlap

Map continuous trait evolution on the tree

Description

Maps a discrete character onto the edges of the tree using variable edge widths.

Usage

edge.widthMap(tree, x, ...)
## S3 method for class 'edge.widthMap'
plot(x, max.width=0.9, legend="trait value", ...)

Arguments

tree

object of class "phylo".
x

a numerical vector of phenotypic trait values for species. names(x) should contain the species names and match tree$tip.label. Or, for plot.edge.widthMap, an object of class "edge.widthMap".
max.width

maximum edge width in plot units.
legend

label for the plot legend.
...

optional arguments - especially for the plot method. Perhaps the most important of these is min.width, which defaults to 0 but could probably be increased for many datasets and graphical devices. Other arguments are passed internally to plotTree.

Value

edge.widthMap returns an object of class "edge.widthMap".

plot.edge.widthMap can be used to plot this object.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

contMap, fastAnc

Examples

## load data from Garland et al. (1992)
data(mammal.tree)
data(mammal.data)
## extract character of interest
ln.bodyMass<-log(setNames(mammal.data$bodyMass,
    rownames(mammal.data)))
## create "edge.widthMap" object
mammal.ewMap<-edge.widthMap(mammal.tree,ln.bodyMass,
    min.width=0.05)
## plot it
plot(mammal.ewMap,legend="log(body mass)")
par(mar=c(5.1,4.1,4.1,2.1)) ## reset margins to default

Compute the relative frequencies of state changes along edges

Description

Computes the relative frequencies of character state changes along edges from a sample of stochastically mapped character histories.

Usage

edgeProbs(trees)

Arguments

trees

an object of class "multiSimmap" containing a sample of trees that are identical in topology & branch lengths with different stochastically mapped character histories.

Details

The function assumes that all trees in the sample differ only in their mapped histories & not at all in topology or branch lengths.

Note that edgeProbs only asks whether the starting and ending states of the edge differ in a particular way, and thus ignores multiple-hits along a single edge.

Value

The object that is returned is a matrix with the state changes & the relative frequency of each state change. Rows are in the order of the matrix edge for any of the mapped trees.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

plotSimmap

Estimate diversity at each node of the tree

Description

Estimates the lineage density at each node in the tree based on a biogeographic model (similar to Mahler et al. 2010).

Usage

estDiversity(tree, x, method=c("asr","simulation"), model="ER", ...)

Arguments

tree

is a phylogenetic tree in "phylo" format.
x

a vector containing the biogeographic area for each of the tip taxa.
method

method for reconstructing ancestral biogeography.
model

model for ancestral character estimation. In theory, any model from ace; however only symmetric models permitted for method="asr".
...

optional arguments. So far, this includes only nsim, the number of stochastic mappings to conduct using make.simmap for method="simulation".

Details

Two different methods are implemented in the current version.

For method="asr" the state at the current node, and at each position along each co-extant internal edge, is computed as the marginal (empirical Bayesian) ancestral state reconstruction using the re-rooting method of Yang (2006). The lineage density is then computed as the sum of the marginal reconstructions (posterior probabilities) times the summed marginal ancestral reconstructions across co-extant edges.

For method="simulation", stochastic character mapping is used to generate optional argument nsim stochastic maps of ancestral biogeography. Then the lineage density at each node is computed as the number of co-existing lineages with the same biogeography as the focal node, averaged across stochastic maps.

The importance of this distinction may depend on the degree to which reconstructions at internal nodes are independent, which relates to the distinction between marginal and joint reconstruction (e.g., see Yang 2006).

Value

A vector containing the estimated lineage density at each node

Author(s)

Liam Revell [email protected]

References

Mahler, D. L, L. J. Revell, R. E. Glor, and J. B. Losos. (2010) Ecological opportunity and the rate of morphological evolution in the diversification of Greater Antillean anoles. Evolution, 64, 2731-2745.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Yang, Z. (2006) Computational Molecular Evolution. Oxford University Press.

See Also

fitDiversityModel

Bayesian MCMC method for identifying exceptional phenotypic diversification in a phylogeny

Description

Estimates the phylogenetic location of a single rate shift on the tree using Bayesian MCMC (as described in Revell et al., 2012b).

Usage

evol.rate.mcmc(tree, x, ngen=10000, control=list(), ...)
## S3 method for class 'evol.rate.mcmc'
print(x, ...)
## S3 method for class 'evol.rate.mcmc'
summary(object, ...)
## S3 method for class 'summary.evol.rate.mcmc'
print(x, ...)
## S3 method for class 'summary.evol.rate.mcmc'
plot(x, ...)

Arguments

tree

an object of class "phylo" (a phylogenetic tree).
x

a vector of tip values for species in which names(x) contains the species names of tree, an object of class "evol.rate.mcmc", or (in the case of the S3 summary method) an object of class "summary.evol.rate.mcmc".
ngen

an integer value indicating the number of generations for the MCMC.
control

a list of control parameters containing the following elements: sig1: starting value for σ12\sigma_1^2; sig2: starting value for σ22\sigma_2^2; a: starting value for a; sd1: standard deviation for the normal proposal distribution for σ12\sigma_1^2; sd2: standard deviation for the normal proposal distribution for σ22\sigma_2^2; kloc: scaling parameter for tree move proposals - 1/λ1/\lambda for the reflected exponential distribution; sdlnr: standard deviation on the log-normal prior on σ12/σ22\sigma_1^2/\sigma_2^2; rand.shift: probability of proposing a random shift in the tree (improves mixing); print: print frequency for the MCMC; sample: sample frequency.
object

for the S3 summary method, an object of class "evol.rate.mcmc".
...

other optional arguments.

Details

This function takes a phylogenetic tree and data for a single continuously valued character and uses a Bayesian MCMC approach to identify the phylogenetic location of a shift in the evolutionary rate through time.

Default values of control are given in Revell et al. (2012b).

Value

An object of class "evol.rate.mcmc" consisting of at least the following elements:

mcmc

results from the MCMC run.
tips

list of tips in rate σ12\sigma_1^2 for each sampled generation of MCMC (to polarize the rate shift).

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Revell, L. J., D. L. Mahler, P. Peres-Neto, and B. D. Redelings (2012) A new method for identifying exceptional phenotypic diversification. Evolution, 66, 135-146.

See Also

anc.Bayes, brownie.lite, evol.vcv, minSplit, posterior.evolrate

Likelihood test for variation in the evolutionary variance-covariance matrix

Description

Fits a multi-regime multivariate Brownian motion model following Revell & Collar (2009).

Usage

evol.vcv(tree, X, maxit=2000, vars=FALSE, ...)

Arguments

tree

an object of class "simmap". If tree is an object of class "phylo" then a simple multivariate Brownian motion model will be fit to the data in X.
X

an n x m matrix of tip values for m continuously valued traits in n species - row names should be species names. If X is supplied as a data frame it will be coerced into a matrix without warning.
maxit

an optional integer value indicating the maximum number of iterations for optimization. This quantity may need to be increased for difficult optimizations.
vars

an optional logical value indicating whether or not to estimate the variances of the parameter estimates from the Hessian matrix.
...

optional arguments. The most important optional argument at this time is err_vcv which should contain a list of matrices of sampling variances and covariances for (and between) the means of each species. The sampling variance for the mean is just the square of the sampling error. Sampling covariances will tend to be zero (or close to zero) if error for different traits is uncorrelated, for instance, because different specimens were used to estimate the means for different traits, and non-zero otherwise.

Details

The function takes an object of class "simmap" with a mapped binary or multi-state trait and data for an arbitrary number of continuously valued character. It then fits the multiple evolutionary variance-covariance matrix (rate matrix) model of Revell & Collar (2009; Evolution).

evol.vcv performs optimization by maximizing the likelihood with respect to the Cholesky matrices using optim. Optimization is by method="Nelder-Mead". Using box constraints does not make sense here as they would be applied to the Cholesky matrix rather than the target parameters. Users may have to increase maxit for large trees and/or more than two traits.

Value

An object of class "evol.vcv" with the following elements:

R.single

vcv matrix for the single rate matrix model.
vars.single

optionally, a matrix containing the variances of the elements of R.single.
logL1

log-likelihood for single matrix model.
k1

number of parameters in the single matrix model.
R.multiple

m x m x p array containing the p estimated vcv matrices for the p regimes painted on the tree.
vars.multiple

optionally, an array containing the variances of the parameter estimates in R.multiple.
logL.multiple

log-likelihood of the multi-matrix model.
k2

number of parameters estimated in this model.
P.chisq

P-value of the χ2\chi^2 test on the likelihood ratio.
convergence

logical value indicating whether or not the optimization has converged.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Revell, L. J., and D. C. Collar (2009) Phylogenetic analysis of the evolutionary correlation using likelihood. Evolution, 63, 1090-1100.

See Also

evol.rate.mcmc, brownie.lite

Examples

## load data from Revell & Collar (2009)
data(sunfish.tree)
data(sunfish.data)
## fit multi-correlation model
sunfish.fit<-evol.vcv(sunfish.tree,sunfish.data[,2:3])
print(sunfish.fit)

Likelihood test for a shift in the evolutionary correlation between traits

Description

Fits a multi-regime model for differences in the evolutionary variance-covariance structure or correlation between two continuous traits, following Revell & Collar (2009) and Revell et al. (2022).

Usage

evolvcv.lite(tree, X, maxit=2000, tol=1e-10, ...)

Arguments

tree

an object of class "simmap". If tree is an object of class "phylo" then a simple multivariate Brownian motion model will be fit to the data in X.
X

an n x m matrix of tip values for m continuously valued traits in n species - row names should be species names. If X is supplied as a data frame it will be coerced into a matrix without warning.
maxit

an optional integer value indicating the maximum number of iterations for optimization - may need to be increased for large trees.
tol

tolerance value for "L-BFGS-B" optimization.
...

other optional arguments. The most important optional argument is probably models which species the models to be fit. See Description for more information. A second useful argument is err_vcv which should be supplied as a list of matrices of sampling variances and covariances for (and between) the means of each species. The sampling variance for the mean is just the square of the sampling error. Sampling covariances will tend to be zero (or close to zero) if error for different traits is uncorrelated, for instance, because different specimens were used to estimate the means for different traits, and non-zero otherwise.

Details

This function takes an object of class "simmap" with a mapped binary or multi-state trait and data for two and only two continuously valued character. It then fits (by default) four different evolutionary models: common rates and correlation; different rates, common correlation; different correlations, common rates; no common structure.

In addition to the four default models specified above, evolvcv.lite now fits an additional four additional models.

The set of models to be fit can be specified using the optional argument models in multiple ways.

First, if left unspecified, then the four models listed above will be fit.

Second, if models is set to "all models" than eight models will be fit.

Lastly, one or more (up to all eight) models can be fit by encoding the models to be fit into a single vector containing a subset or all of the following elements: "1", "2", "2b", "3", "3b", "3c", and "4". These codes correspond to the following eight models: 1. common rates, common correlation; 2. different rates, common correlation; 2b. different rates for trait 1 only, common correlation; 2c. different rates for trait 2 only, common correlation; 3. common rates, different correlations; 3b. different rates for trait 1 only, different correlations; 3c. different rates for trait 2 only, different correlation; and 4. no common structure.

Value

A list with the results summarized for each model.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Revell, L. J., and D. C. Collar (2009) Phylogenetic analysis of the evolutionary correlation using likelihood. Evolution, 63, 1090-1100.

Revell, L. J., K. S. Toyama, and D. L. Mahler (2022) A simple hierarchical model for heterogeneity in the evolutionary correlation on a phylogenetic tree. PeerJ, 10, e13910.

See Also

brownie.lite, evol.vcv

Examples

## load data from Revell & Collar (2009)
data(sunfish.tree)
data(sunfish.data)
## fit heirarchical common-structure models
sunfish.fit<-evolvcv.lite(sunfish.tree,
    sunfish.data[,2:3],models="all models")
## print fitted models
print(sunfish.fit)
## compare models
anova(sunfish.fit)

Exhaustive and branch & bound MP optimization

Description

This function does exhaustive and branch & bound MP searches.

Usage

exhaustiveMP(data, tree=NULL, method="branch.and.bound")

Arguments

data

is a phyDat (Schliep 2011) object containing DNA or other data.
tree

an optional input tree (used only with method="branch.and.bound").
method

an optional string indicating which method to use: "branch.and.bound", implementing a branch-and-bound search (obviously), or "exhaustive".

Details

Should probably not be used for more than about 8 species (and definitely not more than 10 species). Performs parsimony calculations using parsimony in the phangorn package (Schliep, 2011).

Value

A "phylo" or "multiPhylo" object that is the MP tree or set of MP trees. It also returns the parsimony scores in attr(trees,"pscore") or attr(trees[[i]],"pscore") for the ith tree.

Author(s)

Liam Revell [email protected]

References

Felsenstein, J. (2004) Inferring Phylogenies. Sinauer.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Schliep, K. P. (2011) phangorn: phylogenetic analysis in R. Bioinformatics, 27, 592-593.

See Also

mrp.supertree, optim.parsimony, pratchet

Expands (or contracts) the tip-spacing of a given clade or clades

Description

Modify the tip-spacing of a plotted tree.

Usage

expand.clade(tree, node, factor=5)
## S3 method for class 'expand.clade'
plot(x, ...)

Arguments

tree

tree an object of class "phylo" or "simmap".
node

node index or vector of node indices.
factor

expansion factor for the tip-spacing of the taxa descended from node or nodes in node.
x

for plot method, an object of class "expand.clade".
...

optional arguments to be passed to plotTree or plotSimmap, depending on the class of x$tree.

Details

The purpose of this function is to compute a custom tip-spacing for users who want to expand or contract the tip-spacing of the descendant taxa from a given node or nodes.

Value

The function returns an object of class "expand.clade" which consists of the (possibly re-ordered) tree and a numerical vector with the calculated tip spacing based on the expansion factor specified by the user.

This object can be plotted using the S3 plot method for the object class; or it can be plotted simply by calling a standard plotting function on the tree & tip spacings.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Export trees & data in XML format

Description

Exports trees & character data in XML format.

Usage

export.as.xml(file, trees, X)

Arguments

file

filename for export.
trees

a phylogenetic tree or trees in "phylo" or "multiPhylo" format.
X

a matrix of class "DNAbin" or a matrix with discretely valued non-DNA character data.

Details

Can be used to create input file for the program SIMMAP v1.5 (Bollback 2006).

Value

A file.

Author(s)

Liam Revell [email protected]

References

Bollback, J. P. (2006) Stochastic character mapping of discrete traits on phylogenies. BMC Bioinformatics, 7, 88.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

make.simmap, read.nexus, read.simmap, write.simmap

Plots special types of phylogenetic trees

Description

Plots phylogenies (or phylogenetic trees and comparative data) in a variety of different styles.

Usage

fancyTree(tree, type=c("extinction","traitgram3d","droptip","densitymap",
   "contmap","phenogram95","scattergram"), ..., control=list())
phyloScattergram(tree, X=NULL, ...)
phenogram95(tree, x=NULL, ...)

Arguments

tree

an object of class "phylo".
type

the type of special plot to create. See Description.
...

arguments to be passed to different methods. See Description.
control

a list of control parameters, depending on type.
X

in phyloScattergram, a matrix of continuous trait values. Row names in the matrix should correspond to species names in the tree.
x

in phenogram95, a named vector with values for a continuously distributed trait.

Details

This function plots a phylogeny or phylogenetic tree and comparative data in a variety of different styles, depending on the value of type. In some instances, fancyTree is now just a wrappe for other phytools functions, such as contMap and densityMap.

If type="extinction" (or any unambiguous abbreviation) the function will plot a tree in which branches preceding the MRCA of all extant taxa and branches leading only to extinct lineages are plotted with dashed red lines.

If type="traitgram3d" the function will plot a three dimensional traitgram (that is, a projection of the tree into three dimensional morphospace where two dimensions are the phenotypic trait and the third axis is time since the root). In this case, the additional argument X, a matrix containing the tip values of all species (with species IDs as row names) should be supplied. Optionally, the user can also supply the matrix A, which contains the ancestral states in the tree with rows labeled by node number.

If type="droptip" the function will create a two panel figure in which the first panel is the tree with lineages to be pruned highlighted; and the second panel is the pruned tree. In this case, the additional argument tip, the tip name or vector of tip names to be dropped, must be supplied.

If type="densitymap", a posterior probability density "heat-map" is created based on a set of trees in a "multiSimmap" object containing a binary [0,1] mapped character. (See densityMap for additional optional arguments if type="densitymap".)

If type="contmap", reconstructed continuous trait evolution is mapped on the tree. Again, see contMap for additional arguments if type="contmap".

If type="phenogram95" a 95% traitgram (aka. "phenogram") is plotted using transparency to visualize uncertainty at ancestral nodes and along branches. Most of the options of phenogram are available.

Finally, if type="scattergram" a phylogenetic scatter plot matrix containing contMap style trees on the diagonal and phylomorphospace plots in non-diagonal panels is produced. For this type a trait matrix X must also be supplied. The only additional arguments available for this type are ftype, fsize, colors, and label. (See phylomorphospace for details on how these arguments should be used.) This function calls phyloScattergram (which is also now exported to the name space) internally. In addition to creating a plot, phyloScattergram also returns an object of class "phyloScattergram" which can be replotted using different options if desired.

Presently only type="traitgram3d" uses the list control which can be supplied the same set of control parameters as phylomorphospace3d, as well as the control parameter maxit which will be passed to anc.ML.

Finally, the optional argument hold will be passed to multiple methods if supplied. It is a logical value that indicates whether or not the output to the graphical device should be held using dev.hold before plotting (defaults to hold=TRUE).

Value

This function plots different types of phylogenetic trees. For type="droptip" the function also returns the pruned tree.

Author(s)

Liam Revell [email protected]

References

Evans, M. E. K., Smith, S. A., Flynn, R. S., Donoghue, M. J. (2009) Climate, niche evolution, and diversification of the "bird-cage" evening primroses (Oenothera, sections Anogra and Kleinia). American Naturalist, 173, 225-240.

Revell, L. J. (2013) Two new graphical methods for mapping trait evolution on phylogenies. Methods in Ecology and Evolution, 4, 754-759.

Revell, L. J. (2014) Graphical methods for visualizing comparative data on phylogenies. Chapter 4 in Modern phylogenetic comparative methods and their application in evolutionary biology: Concepts and practice (L. Z. Garamszegi ed.), pp. 77-103.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

contMap, densityMap, drop.tip, phenogram, phylomorphospace3d, plot.phylo, plotSimmap

Examples

## plot tree with extinction
set.seed(10)
tree<-pbtree(b=1,d=0.4,t=4)
fancyTree(tree,type="extinction")

## Not run: 
## plot 3D traitgram
## load data from Revell & Collar (2009)
data(sunfish.tree)
data(sunfish.data)
fancyTree(sunfish.tree,type="traitgram3d",
  X=sunfish.data[,2:3],
  control=list(spin=FALSE))
## End(Not run)
	
## plot with dropped tips
tree<-pbtree(n=30)
tips<-sample(tree$tip.label)[1:10]
pruned<-fancyTree(tree,type="droptip",tip=tips)
par(mfrow=c(1,1)) ## reset mfrow to default

## Not run: 
## plot 95-percent CI phenogram
data(mammal.tree)
data(mammal.data)
bodyMass<-setNames(mammal.data$bodyMass,
  rownames(mammal.data))
fancyTree(mammal.tree,type="phenogram95",x=bodyMass,
  fsize=0.7,ftype="i")
## End(Not run)

par(mar=c(5.1,4.1,4.1,2.1)) ## reset mar to defaults

(Reasonably) fast estimation of ML ancestral states

Description

Estimates ancestral states for a continuous character under maximum likelihood.

Usage

fastAnc(tree, x, vars=FALSE, CI=FALSE, ...)

Arguments

tree

an object of class "phylo".
x

a vector of tip values for species; names(x) should be the species names.
vars

a logical value indicating whether or not to compute variances on the ancestral state estimates. Variances are based on Equation (6) of Rohlf (2001).
CI

a logical value indicating whether or not to compute 95% confidence intervals on state estimates.
...

optional arguments. Presently this consists of anc.states, a named vector containing ancestral states to fix. Names should correspond to node numbers in the input tree.

Details

This function performs (reasonably) fast estimation of the ML ancestral states for a continuous trait by taking advantage of the fact that the state computed for the root node of the tree during Felsenstein's (1985) contrasts algorithm is also the MLE of the root node. Thus, the function re-roots the tree at all internal nodes and computes the contrasts state at the root each time.

The function can also (optionally) compute variances or 95% confidence intervals on the estimates.

Value

An object of class "fastAnc" consisting of either: a named vector containing the states at internal nodes - names are node numbers; or a list containing ancestral state estimates (ace), variances on the estimates (var), and/or 95% confidence intervals (CI95).

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

ace, anc.Bayes, anc.ML, pic

Examples

## load data from Garland et al. (1992)
data(mammal.tree)
data(mammal.data)
## extract character of interest
ln.bodyMass<-log(setNames(mammal.data$bodyMass,
    rownames(mammal.data)))
## estimate ancestral body sizes
fit.BM<-fastAnc(mammal.tree,ln.bodyMass,CI=TRUE)
print(fit.BM,printlen=10)

(Reasonably) fast quantitative trait simulation on phylogenies

Description

Simulates one or multiple continuous traits on the tree under various evolutionary models.

Usage

fastBM(tree, a=0, mu=0, sig2=1, bounds=c(-Inf,Inf), internal=FALSE, nsim=1, 
   ...)

Arguments

tree

is a phylogenetic tree in "phylo" format.
a

a value for ancestral state at the root node.
mu

an optional value for the mean of random normal changes along branches of the tree - can be used to simulate a trend if mu!=0.
sig2

instantaneous variance of the BM process, σ2\sigma^2.
bounds

a vector with the lower and upper bounds (respectively) for bounded Brownian simulation - by default simulation is unbounded.
internal

logical value indicating whether or not to return states for internal nodes.
nsim

number of simulations.
...

optional arguments alpha and theta used for OU simulation. If alpha is set then mu and bounds are ignored with a warning.

Details

This function conducts (reasonably) fast quantitative trait simulation on a phylogeny under several different models: Brownian motion (default), BM with a trend (for mu!=0), bounds (for bounds!=c(-Inf, Inf)), and OU.

Value

A vector (for nsim=1) or matrix containing the tip states for the n species in the tree, and (optionally) the ancestral states for internal nodes.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

sim.corrs

Examples

## simulate 10 characters on the Anolis tree 
## under Brownian motion
data(anoletree)
X<-fastBM(anoletree,nsim=10)
head(X)

Get the MRCA (or height above the root of the MRCA) of a pair of tip taxa

Description

Finds the most recent common ancestor (MRCA) for a pair of tip taxa.

Usage

fastMRCA(tree, sp1, sp2)
fastHeight(tree, sp1, sp2)
fastDist(tree, sp1, sp2)

Arguments

tree

an object of class "phylo".
sp1

species one name.
sp2

species two name.

Details

Function (fastMRCA) returns the most recent common ancestor (node number) for a pair of taxa; or, in the case of fastHeight, the height above the root of the MRCA of a pair of taxa; or, in the case of fastDist, the patristic distance between a pair of taxa.

This function is mostly redundant with findMRCA (or findMRCA(...,type="height") in the case of fastHeight), but for very large trees will be considerably faster.

(Also see getMRCA in the ape package.)

Value

The node number of the MRCA, the height above the root (for fastHeight), or the patristic distance between two taxa (for fastDist).

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

getMRCA, findMRCA, mrca

Examples

tree<-pbtree(n=2000)
anc<-fastMRCA(tree,"t1","t15")

Get the MRCA of a set of taxa

Description

Finds the most recent common ancestor (MRCA) of a set of tips.

Usage

findMRCA(tree, tips=NULL, type=c("node","height"))

Arguments

tree

a phylogenetic tree as an object of class "phylo".
tips

a vector containing a set of tip labels.
type

either "node" to return the node of the MRCA; or "height" to return the height above the root of the MRCA of tips.

Details

This function returns node number of the most recent common ancestor of a set of taxa.

If tips==NULL and type="node" (the default) it will return the result of a normal function call to mrca.

If tips=NULL and type="height" it will return a matrix equal to that produced by vcv.phylo.

From phytools 0.5-66 forward, findMRCA uses getMRCA in the ape package internally, which results in a big speed-up. Even though the two functions are thus totally redundant I have left findMRCA in the package namespace to ensure backward compatibility.

Value

The node number of the MRCA, or a matrix of node numbers (if tips==NULL) - for type="node"; or the height of the MRCA, or a matrix of heights (if tips==NULL) - for type="height".

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

findMRCA, mrca

Examples

data(anoletree)
anc<-findMRCA(anoletree,c("cristatellus","cooki",
  "gundlachi"))
plotTree(anoletree,type="fan",fsize=0.7,lwd=1)
nodelabels(node=anc,frame="circle",pch=21,cex=1.5,
  bg="blue")
legend("topleft","most recent common ancestor\nof Puerto Rican TG anoles",
  pch=21,pt.cex=1.5,pt.bg="blue",cex=0.7,bty="n")
par(mar=c(5.1,4.1,4.1,2.1)) ## reset margin to default

Fits birth-death (speciation/extinction) model to reconstructed phylogeny

Description

Fits a birth-death (fit.bd) or pure-birth (fit.yule) model to a reconstructed phylogenetic tree with branch lengths.

Usage

fit.bd(tree, b=NULL, d=NULL, rho=1, ...)
fit.yule(tree, b=NULL, d=NULL, rho=1, ...)
lik.bd(theta, t, rho=1, N=NULL)
## S3 method for class 'fit.bd'
print(x, ...)

Arguments

tree

object of class "phylo".
b

birth (speciation) rate. Presently doesn't do anything as the rate cannot be fixed.
d

death (extinction) rate. Presently doesn't do anything as the rate cannot be fixed.
rho

sampling fraction.
theta

vector of b and d for likelihood function.
t

branching times for calculation of the likelihood.
N

number of tips in the tree.
x

object of class "fit.bd" for print method.
...

optional arguments.

Details

The function fit.bd fits a birth-death model to a phylogenetic tree with edge lengths and a (potentially) incomplete sampling fraction.

The function fit.yule fits a pure-birth model with a (potentially) incomplete sampling fraction.

The function lik.bd computes the likelihood of a set of birth & death rates given the set of branching times computed for a tree and a sampling fraction.

Value

fit.bd returns an object of class "fit.bd" which can be printed. This object is a list containing the fitted model parameters, likelihood, optimization conditions, a summary of the optimization, and a likelihood function.

fit.yule returns an object of class "fit.yule". This object is a list containing the fitted model parameter, likelihood, optimization conditions, a summary of the optimization, and a likelihood function.

Author(s)

Liam Revell [email protected]

References

Nee, S., May, R. M. and Harvey, P. H. (1994) The reconstructed evolutionary process. Philosophical Transactions of the Royal Society of London B, 344, 305-311.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Stadler, T. (2012) How can we improve the accuracy of macroevolutionary rate estimates? Systematic Biology, 62, 321-329.

See Also

birthdeath

Examples

data(salamanders)
## compute sampling fraction based on 55 species of Plethodon
sampling.f<-Ntip(salamanders)/55
## fit birth-death model
bd.fit<-fit.bd(salamanders,rho=sampling.f)
print(bd.fit)
## fit Yule model
yule.fit<-fit.yule(salamanders,rho=sampling.f)
print(yule.fit)
## compare b-d and yule models
anova(yule.fit,bd.fit)
## create a likelihood surface for b-d model
ngrid<-100
b<-seq(0.01,0.06,length.out=ngrid)
d<-seq(0.005,0.03,length.out=ngrid)
logL<-sapply(d,function(d,b) sapply(b,function(b,d) 
    bd.fit$lik(c(b,d)),d=d),b=b)
contour(x=b,y=d,logL,nlevels=100,
    xlab=expression(lambda),
    ylab=expression(mu),bty="l")
title(main="Likelihood surface for plethodontid diversification",
    font.main=3)
points(bd.fit$b,bd.fit$d,cex=1.5,pch=4,
    col="blue",lwd=2)
legend("bottomright","ML solution",pch=4,col="blue",
    bg="white",pt.cex=1.5,pt.lwd=2)

Evolutionary model fitting with intraspecific variability using Bayesian MCMC

Description

fitBayes uses Bayesian MCMC to sample terminal states (species means) as well as the parameters of an evolutionary model from their joint posterior distribution, following Revell & Reynolds (2012).

Usage

fitBayes(tree, x, ngen=10000, model="BM", method="reduced", control=list())

Arguments

tree

an object of class "phylo".
x

a vector of phenotypic values for individuals; names(x) should contain the species names (not individual IDs).
ngen

a integer indicating the number of generations for the MCMC.
model

an evolutionary model: either "BM" or "lambda".
method

a method: either "reduced" or "full".
control

a list of control parameters containing the following elements: sig2: starting value for σ2\sigma^2 (BM rate); lambda: starting value for the λ\lambda parameter; a: starting for the state at the root node; xbar: starting values for the states at the tips; intV: starting value for the intraspecific variance (reduced method); or v: starting value for the vector of intraspecific variances for all species (full method); pr.mean: means for the prior distributions in the following order - sig2, lambda (if applicable), a, xbar, intV or v (if applicable), note that the prior probability distribution is exponential for sig2 and normal for a and y; pr.var: variances on the prior distributions, same order as pr.mean.

Value

An object of class "fitBayes" that includes a matrix (mcmc) with a number of rows ngen/control$sample+1 containing the posterior sample and likelihoods.

Matrix columns are labeled by species (for species means and variances), or by the corresponding evolutionary parameter.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Revell, L. J. and R. G. Reynolds. (2012) A new Bayesian method for fitting evolutionary models to comparative data with intraspecific variation. Evolution, 66, 2697-2707.

See Also

anc.Bayes, brownie.lite, evol.rate.mcmc

Fit diversity-dependent phenotypic evolution model

Description

Fits a diversity-dependent phenotypic evolution model (similar to Mahler et al. 2010).

Usage

fitDiversityModel(tree, x, d=NULL, showTree=TRUE, tol=1e-6)
## S3 method for class 'fitDiversityModel'
logLik(object, ...)
## S3 method for class 'fitDiversityModel'
print(x, ...)

Arguments

tree

an object of class "phylo".
x

a vector with tip values for a continuously distributed trait. For print method, an object of class "fitDiversityModel".
d

a vector containing the inferred historical diversity at each node in the tree - if d=NULL (the default) function will treat the diversification as if it occurred in a single geographic area.
showTree

optional logical value indicating whether to plot the tree transformation implied by the model.
tol

some small value by which d is incremented during rescaling of psi for optimization. If R thinks your matrices are singular during optimization, try increasing tol slightly.
object

for logLik method, an object of class "fitDiversityModel".
...

optional arguments for logLik and print methods. Note that for the logLik method the number of fitted parameters ("df") is assumed to be 3 for the diversity dependent model (that is, if psi is estimated) and 2 for the diversity independent model, unless otherwise specified (using the argument df).

Value

An object of class "fitDiversityModel" consisting of the following elements:

logL

log-likelihood of the fitted model.
sig0

estimated starting value for the rate at the root of the tree, σ02\sigma_0^2.
psi

the estimated rate of change in the rate associated with the addition of a lineage.
vcv

a matrix with the variances and covariance of the estimated parameters (from the Hessian).

Author(s)

Liam Revell [email protected]

References

Mahler, D. L, L. J. Revell, R. E. Glor, and J. B. Losos (2010) Ecological opportunity and the rate of morphological evolution in the diversification of Greater Antillean anoles. Evolution, 64, 2731-2745.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

brownie.lite, estDiversity, evol.rate.mcmc

Fits extended Mk model for discrete character evolution

Description

The functions fitMk, fitmultiMk, fitpolyMk, fitHRM, fitMk.parallel, fitgammaMk, fitfnMk, and mcmcMk fit various flavors of the extended Mk model (Lewis, 2001) for discrete character evolution on a reconstructed phylogeny.

Usage

fitMk(tree, x, model="SYM", fixedQ=NULL, ...)
## S3 method for class 'fitMk'
plot(x, ...)
## S3 method for class 'gfit'
plot(x, ...)
fitmultiMk(tree, x, model="ER", ...)
fitpolyMk(tree, x, model="SYM", ordered=FALSE, ...)
graph.polyMk(k=2, model="SYM", ordered=FALSE, ...)
## S3 method for class 'fitpolyMk'
plot(x, ...)
mcmcMk(tree, x, model="ER", ngen=10000, ...)
## S3 method for class 'mcmcMk'
plot(x, ...)
## S3 method for class 'mcmcMk'
density(x, ...)
## S3 method for class 'density.mcmcMk'
plot(x, ...)
fitHRM(tree, x, model="ARD", ncat=2, ...)
## S3 method for class 'fitHRM'
plot(x, ...)
fitMk.parallel(tree, x, model="SYM", ncores=1, ...)
fitgammaMk(tree, x, model="ER", fixedQ=NULL, nrates=8, ...)
fitfnMk(tree, x, model="polynomial", degree=2, ...)

Arguments

tree

an object of class "phylo". In the case of fitmultiMk an object of class "simmap" with a mapped discrete character.
x

a vector (or numeric matrix) of tip values for species; names(x) should be the species names. In the case of plot and density methods, an object of the appropriate class.
model

model. See make.simmap or ace for details. For fitfnMk the only option is presently model="polynomial".
fixedQ

fixed value of transition matrix Q, if one is desired.
ordered

for fitpolyMk, a logical value indicating whether or not the character should be treated as ordered. For now the function assumes alphanumerical order (i.e., numbers sorted by their initial and then successive digits followed by characters or character strings in alphabetical order).
k

For graph.polyMk, the number of monomorphic states for the discrete trait.
ngen

number of generations of MCMC for mcmcMk.
ncat

number of rate categories (per level of the discrete trait) in the hidden-rate model.
ncores

number of cores for fitMk.parallel.
nrates

number of rate categories for discretized Γ\Gamma distribution.
degree

the degree of the polynomial for fitfnMk. (Defaults to degree=2.)
...

optional arguments, including pi, the prior distribution at the root node (defaults to pi="equal"). Other options for pi include pi="fitzjohn" (which implements the prior distribution of FitzJohn et al. 2009), pi="estimated" (which finds the stationary distribution of state frequencies and sets that as the prior), or an arbitrary prior distribution specified by the user. For plot method optional arguments include (but may not be limited to): signif, the number of digits for the rates to be plotted; main, a character vector of length two with the headings for each subplot; cex.main, cex.traits, and cex.rates, font sizes for the various text elements of the plot; and show.zeros, a logical argument specifying whether or not to plot arrows with the ML estimated transition rate is not different from zero (with tolerance specified by the optional argument tol). Finally, for fitpolyMk, both order (an evolutionary sequence for the monomorphic condition) and max.poly can be set for the ordered=TRUE model. If not set, order defaults to alphanumeric order, and max.poly defaults to the highest level of polymorphism observed in the data. (max.poly can also be specified for an unordered polymorphic trait model, and if not specified, defaults to the number of distinct monomorphic states of the data.)

Details

The function fitMk fits a so-called extended Mk model for discrete character evolution (Lewis, 2001).

plot.fitMk plots an object of class "fitMk" returned by fitMk. plot.gfit plots an object of class "gfit" from geiger's fitDiscrete function. Both plots portray the fitted model using a graph of arrows connecting states.

The function fitmultiMk fits an Mk model in which the transition rates between character states are allowed to vary depending on the mapped state of a discrete character on the tree. It can be combined with, for example, paintSubTree to test hypotheses about how the process of discrete character evolution for x varies between different parts of the tree.

The function fitgammaMk fits an Mk model in which the edge rates are assumed to have been sampled randomly from a Γ\Gamma distribution with mean of 1.0 and shape parameter α\alpha.

The function fitfnMk fit an ordered Mk model in which the backward and forward transition rates between adjacent levels of the trait vary according to a functional form. Presently that function form is an nth degree polynomial, in which degree is set by the user (but defaults to degree = 2).

The function fitpolyMk fits an Mk model to data for a discrete character with intraspecific polymorphism. Polymorphic species should be coded with the name of the two or more states recorded for the species separated by a plus sign + (e.g., A+B would indicate that both states A and B are found in the corresponding taxon). Invariably it's assumed that transitions between states must occur through a polymorphic condition, whereas transitions cannot occur directly between two incompatible polymorphic conditions. For instance, a transition between A+B and B+C would have to occur through the monomorphic state B. At time of writing, this function permits the models "ER" (equal rates for all permitted transitions), "SYM" (symmetric backward & forward rates for all permitted transitions), "ARD" (all-rates-different for permitted transitions), and a new model called "transient" in which the acquisition of polymorphism (e.g., A -> A+B) is assumed to occur at a different rate than its loss (e.g., A+B -> B). The method plot.fitpolyMk plots the fitted Mk model with intraspecific polymorphism.

The function mcmcMk runs a Bayesian MCMC version of fitMk. The shape of the prior distribution of the transition rates is Γ\Gamma, with α\alpha and β\beta via the argument prior, which takes the form of a list. The default value of α\alpha is 0.1, and β\beta defaults to a value such that α/β\alpha/\beta is equal to the parsimony score for x divided by the sum of the edge lengths of the tree. The shape of the proposal distribution is normal, with mean zero and a variance that can be controlled by the user via the optional argument prior.var. The argument auto.tune, if TRUE or FALSE, indicates whether or not to 'tune' the proposal variance up or down to target a particular acceptance rate (defaults to 0.5). auto.tune can also be a numeric value between 0 and 1, in which case this value will be the target acceptance ratio. The argument plot indicates whether the progress of the MCMC should be plotted (defaults to TRUE, but runs much faster when set to FALSE).

The method plot.mcmcMk plots a log-likelihood trace and a trace of the rate parameters from the MCMC. (This the same graph that is created by setting plot=TRUE in mcmcMk.) The method density.mcmcMk computes a posterior density on the transition rates in the model from the posterior sample obtained in the MCMC, will import the package coda if it is available, and returns an object of class "density.mcmcMk". Finally, the method plot.density.mcmcMk creates a plot of the posterior density (or a set of plots) for the transition rates between states.

Finally, the function fitHRM fits a hidden-rate Mk model following Beaulieu et al. (2013). For the hidden-rate model we need to specify a number of rate categories for each level of the trait - and this can be a vector of different values for each trait. We can also choose a model ("ER", "SYM", or "ARD"), as well as whether or not to treat the character as a 'threshold' trait (umbral=TRUE, defaults to FALSE). This latter model is basically one that allows absorbing conditions for some hidden states. Since this can be a difficult optimization problem, the optional argument niter sets the number of optimization iterations to be run. niter defaults to niter=10. To fit the same default hidden-rates model as is implemented in corHMM, one should set corHMM_model=TRUE and ordered_hrm=FALSE.

Note that (by default) both fitMk and fitmultiMk recycle code from ace in the ape package for computing the likelihood. (If the optional argument pruning=TRUE then alternative, slightly faster, phytools code for the pruning algorithm is used.) fitpolyMk, mcmcMk, and fitHRM use fitMk internally to compute the likelihood.

Value

An object of class "fitMk", "fitmultiMk", "fitpolyMk", "mcmcMk", "fitHRM", "fitgammaMk", or "fitfnMk". In the case of density.mcmcMk an object of class "density.mcmcMk".

plot.fitMk, plot.gfit, and plot.HRM invisibly return the coordinates of vertices of the plotted Q-matrix.

Author(s)

Liam Revell [email protected]

References

Beaulieu, J. M., B. C. O'Meara, and M. J. Donoghue (2013) Identifying hidden rate changes in the evolution of a binary morphological character: The evolution of plant habit in campanulid angiosperms. Systematic Biology, 62, 725-737.

FitzJohn, R. G., W. P. Maddison, and S. P. Otto (2009) Estimating trait-dependent speciation and extinction rates from incompletely resolved phylogenies. Systematic Biology, 58, 595-611.

Lewis, P. O. (2001) A likelihood approach to estimating phylogeny from discrete morphological character data. Systematic Biology, 50, 913-925.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Revell, L. J. and L. J. Harmon (2022) Phylogenetic Comparative Methods in R. Princeton University Press.

See Also

ace, make.simmap

Examples

## load tree and data from Revell & Collar (2009)
data(sunfish.tree)
data(sunfish.data)
## extract discrete character (feeding mode)
fmode<-setNames(sunfish.data$feeding.mode,
    rownames(sunfish.data))
## fit "ER" model
fit.ER<-fitMk(sunfish.tree,fmode,model="ER")
print(fit.ER)
## fit "ARD" model
fit.ARD<-fitMk(sunfish.tree,fmode,model="ARD")
print(fit.ARD)
## compare the models
AIC(fit.ER,fit.ARD)

## load tree and data from Benitez-Alvarez et al. (2000)
data(flatworm.data)
data(flatworm.tree)
## extract discrete character (habitat)
habitat<-setNames(flatworm.data$Habitat,
    rownames(flatworm.data))
## fit polymorphic models "ER" and "transient"
fitpoly.ER<-fitpolyMk(flatworm.tree,habitat,
    model="ER")
fitpoly.transient<-fitpolyMk(flatworm.tree,habitat,
    model="transient")
## print fitted models
print(fitpoly.ER)
print(fitpoly.transient)
## compare model
AIC(fitpoly.ER,fitpoly.transient)
## plot models
par(mfrow=c(2,1))
plot(fitpoly.ER)
mtext("a) ER polymorphic model",adj=0,line=1)
plot(fitpoly.transient)
mtext("b) Transient polymorphic model",adj=0,
     line=1)
par(mfrow=c(1,1))

Fits bounded and wrapped Brownian motion models

Description

Fits a multi-rate discrete-state-dependent Brownian motion model using the discrete approximation of Boucher & Demery (2016).

Usage

fitmultiBM(tree, x, y=NULL, model="ER", ncat=1, ...)

Arguments

tree

object of class "phylo".
x

continuous character data in a vector.
y

optional discrete character, normally in the form of a factor or character vector.
model

discrete character evolution model. (E.g., "ER", "SYM", "ARD".)
ncat

number of rate categories (if hidden rates).
...

optional arguments.

Details

Optional arguments.

Value

An object of class "fitmultiBM".

Author(s)

Liam Revell [email protected]

References

Boucher, F. C., and V. Demery (2016) Inferring bounded evolution in phenotypic characters from phylogenetic comparative data. Systematic Biology, 65, 651-661.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

bounded_bm, brownie.lite, fitMk

Function to test for correlated evolution of binary traits

Description

Fits Pagel's (1994) model for the correlated evolution of two binary characters.

Usage

fitPagel(tree, x, y, method="fitMk", model="ARD", dep.var="xy", ...)
## S3 method for class 'fitPagel'
plot(x, ...)

Arguments

tree

an object of class "phylo".
x

a vector of phenotypic values for a binary trait for the species in tree; or a matrix in which the rows of x give the probability of being in each column state. (The latter option is only supported for method="fitMk".) For S3 plot method, an object of class "fitPagel".
y

a second binary character for the species in tree; or a matrix in which the rows give the probability of being in each column state.
method

function to use for optimization (defaults to method="fitMk"). Other options are "ace" to use the ace function in ape for optimization, or to "fitDiscrete" (if the geiger package is installed) to use geiger's fitDiscrete for optimization.
model

model of evolution for the individual characters. Can be model="ER", "SYM" (equivalent to "ER" in this case), and "ARD".
dep.var

dependent variable. If dep.var="xy" than the rate of substitution in x depends on y & vice versa. If dep.var="x" than the substitution rate in x depends on y, but not the converse. Finally, if dep.var="y" than the rate of substitution in y depends on x, but not the converse.
...

optional arguments to be passed to fitMk, ace, or fitDiscrete. For plot method optional arguments include (but may not be limited to): signif, the number of digits for the rates to be plotted; main, a character vector of length two with the headings for each subplot; cex.main, cex.sub, cex.traits, and cex.rates, font sizes for the various text elements of the plot; and lwd.by.rate, a logical argument specifying whether or not to scale arrow line widths in proportion to the estimated rates.

Details

fitPagel fits both an independent evolution model, as well as Pagel's (1994) binary dependent model, and compares them with a likelihood-ratio test.

plot.fitPagel plots the fitted models using arrows.

Value

An object of class "fitPagel" which contains the optimized matrices under an independence & a dependence model, log-likelihoods, a likelihood ratio, and a P-value for the independence model based on a chi-squared test.

plot.fitPagel creates a plot showing the different fitted models with arrows.

Author(s)

Liam Revell [email protected]

References

Pagel, M. (1994) Detecting correlated evolution on phylogenies: A general method for the comparative analysis of discrete characters. Proceedings of the Royal Society B, 255, 37-45.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

ace, fitMk, make.simmap

Examples

## Not run: 
## load data
data(bonyfish.tree)
data(bonyfish.data)
## extract discrete characters
spawning_mode<-setNames(bonyfish.data$spawning_mode,
    rownames(bonyfish.data))
paternal_care<-setNames(bonyfish.data$paternal_care,
    rownames(bonyfish.data))
## fit correlational model
bonyfish.pagel<-fitPagel(bonyfish.tree,paternal_care,
    spawning_mode)
## test for a difference between models
anova(bonyfish.pagel)
## plot fitted models
plot(bonyfish.pagel,lwd.by.rate=TRUE)
## reset par
par(mar=c(5.1,4.1,4.1,2.1),
    mfrow=c(1,1))
## End(Not run)

Fits multi-state threshold model using the discrete approximation

Description

This function uses the discrete approximation of Boucher and Demery (2016) to fit a multi-state discrete character threshold model following Felsenstein (2012; Revell 2014).

Usage

fitThresh(tree, x, sequence=NULL, ...)

Arguments

tree

object of class "phylo".
x

a named vector.
sequence

assumed ordering of the discrete character state. If not supplied and then alphanumeric order is assumed.
...

optional arguments.

Value

An object of class "fitThresh".

Author(s)

Liam Revell [email protected]

References

Boucher, F. C., and V. Demery (2016) Inferring bounded evolution in phenotypic characters from phylogenetic comparative data. Systematic Biology, 65, 651-661.

Felsenstein, J. (2012) A comparative method for both discrete and continuous characters using the threshold model. American Naturalist, 179, 145-156.

Revell, L. J. (2014) Ancestral character estimation under the threshold model from quantitative genetics. Evolution, 68, 743-759.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

ancThresh, bounded_bm, fitmultiBM, threshBayes

Coerces a phylogenetic tree to be ultrametric

Description

Coerces an object of class "phylo" to be ultrametric.

Usage

force.ultrametric(tree, method=c("nnls","extend"), ...)

Arguments

tree

an object of class "phylo".
method

the method to use to force the tree to be ultrametric. Options are "nnls" (which uses the phangorn function nnls.tree internally), or "extend".
...

optional arguments: principally, message. This argument (if set to FALSE) can be used to suppress the default warning message that force.ultrametric should not be used as a formal statistical method to ultrametricize a tree.

Details

force.ultrametric coerces a non-ultrametric tree to be ultrametric.

This is achieved either by using nnls.tree from the phangorn package to compute the set of edge lengths that result in a minimized sum-of-squares distance between the patristic distance of the output and input trees (method="nnls"); or by simply extending all the external edges of the tree to match the external edge with the greatest total height (method="extend").

Note that neither of these should be treated as formal statistical methods for inferring an ultrametric tree. Rather, this method can be deployed when a genuinely ultrametric tree read from file fails is.ultrametric for reasons of numerical precision.

Value

An ultrametric tree in an object of class "phylo".

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

is.ultrametric, nnls.tree

Internally used function

Description

Internally used function to compute the likelihood under a Γ\Gamma model.

Usage

gamma_pruning(par, nrates=4, tree, x, model=NULL, median=TRUE,
  expm.method="Higham08.b", ...)

Arguments

par

function parameters.
nrates

number of discrete rate categories.
tree

object of class "phylo".
x

data in the form of a binary matrix.
model

design matrix of fitted model.
median

use the median of each rate category.
expm.method

method used for matrix exponentiation.
...

optional arguments.

Value

A value of the log-likelihood.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Gamma test of Pybus & Harvey (2000)

Description

Conducts γ\gamma-test of Pybus & Harvey (2000).

Usage

gammatest(x)

Arguments

x

an object of class "ltt" resulting from a call of the function ltt.

Value

A an object of class "gammatest" consisting of a list that contains:

gamma

a value for the γ\gamma-statistic.
p

two-tailed P-value for the γ\gamma-test.

Author(s)

Liam Revell [email protected]

References

Pybus, O. G., and P. H. Harvey (2000) Testing macro-evolutionary models using incomplete molecular phylogenies. Proc. R. Soc. Lond. B, 267, 2267-2272.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

ltt, mccr

Examples

data(darter.tree)
gammatest(ltt(darter.tree,plot=FALSE))

Simulate a DNA alignment on the tree under a model

Description

Simulates DNA sequence on tree under the specified model.

Usage

genSeq(tree, l=1000, Q=NULL, rate=1, format="DNAbin", ...)

Arguments

tree

object of class "phylo".
l

length of desired sequences.
Q

transition matrix for the simulation. Row and column names (c("a","c","g","t"), although not necessarily in that order) should be provided. If NULL, a single rate is assumed.
rate

multiplier for Q, or a vector for Γ\Gamma rate heterogeneity.
format

format of the output object. Can be "DNAbin", "phyDat", or "matrix".
...

optional arguments.

Details

Uses sim.Mk internally.

Value

An object of class "DNAbin" or "phyDat", or a matrix of nucleotides.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Examples

data(mammal.tree)
mammal.tree$edge.length<-mammal.tree$edge.length/
    max(nodeHeights(mammal.tree))*0.2 ## rescale tree
## simulate gamma rate heterogeneity
gg<-rgamma(n=100,shape=0.25,rate=0.25)
dna<-genSeq(mammal.tree,l=100,rate=gg)

Adds a geological (or other temporal) legend to a plotted tree

Description

Adds a geological legend to a plotted tree.

Usage

geo.legend(leg=NULL, colors=NULL, alpha=0.2, ...)
geo.palette()

Arguments

leg

a matrix with the starting & ending point of each plotted era in rows, & names of the time periods as rownames.
colors

a vector of colors for the time periods of the rows in leg.
alpha

transparency level to apply to colors.
...

optional arguments.

Details

The function geo.legend adds a geological (or other temporal) legend to a plotted tree.

The function geo.palette returns a geological time color palette to the user.

Value

geo.legend adds a visual element to a plotted tree and invisible returns an object of class geo.legend containing the time periods and colors of the painted legend.

geo.palette simply returns a geological timescale color palette as an object of class "geo.palette".

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Examples

data(anoletree)
## rescale tree to 50 ma total depth
anoletree<-rescale(anoletree,model="depth",depth=50)
## plot phylogeny
plotTree(anoletree,ylim=c(-0.16,1)*Ntip(anoletree),
  ftype="i",lwd=1,fsize=0.5)
## add geological color legend
obj<-geo.legend()
par(mar=c(5.1,4.1,4.1,2.1))

Get position or node of a plotted tree interactively

Description

Return the phylogenetic position of a mouse click on a plotted tree.

Usage

get.treepos(message=TRUE, ...)
getnode(...)

Arguments

message

for get.treepos, a logical value indicating whether or not to print an instructional message.
...

optional arguments.

Details

Both get.treepos and getnode are primarily meant for internal use in other phytools functions.

get.treepos returns the index of the node at the end of the selected edge, along with the branch distance to that node.

getnode simply returns the closest node to the user mouse click.

Value

A list for get.treepos and a node number for getnode.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Get all subtrees larger than or equal to a specified size

Description

This function gets all subtrees that cannot be further subdivided into two reciprocally monophyletic subtrees of size >= clade.size.

Usage

getCladesofSize(tree, clade.size=2)

Arguments

tree

is an object of class "phylo".
clade.size

subtree size.

Value

An object of class "multiPhylo".

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

extract.clade, getDescendants

Get descendant node numbers

Description

Returns the descendants or parent of a specified node.

Usage

getDescendants(tree, node, curr=NULL)
getParent(tree, node)

Arguments

tree

a phylogenetic tree as an object of class "phylo".
node

an integer specifying a node number in the tree.
curr

the set of previously stored node numbers - used in recursive function calls.

Details

getDescendants returns the set of node & tip numbers descended from node.

getParent returns the single parent node of a specified node number (or NULL if node is already the root).

Value

The set of node and tip numbers for the nodes and tips descended from node in a vector, or for getParent the single node preceding node in the tree.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

Descendants, paintSubTree

Returns a list of the extant or extinct lineages in a tree containing non-contemporaneous tips

Description

Computes the set of extant or extinct tips from a phylogenetic tree.

Usage

getExtant(tree, tol=1e-8)
getExtinct(tree, tol=1e-8)

Arguments

tree

a phylogeny stored as an object of class "phylo" with some tips that are non-contemporaneous (i.e., end before the present).
tol

a tolerance value to account for numerical imprecision.

Details

The function getExtant takes a tree as input and returns a vector containing the names of all the tips that have a height above the root that is equal (to a degree of numerical precision determined by tol) to the height of the highest tip. These tips are presumed to be "extant."

getExtinct returns the complement.

Value

A vector with the tip names of extant or extinct species in the tree.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

nodeHeights

Get the sister node number, label, or set of nodes for a node or tip

Description

Computes the sister taxon or node.

Usage

getSisters(tree, node, mode=c("number","label"))

Arguments

tree

object of class "phylo".
node

a node number, tip number, node label, or tip label.
mode

an optional string indicating whether to return the node or tip number(s) or the node or tip label(s), if applicable.

Details

This function takes a tree and node or tip number of label and returns the number or label of the sister or sisters to that node or tip.

Value

If mode="number" this function returns an integer or vector containing the node number of numbers of the sister node or tip. If mode="label" then this function returns a list containing up to two vectors: one for the node numbers of labels of sister nodes (if applicable); and the other containing the tip labels of the sister tips.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

getDescendants, Siblings

Get the states at nodes or tips from a mapped tree

Description

Gets the states from the nodes or tips of a mapped tree (e.g., make.simmap).

Usage

getStates(tree, type=c("nodes","tips","both"))

Arguments

tree

is a modified object of class "phylo" or "multiPhylo".
type

mode indicating whether to get states at the nodes (type="nodes") or the tips (type="tips") of the tree.

Value

A named vector (for "phylo") or matrix (for "multiPhylo").

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

describe.simmap, make.simmap, read.simmap, sim.history

Function to interactively label nodes of a plotted tree

Description

Adds node labels to a plotted object of class "phylo".

Usage

labelnodes(text, node=NULL, interactive=TRUE, shape=c("circle","ellipse",
   "rect"), ...)

Arguments

text

text string or vector to be used as labels.
node

node numbers (indices) for the labels.
interactive

logical value indicating whether or not nodes should be supplied interactively. (I.e., by clicking on the nodes.)
shape

shape to plot around the plotted node label(s).
...

optional arguments.

Details

The nodes to be labels can be selected interactively by the user (i.e., by clicking on the corresponding nodes of the plotted tree).

Value

Invisibly returns a vector of the node indices for the labeled nodes.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

cladelabels, nodelabels

Ladderize a tree with a mapped discrete character

Description

Ladderizes an object of class "simmap".

Usage

ladderize.simmap(tree, right=TRUE)

Arguments

tree

an object of class "simmap".
right

a logical specifying how the tree should be ladderized.

Details

This function 'ladderizes' an object of class "simmap" with a mapped discrete character.

For more information see ladderize.

Value

A ladderized object of class "simmap".

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

make.simmap, ladderize

λ\lambda transformation of matrix

Description

Internal function for phyl.pca and others.

Usage

lambda.transform(lambda, C)

Arguments

lambda

scalar, usually (but not necessarily) on the interval 0,1.
C

matrix probably returned by vcv.phylo.

Details

Multiplies the off-diagonals of a square matrix by lambda and returns the result.

Value

Typically an among-species phylogenetic variance covariance matrix (e.g., vcv.phylo) in which the off-diagonal elements have been multiplied by lambda.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Likelihood for joint λ\lambda

Description

Likelihood function for joint estimation of Pagel's λ\lambda parameter.

Usage

likMlambda(lambda, X, C)

Arguments

lambda

scalar, usually on the interval 0,1 (although not required to be).
X

data for various continuous character, in the form of a matrix.
C

n x n matrix (for n taxa) containing the height above the root for each pair of taxa in the tree (e.g., vcv.phylo).

Details

Generally intended to be used internally by other methods that do joint optimization of λ\lambda (e.g., phyl.pca).

Value

The log-likelihood.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Function to add tip labels to a plotted tree with linking lines

Description

Adds tip labels to a plotted tree by drawing curved, bent, or straight linking lines.

Usage

linklabels(text,tips,link.type=c("bent","curved","straight"),
   ...)

Arguments

text

text string or vector to be used as labels.
tips

node numbers (indices) for the tips to be labeled.
link.type

manner in which to draw the linking lines.
...

optional arguments, including cex, lty, lwd, and col.

Details

The idea underlying this function is that the user should first plot the tree without tip labels, but set the area of the plotting device to be sufficient to accommodate the tip labels once they have been added. The function then can be called to add tip labels connected by linking lines to the tips of the plotted tree.

Value

This function annotates a plot.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

cladelabels, nodelabels, tiplabels

Locate a fossil lineage in a tree using continuous characters

Description

Uses ML to place a fossil lineage into a tree using continuous traits following Revell et al. (2015).

Usage

locate.fossil(tree, X, ...)

Arguments

tree

an object of class "phylo".
X

a matrix with continuous character data.
...

optional arguments including time.constraint which can be a scalar (positive height above the root of the fossil or negative time before present) or a vector (age range of fossil, either positive or negative); edge.constraint, which is equivalent to constraint in locate.yeti; plot, rotate, and quiet, which have the same interpretation (and defaults) as the equivalent arguments in locate.yeti.

Value

Optimized tree as an object of class "phylo".

Author(s)

Liam Revell [email protected]

References

Felsenstein, J. (1981) Maximum likelihood estimation of evolutionary trees from continuous characters. American Journal of Human Genetics, 25, 471-492.

Felsenstein, J. (2002) Quantitative characters, phylogenies, and morphometrics. In: MacLeod, N. and P. Forey (Eds.) Morphology, Shape and Phylogeny (pp. 27-44). Taylor and Francis, London.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Revell, L. J., D. L. Mahler, R. G. Reynolds, and G. J. Slater. (2015) Placing cryptic, recently extinct, or hypothesized taxa into an ultrametric phylogeny using continuous, character data: A case study with the lizard Anolis roosevelti. Evolution, 69, 1027-1035.

Locate a cryptic, recently extinct, or missing taxon on a tree

Description

Uses ML (or REML) to place a recently extinct, cryptic, or missing taxon on an ultrametric (i.e., time-calibrated) phylogeny following Revell et al. (2015).

Usage

locate.yeti(tree, X, ...)

Arguments

tree

an object of class "phylo".
X

a matrix with continuous character data.
...

optional arguments including: method ("ML" or "REML", defaults to "ML"); search ("heuristic" or "exhaustive", defaults to "heuristic"); constraint, a vector containing the daughter node numbers from tree$edge for each edge to try; plot a logical argument specifying whether or not to plot the likelihood profile on edges (defaults to FALSE); rotate a logical indicating whether or not to rotate the data based on the input tree; and quiet, which is logical and has an obvious interpretation.

Value

Optimized tree as an object of class "phylo".

Author(s)

Liam Revell [email protected]

References

Felsenstein, J. (1981) Maximum likelihood estimation of evolutionary trees from continuous characters. American Journal of Human Genetics, 25, 471-492.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Revell, L. J., D. L. Mahler, R. G. Reynolds, and G. J. Slater. (2015) Placing cryptic, recently extinct, or hypothesized taxa into an ultrametric phylogeny using continuous, character data: A case study with the lizard Anolis roosevelti. Evolution, 69, 1027-1035.

Least squares branch lengths for a given tree

Description

Computes the least squares branch lengths conditioned on a topology and distance matrix.

Usage

ls.tree(tree, D)

Arguments

tree

phylogeny.
D

distance matrix.

Details

Generally intended as a function to be used internally by optim.phylo.ls.

Value

A tree with branch lengths.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Creates lineage-through-time plot (including extinct lineages)

Description

Computes and visualizes a lineage through time (LTT) plot, and related measures.

Usage

ltt(tree, ...)
## S3 method for class 'phylo'
ltt(tree, plot=TRUE, drop.extinct=FALSE, log.lineages=TRUE, gamma=TRUE, ...)
## S3 method for class 'multiPhylo'
ltt(tree, drop.extinct=FALSE, gamma=TRUE, ...)
## S3 method for class 'simmap'
ltt(tree, plot=TRUE, log.lineages=FALSE, gamma=TRUE, ...)
## S3 method for class 'multiSimmap'
ltt(tree, gamma=TRUE, ...)
gtt(tree, n=100, ...)
mccr(obj, rho=1, nsim=100, ...)

Arguments

tree

an object of class "phylo", "multiPhylo", "simmap", or "multiSimmap".
plot

a logical value indicating whether or not to create LTT plot.
drop.extinct

logical value indicating whether or not to drop extinct tips from the tree.
log.lineages

logical value indicating whether LTT plot should be on log-linear (default for "phylo" and "multiPhylo" objects) or linear-linear scale.
gamma

logical value indicating whether or not to compute γ\gamma from Pybus & Harvey (2000; Proc. Roy. Soc. B).
n

for gtt the number of time intervals to use to track γ\gamma through time.
obj

for mccr an object of class "ltt".
rho

for mccr sampling fraction.
nsim

for mccr number of simulations to use for the MCCR test.
...

other arguments to be passed to plotting methods. See plot.default.

Details

The function ltt computes LTT plot with extant and extinct lineages, and optionally conducts γ\gamma-test of Pybus & Harvey (2000). The object returned by ltt can be plotted or re-plotted using plot.

For the case in which tree is an object of class "simmap" or "multiSimmap" then the object will contain the number of lineages through time (for each tree, in the case of "multiSimmap" objects) separated by mapped regimes.

The function gtt computes the value of Pybus & Harvey's γ\gamma statistic through time by slicing the tree at various points - by default in even intervals from the time above the root at which N = 3 to the present day.

The function mccr performs the MCCR test of Pybus & Harvey (2000) which takes into account incomplete taxon sampling in computing a P-value of the γ\gamma statistic.

Although it is calculated here, it's unclear how to interpret the γ\gamma-statistic if not all the tips in the tree are contemporaneous.

Value

ltt returns an object of class "ltt" which normally includes the following elements:

times

a vector of branching times.
ltt

a vector of lineages, or a matrix of lineages in each state over time for objects of class "simmap" and "multiSimmap".
gamma

optionally, a value for the γ\gamma-statistic.
p

two-tailed P-value for the γ\gamma-test.

If tree is an object of class "multiPhylo", then an object of class "multiLtt" is returned consisting of a list of object of class "ltt".

gtt returns an object of class "gtt".

mccr returns of object of class "mccr".

Author(s)

Liam Revell [email protected]

References

Pybus, O. G., and P. H. Harvey (2000) Testing macro-evolutionary models using incomplete molecular phylogenies. Proc. R. Soc. Lond. B, 267, 2267-2272.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

gammatest, ltt95

Examples

## LTT plots
set.seed(99)
trees<-pbtree(n=100,scale=100,nsim=10)
obj<-ltt(trees,plot=FALSE)
plot(obj,log="y",log.lineages=FALSE,
    bty="l")
title(main="LTT plots for 10 pure-birth trees",
    font.main=3)
tree<-pbtree(b=1,d=0.25,t=4)
obj<-ltt(tree,gamma=FALSE,show.tree=TRUE,
    bty="l")
title(main="LTT plot with superimposed tree",
    font.main=3)
obj
## GTT plot
data(anoletree)
anole.gtt<-gtt(anoletree,n=40)
plot(anole.gtt)

Creates a (1-α\alpha)% CI for a set of LTTs

Description

This function computes LTT plots for a set of trees & plots a (1-α\alpha)% CI by various methods. (See ltt for more details.)

Usage

ltt95(trees, alpha=0.05, log=FALSE, method=c("lineages","times"),
   mode=c("median","mean"), ...)
## S3 method for class 'ltt95'
plot(x, ...)

Arguments

trees

is an object of class "multiPhylo" containing a list of phylogenetic trees.
alpha

confidence level. Defaults to alpha=0.05. alpha=0 will mean that the interval around all trees in the set will be plotted.
log

logical value indicating whether or not to plot on the semi-log scale.
method

plot the CI on the number of lineages given time ("lineages"); or on times given a number of lineages ("times").
mode

plot the median or mean LTT.
x

object of class "ltt95" for plotting method.
...

optional arguments to be used by ltt95 or the plotting method. So far: res gives the number of time-steps (defaults to res=100); xaxis ("standard", "negative", or "flipped") determines the scale (time from the root, time back from the present, or time from the present) of the x-axis of the plot; lend determines the line end type (as in par); shaded determines whether to plot the (1-α\alpha)% CI using dotted lines (if FALSE) or shading (if TRUE); and bg is the background color for shading if shaded=TRUE.

Details

This function creates a plot and invisibly returns an object of class "ltt95".

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

ltt

Create "era" map on a phylogenetic tree

Description

Creates a temporal map on the tree based on limits provided by the user.

Usage

make.era.map(tree, limits, ...)

Arguments

tree

an object of class "phylo".
limits

a vector containing the temporal limits, in time since the root node of the tree, for the mappings. The first number should be 0, and each subsequent number should be the start of each subsequent regime or era to be mapped on the tree.
...

optional arguments.

Value

An object of class "simmap" with the specified eras mapped as different regimes.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

make.simmap, read.simmap, plotSimmap

Examples

tree<-pbtree(n=1000,scale=100)
tree<-make.era.map(tree,c(0,25,50,75))
plot(tree,ftype="off",lwd=1)
par(mar=c(5.1,4.1,4.1,2.1)) ## reset margins to default

Simulate stochastic character maps on a phylogenetic tree or trees

Description

Performs stochastic character mapping (Huelsenbeck et al., 2003) using several different alternative methods.

Usage

make.simmap(tree, x, model="SYM", nsim=1, ...)
simmap(object, ...)

Arguments

tree

a phylogenetic tree as an object of class "phylo", or a list of trees as an object of class "multiPhylo".
x

a vector containing the tip states for a discretely valued character, or a matrix containing the prior probabilities of tip states in rows and character states as column names. The names (if x is a vector) or row names (if x is a matrix) should match the tip labels of the tree. The vector can be of class "factor", "character", or "numeric" (although in the lattermost case its content should obviously be only integer values).
model

a character string containing the model or a transition model specified in the form of a matrix. See ace for more details.
nsim

number of simulations. If tree is an object of class "multiPhylo", then nsim simulations will be conducted per input tree.
...

optional arguments. So far, pi gives the prior distribution on the root node of the tree. Acceptable values for pi are "equal", "estimated", or a vector with the frequencies. If pi="estimated" then the stationary distribution is estimated by numerically solving pi*Q=0 for pi, and this is used as a prior on the root. If pi="fitzjohn", then the Fitzjohn et al. (2009) root prior is used. Finally, if pi is a numeric vector then the root state will be sampled from this vector. The function defaults to pi="equal" which results in the root node being sampled from the conditional scaled likelihood distribution at the root. message tells whether or not to print a message containing the rate matrix, Q and state frequencies. message defaults to TRUE. For optional argument Q="mcmc" (see below) the mean value of Q from the posterior sample is printed. tol gives the tolerance for zero elements in Q. (Elements less then tol will be reset to tol). Optional argument Q can be a string ("empirical" or "mcmc"), or a fixed value of the transition matrix, Q. If "empirical" than a single value of Q, the most likely value, is used for all simulations. If "mcmc", then nsim values of Q are first obtained from the posterior distribution for Q using Bayesian MCMC, then a simulated stochastic character map is generated for each sampled value of Q. Optional argument vQ can consist of a single numeric value or a vector containing the variances of the (normal) proposal distributions for the MCMC. The order of vQ is assumed to be in the order of the index.matrix in ace for the chosen model. prior is a list containing alpha and beta parameters for the Γ\Gamma prior distribution on the transition rates in Q. Note that alpha and beta can be single values or vectors, if different priors are desired for each value in the transition matrix Q. As for vQ, the order of prior is assumed to correspond with the order of index.matrix as in ace. prior can also be given the optional logical value use.empirical which tells the function whether or not to give the prior distribution the empirical mean for Q. If TRUE then only prior$beta is used and prior$alpha is set equal to prior$beta times the empirical mean of Q. burnin and samplefreq are burn-in and sample frequency for the MCMC, respectively.
object

for generic simmap method, object of various classes: for instance, an object of class "fitMk" from fitMk.

Details

For Q="empirical", make.simmap first fits a continuous-time reversible Markov model for the evolution of x and then simulates stochastic character histories using that model and the tip states on the tree. This is the same procedure that is described in Bollback (2006), except that simulation is performed using a fixed value of the transition matrix, Q, instead of by sampling Q from its posterior distribution.

For Q="mcmc", make.simmap first samples Q nsim times from the posterior probability distribution of Q using MCMC, then it simulates nsim stochastic maps conditioned on each sampled value of Q.

For Q set to a matrix, make.simmap samples stochastic mappings conditioned on the fixed input matrix.

make.simmap uses code that has been adapted from ape's function ace (by Paradis et al.) to perform Felsenstein's pruning algorithm to compute the likelihood.

As of phytools >= 0.2-33 x can be a vector of states or a matrix containing the prior probabilities of tip states in rows. In this case the column names of x should contain the states, and the row names should contain the tip names.

Note that there was a small (but potentially significant) bug in how node states were simulated by make.simmap in versions of phytools <= 0.2-26. Between phytools 0.2-26 and 0.2-36 there was also a bug for asymmetric models of character change (e.g., model="ARD"). Finally, between phytools 0.2-33 and phytools 0.2-47 there was an error in use of the conditional likelihoods for the root node, which caused the root node of the tree to be sampled incorrectly. Giorgio Bianchini pointed out that in phytools 1.0-1 (and probably prior recent versions) there was an error sampling the state at the root node of the tree based on the input prior (pi) supplied by a user – except for pi="equal" (a flat prior, the default) or for a prior distribution in which one or another state was known to be the global root state (e.g., pi=c(1,0), pi=c(0,1), etc.). All of these issues should be fixed in the current and all later versions.

If tree is an object of class "multiPhylo" then nsim stochastic maps are generated for each input tree.

Value

A object of class "simmap" or "multiSimmap" which consists of an object of class "phylo" (or a list of such objects with class "multiPhylo"), with the following additional elements:

maps

a list of named vectors containing the times spent in each state on each branch, in the order in which they occur.
mapped.edge

a matrix containing the total time spent in each state along each edge of the tree.
Q

the assumed or sampled value of Q.
logL

the log-likelihood of the assumed or sampled Q.

Author(s)

Liam Revell [email protected]

References

Bollback, J. P. (2006) Stochastic character mapping of discrete traits on phylogenies. BMC Bioinformatics, 7, 88.

FitzJohn, R. G., W. P. Maddison, and S. P. Otto (2009) Estimating trait-dependent speciation and extinction rates from incompletely resolved phylogenies. Systematic Biology, 58, 595-611.

Huelsenbeck, J. P., R. Neilsen, and J. P. Bollback (2003) Stochastic mapping of morphological characters. Systematic Biology, 52, 131-138.

Paradis, E., J. Claude, and K. Strimmer (2004) APE: Analyses of phylogenetics and evolution in R language. Bioinformatics, 20, 289-290.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Revell, L. J. and L. J. Harmon (2022) Phylogenetic Comparative Methods in R. Princeton University Press.

See Also

brownie.lite, brownieREML, countSimmap, describe.simmap, evol.vcv, plotSimmap, read.simmap, write.simmap

Examples

## Not run: 
## load tree and data from Revell & Collar (2009)
data(sunfish.tree)
data(sunfish.data)
## extract discrete character (feeding mode)
fmode<-setNames(sunfish.data$feeding.mode,
  rownames(sunfish.data))
## fit model
er_model<-fitMk(sunfish.tree,fmode,model="ER",
  pi="fitzjohn")
## do stochastic mapping
sunfish_smap<-simmap(er_model)
## print a summary of the stochastic mapping
summary(sunfish_smap)
## plot a posterior probabilities of ancestral states
cols<-setNames(c("blue","red"),levels(fmode))
plot(summary(sunfish_smap),colors=cols,ftype="i")
legend("topleft",c("non-piscivorous","piscivorous"),
  pch=21,pt.bg=cols,pt.cex=2)
par(mar=c(5.1,4.1,4.1,2.1),las=1)
## plot posterior density on the number of changes
plot(density(sunfish_smap),bty="l")
title(main="Posterior distribution of changes of each type",
  font.main=3)
## End(Not run)

Proportional overlap between two mapped character histories on a tree

Description

Calculates the similarity of two different stochastically mapped character histories.

Usage

map.overlap(tree1, tree2, tol=1e-6, ...)
Map.Overlap(tree1, tree2, tol=1e-06, standardize=TRUE, ...)

Arguments

tree1

an object of class "simmap".
tree2

an object of class "simmap".
tol

an optional tolerance value.
standardize

for Map.Overlap, a logical value indicating whether or not to standardize overlap by dividing by the summed branch length of the tree.
...

optional arguments, such as check.equal, a logical value indicating whether or not to check if tree1 and tree2 match in underlying topology and branch lengths (they should). This value is TRUE by default, but can be set to FALSE if tree1 and tree2 are known to be equal to speed up calculation.

Details

map.overlap computes a single quantity giving the overall similarity of the maps, consequently this measure only makes sense of some or all of the states are shared between the two mapped tress.

In Map.Overlap what is computed instead is a matrix in which the rows correspond to the states observed in tree1 and the columns give the states for tree2, with the numerical values of the matrix showing the total overlap between each pair of mapped states on the two trees.

Value

A numerical value on the interval (0, 1), for map.overlap; or a matrix whose elements should sum to 1.0 (Map.Overlap).

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

make.simmap, read.simmap

Converts a tree without singletons to a tree with singleton nodes

Description

map.to.singleton takes an object of class "simmap" with a mapped discrete character and converts it to a tree with singleton nodes, in which edge has only one state.

Usage

map.to.singleton(tree)
plotTree.singletons(tree)
## S3 method for class 'singleton'
drop.tip(phy, tip, ...)
rootedge.to.singleton(tree)

Arguments

tree

an object of class "simmap" (for map.to.singleton, or a tree with one or more singleton nodes (for plotTree.singletons, drop.tip.singleton, and rootedge.to.singleton).
phy

for drop.tip.singleton, an object of class "singleton" or "phylo".
tip

for drop.tip.singleton, a tip label or vector of tip labels.
...

optional arguments for drop.tip.singleton.

Details

The states for each edge are stored in names(tree$edge.length). In a sense this is just an alternative way to use the general structure of the "phylo" object to encode a tree with a mapped character.

plotTree.singletons plots a tree with singleton nodes. Note that plotTree and plot.phylo now have no trouble graphing trees with singleton nodes - but they do this by just ignoring the singletons. plotTree.singletons marks the singletons as nodes on the plotted phylogeny.

drop.tip.singleton drops tips from the tree leaving ancestral nodes for all remaining tips as singletons.

Finally, rootedge.to.singleton converts a tree with a root edge to a tree with a singleton node instead.

Value

An object of class "phylo" with singleton nodes. plotTree.singletons graphs a tree in which the singleton nodes are shown.

If names(tree$edge.length)!=NULL plotTree.singletons will use a different color from palette for each mapped state.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

collapse.singles, drop.tip, make.simmap

Returns a vector, matrix, or list of the mapped states on a tree or set of trees

Description

Computes and orders a vector, matrix, or list of the unique mapped states on a tree or state of trees of class "simmap" or "multiSimmap".

Usage

mapped.states(tree, ...)

Arguments

tree

a single tree or a set of trees as an object of class "simmap" or "multiSimmap", respectively.
...

optional arguments.

Value

A vector, matrix, or list.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Add marked changes to a plotted tree with mapped discrete character

Description

Adds the reconstructed changes to a plotted tree with a stochastically mapped discrete character.

Usage

markChanges(tree, colors=NULL, cex=1, lwd=2, plot=TRUE)

Arguments

tree

an object of class "simmap".
colors

a named vector of colors used to plot the stochastically mapped character on the tree.
cex

expansion factor for line height.
lwd

line width.
plot

logical value indicating whether the changes should be plotted or not.

Value

This function returns (invisibly) a matrix containing the x & y coordinates of the marked changes on the plotted tree.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

plotSimmap

Examples

## load tree and data from Revell & Collar (2009)
data(sunfish.tree)
data(sunfish.data)
## extract discrete character (feeding mode)
fmode<-setNames(sunfish.data$feeding.mode,
  rownames(sunfish.data))
## fit model
er_model<-fitMk(sunfish.tree,fmode,model="ER",
  pi="fitzjohn")
## generate single stochastic map
sunfish_smap<-simmap(er_model,nsim=1)
## plot stochastic map & mark changes
cols<-setNames(c("blue","red"),levels(fmode))
plot(sunfish_smap,cols,ftype="i")
markChanges(sunfish_smap,colors=cols,lwd=6)
par(mar=c(5.1,4.1,4.1,2.1))

Matches nodes between two trees

Description

This function returns a matrix in which the first column contains all of the internal nodes of tr1 and the second column contains the matching nodes from tr2, inasmuch as they can be identified.

Usage

matchNodes(tr1, tr2, method=c("descendants","distances"), ...)
matchLabels(tr1, tr2)

Arguments

tr1

first tree.
tr2

second tree.
method

method to use to match nodes between trees. "descendants" uses the tip species descended from each node; "distances" uses the distances from the nodes to the tips. Any unambiguous shortening of "descendants" or "distances" is also permitted.
...

optional arguments which may or may not be used depending on the value of method. tol is a tolerance value for the difference from exact matching that is allowed for method="distances". corr, which is FALSE by default, indicates whether to match nodes under method="distances" using the correlation (corr=TRUE) or the absolute similarity of distances.

Details

For method="descendants", pairs of matching nodes are defined by sharing all descendant leaves in common.

For method="distances", nodes are considered to matched if the share the same set of distances (or proportional distances, for optional argument corr=TRUE) to all tips.

matchLabels is functionally equivalent but matches node (tip) indices based on identifying matching in the labels only.

Value

A matrix in which the first column contains the nodes of tr1 with the second column containing matching nodes in tr2, with the criterion for matching defined by method.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Merge two or more mapped states into one state

Description

Merges two or mapped states on the tree to get one new state.

Usage

mergeMappedStates(tree, old.states, new.state)

Arguments

tree

an object of class "simmap" or "multiSimmap" containing one or more phylogenetic trees with a mapped discrete character.
old.states

states to merge.
new.state

name for new state.

Details

mergeMappedStates can be used to merge two or more mapped states into a single, new state. For instance, one could merge the states "C", "G", and "T" and define the new the state "not-A".

Value

An object of class "simmap" or "multiSimmap".

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

make.simmap, read.simmap

Midpoint root a phylogeny

Description

These functions midpoint root a rooted or unrooted tree (Farris 1972).

Usage

midpoint_root(tree)
## S3 method for class 'root'
midpoint(tree, node.labels="support", ...)

Arguments

tree

an object of class "phylo".
node.labels

argument to be passed to midpoint.
...

optional arguments to be passed to midpoint.

Details

Midpoint rooting involves locating the midpoint of the longest path between any two tips and putting the root in that location.

The function midpoint_root performs the same operation as midpoint in the phangorn package, but uses no phangorn (Schliep, 2011) code internally.

The function midpoint.root is a pseudo S3 method for the object class "root" that exists because when midpoint was created in phangorn it was not defined as a generic method. This function merely points to midpoint and is being deprecated out.

Value

An object of class "phylo" containing a rooted phylogenetic tree.

Author(s)

Liam Revell [email protected]

References

Farris, J. (1972) Estimating phylogenetic trees from distance matrices. American Naturalist, 106, 645-667.

Paradis, E., J. Claude, and K. Strimmer (2004) APE: Analyses of phylogenetics and evolution in R language. Bioinformatics, 20, 289-290.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Schliep K. P. (2011) phangorn: phylogenetic analysis in R. Bioinformatics, 27, 592-593.

See Also

midpoint, reroot, root

Rotates all nodes of the tree to minimize the difference in order with a vector

Description

Rotates all the nodes of the tree to try and minimize the different between the order of the tips and the rank-order of a numeric vector x or (in the case of tipRotate) the actual integer vector, x.

Usage

minRotate(tree, x, ...)
tipRotate(tree, x, ...)

Arguments

tree

tree.
x

numeric vector.
...

optional arguments to be used by tipRotate. Presently optional arguments can be fn, function to be used to compute the distance between the order of the tip labels in tree and the numeric vector x (presently fn=function(x) x^2 by default); methods, the method or methods of tree traversal (can be "pre", "post", or c("pre","post"), for pre-, post-, or both pre- and post-order tree traversal); rotate.multi, whether to rotate multifurcations in all possible ways using rotate.multi (defaults to FALSE); and print, a logical argument specifying whether to print the search progress or to behave quietly. Only the option print is available for minRotate.

Details

Both minRotate and tipRotate are designed primarily to be used internally by other phytools functions and particularly by phylo.to.map (in the case of minRotate) and by cophylo (in the case of tipRotate).

Value

A node-rotated object of class "phylo".

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Finding the minimum (median) split in the posterior sample

Description

This function takes a phylogenetic tree and a list of splits and identifies the split with the smallest summed or summed squared distances to all the other splits.

Usage

minSplit(tree, split.list, method="sum", printD=FALSE)

Arguments

tree

an object of class "phylo".
split.list

either a matrix with two named columns, "node" and "bp"; a $mcmc matrix from evol.rate.mcmc(); or the entire raw output from evol.rate.mcmc().
method

an optional string indicating the criterion to minimize: options are "sum" and "sumsq".
printD

logical specifying whether to print distances to screen (FALSE by default).

Value

A list with the following elements:

node

node for the minimum split.
bp

location on the branch leading to node of the minimum split.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Revell, L. J., D. L. Mahler, P. Peres-Neto, and B. D. Redelings (2012) A new method for identifying exceptional phenotypic diversification. Evolution, 66, 135-146.

See Also

evol.rate.mcmc, posterior.evolrate

Computes modified Grafen edge lengths

Description

Computes modified Grafen (1989) edge lengths.

Usage

modified.Grafen(tree, power=2)
node.paths(tree, node)

Arguments

tree

object of class "phylo".
power

power to raise the depths of each node (in nodes).
node

node number for node.paths.

Details

This function computes modified Grafen edge lengths in which the length of the edge is determined not by the number of descendant leaves, but instead by the maximum number of node lengths in the path from the node to any leaf.

node.paths is used internally by modified.Grafen and computes the set of paths from a node to all tips descended from that node.

Value

An object of class "phylo" with edge lengths.

Author(s)

Liam Revell [email protected]

References

Grafen, A. (1989) The phylogenetic regression. Philosophical Transactions of the Royal Society of London. Series B. Biological Sciences, 326, 119-157.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

compute.brlen

Matrix representation parsimony supertree estimation

Description

This function estimates the MRP (matrix representation parsimony) supertree from a set of input trees (Baum 1992; Ragan 1992).

Usage

mrp.supertree(trees, method=c("pratchet","optim.parsimony"), ...)
compute.mr(trees, type=c("phyDat","matrix"))

Arguments

trees

an object of class "multiPhylo" that consists of a list of phylogenetic trees.
method

an argument specifying whether to optimize the tree using the phangorn parsimony optimizer pratchet or optim.parsimony.
type

for compute.mr, the type of object to return (e.g., "phyDat" or "matrix").
...

optional arguments - mostly to be passed to pratchet or optim.parsimony.

Details

mrp.supertree uses pratchet or optim.parsimony from the phangorn package (Schliep, 2011) for optimization, and prop.part from ape package (Paradis et al. 2004).

See pratchet or optim.parsimony for optional arguments, which vary slightly depending on the method. All optional arguments of these methods are available to the user with one exception. The argument tree in optim.parsimony is supplied instead as start. In addition to being an object of class "phylo", start can also be assigned the string values of "NJ" or "random", in which case either a neighbor-joining or random tree will be used as the starting tree for optimization.

The function compute.mr computes the matrix-representation matrix of the input trees. It is used internally by mrp.supertree, but can also be used to export an object that can be written to file if desired.

Value

An object of class "phylo" or "multiPhylo" that is the MP or set of MP MRP trees.

In the case of compute.mr, an object of class "phyDat" or a matrix.

Author(s)

Liam Revell [email protected]

References

Baum, B. R., (1992) Combining trees as a way of combining data sets for phylogenetic inference, and the desirability of combining gene trees. Taxon, 41, 3-10.

Felsenstein, J. (2004) Inferring Phylogenies. Sinauer.

Paradis, E., J. Claude, and K. Strimmer (2004) APE: Analyses of phylogenetics and evolution in R language. Bioinformatics, 20, 289-290.

Ragan, M. A. (1992) Phylogenetic inference based on matrix representation of trees. Molecular Phylogenetics and Evolution, 1, 53-58.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Schliep, K. P. (2011) phangorn: phylogenetic analysis in R. Bioinformatics, 27, 592-593.

See Also

exhaustiveMP, optim.parsimony, pratchet

Multiple matrix regression (partial Mantel test)

Description

This function conducting a multiple matrix regression (partial Mantel test) and uses Mantel (1967) permutations to test the significance of the model and individual coefficients. It also returns the residual and predicted matrices.

Usage

multi.mantel(Y, X, nperm=1000)

Arguments

Y

single "dependent" square matrix. Can be either a symmetric matrix of class "matrix" or a distance matrix of class "dist".
X

a single independent matrix or multiple independent matrices in a list. As with Y can be a object of class "matrix" or class "dist", or a list of such objects.
nperm

number of Mantel permutations to be used to compute a P-value of the test.

Details

Printing the object to screen will result in a summary of the analysis similar to summary.lm, but with p-values derived from Mantel permutations.

Methods residuals and fitted can be used to return residual and fitted matrices, respectively.

Value

An object of class "multi.mantel" consisting of the following elements:

r.squared

multiple R-squared.
coefficients

model coefficients, including intercept.
tstatistic

t-statistics for model coefficients.
fstatistic

F-statistic for the overall model.
probt

vector of probabilities, based on permutations, for tstatistic.
probF

probability of F, based on Mantel permutations.
residuals

matrix of residuals.
predicted

matrix of predicted values.
nperm

the number of permutations used.

Author(s)

Liam Revell [email protected]

References

Mantel, N. (1967) The detection of disease clustering and a generalized regression approach. Cancer Research, 27, 209-220.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Returns a list with phylogenetic VCV matrix for each mapped state

Description

Computes phylogenetic covariance matrices from a "simmap" object.

Usage

multiC(tree, internal=FALSE)

Arguments

tree

an object of class "simmap" consisting of a phylogeny with a mapped discrete character.
internal

logical value indicating whether or not internal nodes should be returned.

Details

This function takes a modified "phylo" object as input and returns a set of so-called phylogenetic covariance matrices (e.g., see vcv.phylo) as a list: one for each mapped state.

Used internally by multiple phytools functions, such as brownie.lite.

Value

A list of matrices.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

evolvcv.lite, read.simmap, vcvPhylo, vcv.phylo

Function to fit a multi-rate Brownian evolution model

Description

Fits a flexible multi-rate Brownian motion evolution model using penalized likelihood.

Usage

multirateBM(tree, x, method=c("ML","REML"), 
    optim=c("L-BFGS-B","Nelder-Mead","BFGS","CG"),
    maxit=NULL, n.iter=1, lambda=1, ...)

Arguments

tree

an object of class "phylo".
x

a named numerical vector. Names should correspond to the species names of tree.
method

method of optimization. Currently only method="ML".
optim

optimization routine to be used by optim. If more than one is specified and n.iter>1 then they will be alternated. (This is recommended to improve optimization.)
maxit

to be passed to optim. If set to maxit=NULL, the default value of maxit will be used, depending on the optimization method.
n.iter

number of times to reiterate failed optimization.
lambda

lambda penalty term. High values of lambda correspond to high penalty for rate heterogeneity among edges. Low values of lambda correspond to low penalty.
...

optional arguments.

Details

This function fits a flexible Brownian multi-rate model using penalized likelihood.

The model that is being fit is one in which the rate of Brownian motion evolution itself evolves from edge to edge in the tree under a process of geometric Brownian evolution (i.e., Brownian motion evolution on a log scale).

The penalty term, lambda, determines the cost of variation in the rate of evolution from branch to branch. If lambda is high, then the rate of evolution will vary relatively little between edges (and in the limiting case converge to the single-rate MLE estimate of the rate). By contrast, if the value of lambda is set to be low, then the rate of evolution can vary from edge to edge with relatively little penalty.

Decreasing the penalty term, however, is not without cost. As lambda is decreased towards zero, estimated rates will tend to become less and less accurate.

Value

An object of class "multirateBM".

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2021) A variable-rate quantitative trait evolution model using penalized-likelihood. PeerJ, 9, e11997.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

brownie.lite, evol.rate.mcmc

Examples

## Not run: 
## load data
data(sunfish.tree)
data(sunfish.data)
## convert from "simmap" to "phylo"
sunfish.tree<-as.phylo(sunfish.tree)
## extract character of interest
gw<-setNames(sunfish.data$gape.width,
    rownames(sunfish.data))
## run penalized-likelihood optimization
## lambda=0.1 is arbitrary
fitBM<-multirateBM(sunfish.tree,gw,
    lambda=0.01)
## print and plot the results
print(fitBM)
plot(fitBM,ftype="i",fsize=0.8,lwd=6,
    outline=TRUE)
## reset par
par(mar=c(5.1,4.1,4.1,2.1))
## End(Not run)

Computes Robinson-Foulds distance between a set of trees

Description

Computes the Robinson-Foulds (Robinson & Foulds 1981) distance between a set of trees in an object of class "multiPhylo".

Usage

multiRF(trees,quiet=FALSE,multi2di=FALSE)

Arguments

trees

object of class "multiPhylo" consisting of two or more fully bifurcating, unrooted trees. If trees are rooted, they will be unrooted.
quiet

logical argument indicating whether or not to run quietly. (Defaults to FALSE.)
multi2di

logical argument indicating whether or not to resolve multifurcating trees. (Defaults to FALSE.)

Details

Computes the Robinson-Foulds distance between all phylogenies in an object of class "multiPhylo". Uses prop.part internally for most of the heavy lifting.

Value

A matrix containing distances.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Robinson, D. R., Foulds, L. R. (1981) Comparison of phylogenetic trees. Mathematical Biosciences, 53, 131-147.

Compute the heights above the root of each node

Description

nodeHeights computes the height above the root for all nodes in the tree. nodeheight computes the height above the root for a single node.

Usage

nodeHeights(tree, ...)
nodeheight(tree, node, ...)

Arguments

tree

a phylogeny as an object of class "phylo".
node

for nodeheight, the node for which we want to compute a height above the root (or including the root edge, for root.edge=TRUE).
...

optional arguments - presently only root.edge, a logical value indicating whether or not to include the root edge length in the calculation of node heights.

Details

The function nodeHeights also gives a handy way to get the total length of the tree from the root to the highest tip which will be given by max(nodeHeights(tree)).

Generally speaking, nodeHeights will be faster if the heights of all or a large proportion of nodes is needed, whereas nodeheight will be faster if the height of one or a small number of nodes are needed.

Value

Either a matrix of the same dimensions as tree$edge containing the height above the root of each node in edge (for nodeHeights); or a single positive number (for nodeheight).

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

vcvPhylo

Examples

## load tree
data(vertebrate.tree)
## compute height of all nodes
H<-nodeHeights(vertebrate.tree)
print(H)
## compute total tree depth
max(H)

Add labels to a plotted "cophylo" object

Description

This function adds node, edge, or tip labels to the plotted trees of a "cophylo" object.

Usage

nodelabels.cophylo(..., which=c("left","right"))
edgelabels.cophylo(..., which=c("left","right"))
tiplabels.cophylo(..., which=c("left","right"))

Arguments

...

arguments to be passed to nodelabels, edgelabels, or tiplabels.
which

argument indicated which of the two plotted trees (the "left" or "right" tree) to be used.

Details

Note that the order of tips, edges, and nodes may be different in the object of class "cophylo" than they are in the original input trees, particularly if cophylo(...,rotate=TRUE) was used.

Author(s)

Liam Revell [email protected]

References

Paradis, E., J. Claude, and K. Strimmer (2004) APE: Analyses of phylogenetics and evolution in R language. Bioinformatics, 20, 289-290.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

cophylo, edgelabels, nodelabels, tiplabels

Phylogeny inference using the least squares method

Description

Phylogenetic inference using the method of least-squares (Cavalli-Sforza & Edwards, 1967).

Usage

optim.phylo.ls(D, stree=NULL, set.neg.to.zero=TRUE, fixed=FALSE,
   tol=1e-10, collapse=TRUE)

Arguments

D

a distance matrix.
stree

an optional starting tree for the optimization.
set.neg.to.zero

a logical value indicating whether to set negative branch lengths to zero (default TRUE).
fixed

a logical value indicating whether to estimate the topology - if TRUE only the branch lengths will be computed.
tol

a tolerance value used to assess whether the optimization has converged.
collapse

a logical indicating whether to collapse branches with zero length.

Details

Function uses nni from the phangorn package (Schliep 2011) to conduct NNIs for topology estimation.

Since topology optimization is performed using NNIs, convergence to the true least-squares topology is not guaranteed. It is consequently probably wise to start with a very good tree - such as a NJ tree.

Value

An object of class "phylo" that (may be) the least-squares tree with branch lengths; also returns the sum of squares in attr(tree,"Q-score").

Author(s)

Liam Revell [email protected]

References

Cavalli-Sforza, L. L., and A. W. F. Edwards. (1967) Phylogenetic analysis: Models and estimation procedures. American Journal of Human Genetics, 19, 233-257.

Felsenstein, J. (2004) Inferring Phylogenies. Sinauer.

Paradis, E., J. Claude, and K. Strimmer. (2004) APE: Analyses of phylogenetics and evolution in R language. Bioinformatics, 20, 289-290.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Schliep, K. P. (2011) phangorn: phylogenetic analysis in R. Bioinformatics, 27, 592-593.

See Also

exhaustiveMP, nni

Order the columns of mapped.edge to match across trees

Description

Orders the levels of a mapped character to match across trees in a "multiSimmap" object.

Usage

orderMappedEdge(trees, ordering=NULL)

Arguments

trees

object of class "phylo" or "multiPhylo".
ordering

ordering for the columns of $mapped.edge. If NULL, then an alphabetical order is assumed. Options are "alphabetical", "numerical", or any specific ordering of the mapped traits (e.g., c("A","B","C").

Details

This function takes a an object of class "multiSimmap" with a mapped discrete character (e.g., see make.simmap and sorts the columns of each tree$mapped.edge element to have the same state ordering.

This is handy if we want to, for instance, run brownie.lite on a set of mapped trees, and then average the fitted parameter values across trees. The function also works for a single tree.

Value

An object of class "simmap" or (normally) "multiSimmap".

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Paint sub-trees with a discrete character

Description

Paints regimes on a tree to create an object of class "simmap" with mapped regimes.

Usage

paintSubTree(tree, node, state, anc.state="1", stem=FALSE)
paintBranches(tree, edge, state, anc.state="1")

Arguments

tree

a phylogenetic tree as an object of class "phylo" or a modified object with mapped character traits.
node

an integer specifying the node number tipward of which the function should paint the derived state.
edge

an integer or vector of integers specifying the node or tip numbers of the edges that should be painted in paintBranches.
state

a string (or numeric value) specifying the state to paint on the tree tipward of node.
anc.state

the ancestral state to use; will only be applied if there are presently no character values mapped on the tree.
stem

logical or numeric value indicating whether to use the derived state on the stem leading to node (or not, if stem=FALSE), or, alternatively, what fraction of the stem should be assigned to the derived clade. Note that for tip clades stem=FALSE is not allowed.

Details

These functions map or "paint" arbitrary (i.e., user-specified) discrete character histories on the tree.

paintSubTree paints the clade downstream of node with a particular state; whereas paintBranches paints only a specified branch.

Value

An object of class "simmap" that contains the specified paintings as a mapped discrete character.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

make.simmap, read.simmap, plotSimmap, sim.history

Paste two trees together

Description

Internal function for posterior.evolrate.

Usage

paste.tree(tr1, tr2)

Arguments

tr1

receptor tree.
tr2

donor clade.

Details

Primarily designed as an internal function for posterior.evolrate; however, can be used to graft a clade onto a receptor tree at the "sticky tip" labeled with "NA".

The donor clade needs to have a root edge, even if it is zero length.

Value

A tree.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Examples

tr1<-rtree(10)
tr2<-rtree(10)
tr1$tip.label[1]<-"NA"
tr2$root.edge<-0
tr3<-paste.tree(tr1,tr2)

Simulate pure-birth or birth-death stochastic tree or trees

Description

This function simulates stochastic birth-death trees.

Simulation can be performed conditioning on n, on t, or on both simultaneously. If both, then (for optional argument method="rejection") rejection sampling is performed whereby trees are simulated given b and t until a tree containing n taxa is found. The giving-up point can be set using the optional argument max.count.

Simulations can also be performed in continuous time (the default) or discrete time; the difference being that wait times in the continuous-time simulation come from the exponential distribution; whereas waiting times in discrete-time simulations come from the geometric distribution. In addition, discrete-time simulations allow for the possibility that multiple speciation events can occur at (exactly) the same time, so long as they are on separate branches. Finally, sometimes for stopping criterion n in discrete-time there will be a number of tips different from n. This indicates that the last event contained more than one speciation event, and a warning is printed.

method="direct" is presently experimental. It does not really perform direct sampling; however waiting times & birth or death events are sampled first - with only wait-times consistent with n and t being retained. This rejection sampling occurs one layer earlier than for method="rejection". This results in a significant (several-fold) speed-up of the code and enables sampling conditioned on n and t simultaneously for much higher b and d. At the present time, extant.only=TRUE does not work for this mode, nor does type="discrete".

Note that if ape=FALSE, then the function will run faster, and the tree is theoretically compatible with the ape "phylo" standard; however some downstream errors with functions such as bind.tree have been observed.

Lastly, under the taxon number stopping criterion (n) for a non-zero extinction rate (d>0) sometimes a tree containing fewer than n extant tips is returned because it has gone completely extinct before the end of the simulation.

Usage

pbtree(b=1, d=0, n=NULL, t=NULL, scale=NULL, nsim=1, type=c("continuous",
   "discrete"), ...)

Arguments

b

birth rate or speciation rate for type="continuous"; the probability of speciating per time-step for type="discrete".
d

death rate or extinction rate for type="continuous"; the probability of going extinct per time-step for type="discrete".
n

desired number of species (i.e., taxa-stop criterion).
t

total time for simulation (i.e., time-stop criterion).
scale

if set, rescales tree to have total length scale.
nsim

number of simulated trees to return.
type

string to indicate whether to simulate trees in continuous or discrete time. If the former, then wait times between speciation events are drawn from an exponential distribution; whereas if the latter then wait times comes from a geometric distribution.
...

optional arguments including ape, a logical value indicating whether to return nodes in a 'ape' compatible ordering (default is TRUE); extant.only a logical value indicating whether or not to return only extant species (defaults to FALSE); max.count a numeric value indicating the maximum number of iterations to run is sampling conditioned on both n and t (defaults to 1e5); method gives the method used for simultaneously conditioning on n and t - options are "rejection" and "direct"; tip.label, a vector of tip labels (only works for n!=NULL); and, finally, quiet, a logical value indicating whether or not to suppress certain message (defaults to FALSE).

Details

Simulate stochastic birth-death trees.

Value

A tree or set of trees as an object of class "phylo" or "multiPhylo", respectively.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Examples

## simulate a pure-birth tree with 400 tips
## scaled to a length of 1.0
tree<-pbtree(n=400,scale=1)
## simulate a pure-birth tree conditioning on n & t
tt<-log(50)-log(2)
tree<-pbtree(n=50,t=tt)

Phylogenetic regression with intraspecific sampling error

Description

Phylogenetic regression with within-species sampling error following Ives et al. (2007).

Usage

pgls.Ives(tree, X, y, Vx=NULL, Vy=NULL, Cxy=NULL, lower=c(1e-8,1e-8),
    fixed.b1=NULL)
pgls.SEy(model, data, corClass=corBrownian, tree,
    se=NULL, method=c("REML","ML"), interval=c(0,1000), ...)

Arguments

tree

a phylogeny as an object of class "phylo".
X

a named vector containing a single independent variable (multiple independent variables to be added in future). X can contain the species means, or a single long vector containing the sample of values for each species. In the latter case the names(X) will be repeating - all samples from the same species should have the same name.
y

vector the dependent variable. Can be species means or individual values, as for X.
Vx

sampling variances for X. If NULL, then the within-species variance is computed from the data assuming that individual samples, not species means, have been provided in X.
Vy

sampling variances for y. If NULL, then the within-species variance is computed from the data assuming that individual samples, not species means, have been provided in y.
Cxy

sampling covariances between X and y. This will also be computed from the data if Cxy==NULL. Note than in this case - but not for the calculation of Vx and Vy, the same number of observations and the same ordering must be provided for X and y. If this is not the case, then it is assumed that different individuals have been sampled for X and y and thus Cxy is assumed to be zero for all species.
lower

vector specifying the lower bounds for estimation for σx2\sigma_x^2 and σy2\sigma_y^2, respectively. (Must be > 0.)
fixed.b1

fixed regression slope, β\beta. Usually set to zero for null hypothesis testing.
model

model to fit. (For pgls.SEy.)
data

data frame. (For pgls.SEy.)
corClass

correlation structure. (For pgls.SEy.)
se

vector of standard errors in y. (For pgls.SEy.)
method

optimization method. (For pgls.SEy.)
interval

interval over which to perform optimization. (For pgls.SEy.)
...

optional arguments. (For pgls.SEy.)

Details

pgls.Ives fits the phylogenetic regression model with within-species sampling error following Ives et al. (2007).

pgls.SEy fits a simpler model in which only sampling error in y is taken into account. This function uses gls from the nlme package internally for optimization and returns an object of class "gls" that is compatible with all methods for that object class.

In the case of pgls.Ives, only the bivariate regression model is implemented. Note that some problems have been reported with the optimization algorithm for this model, which is simple and thus may fail to find the ML solution.

In the case of pgls.SEy the user can (theoretically) specify any class of linear model permitted by gls.

Value

In the case of pgls.Ives, an object of class "pgls.Ives" with the following elements:

beta

a vector or matrix of regression coefficients.
sig2x

fitted BM rate for X.
sig2y

fitted BM rate for y.
a

fitted ancestral states for X and y.
logL

log-likelihood.
convergence

a value for convergence. convergence=0 is good; see optim for more details.
message

a message for convergence.

In the case of pgls.SEy, an object of class "gls".

Author(s)

Liam Revell [email protected]

References

Ives, A. R., P. E. Midford, and T. Garland Jr. (2007) Within-species measurement error in phylogenetic comparative methods. Systematic Biology, 56, 252-270.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

brownie.lite, phylosig, phyl.resid

Plot traitgram (phenogram)

Description

Plots a phylogenetic traitgram (Evans et al., 2009).

Usage

phenogram(tree, x, fsize=1.0, ftype="reg", colors=NULL, axes=list(),
   add=FALSE, ...)

Arguments

tree

an object of class "phylo", with or without a mapped discrete character.
x

a vector containing the states at the tips or the states at all the tips and the internal nodes of the tree.
fsize

relative font size for tip labels.
ftype

font type - options are "reg", "i" (italics), "b" (bold), or "bi" (bold-italics).
colors

colors for plotting the mapped character (if available) in tree. If no character is mapped on the tree, then a single color for all the branches of the tree can be provided.
axes

list of axis dimensions. Items are time and trait.
add

optional logical value indicating whether to add to an open plot. If TRUE, then new axes will not be plotted.
...

optional arguments including xlim, ylim, log, main, sub, xlab, ylab, asp, type, lty, lwd, offset, and digits are as in plot.default or par. Note that axes overrides xlim and ylim. spread.labels is a logical value indicating whether or not to minimize tip label overlap (default is TRUE); spread.cost is a numeric vector indicating the relative penalty to be used for label overlap and deviance, respectively (if spread.labels=TRUE); spread.range is the range over which to (potentially) spread the labels - note that if labels do not overlap, not all of that range will be used; finally, link is a numeric value by which to offset the tip labels, linking them to the tips with a dashed line (default is 0, if spread.labels=FALSE, or 10% of the total tree length otherwise). The optional argument offsetFudge "fudges" the computation of label offset in scaling xlim. It is 1.37, which is the correct fudge in the Windows R GUI, but this may need to be changed in other systems. hold indicates whether (or not) the output to the graphical device should be held using dev.hold before plotting (defaults to hold=TRUE). quiet suppresses some system messages if set to quiet=TRUE.

Details

Function plots a traitgram (Evans et al. 2009), that is, a projection of the phylogenetic tree in a space defined by phenotype (on the y axis) and time (on the x). If a discrete character is mapped on the tree this will also be plotted.

For spread.labels=TRUE numerical optimization is performed to optimize the distribution of the labels vertically, where the solution depends on the vector spread.cost containing the cost of overlap (first) and the cost of deviation from the vertical position of the tip. Note that because this is done via numerical optimization, plotting may hang briefly while the best solution is found (especially for large trees).

Value

Plots a traitgram, optionally with a mapped discrete character, and (invisibly) returns a matrix containing the coordinates of the plotted tip labels.

Author(s)

Liam Revell [email protected]

References

Evans, M. E. K., Smith, S. A., Flynn, R. S., Donoghue, M. J. (2009) Climate, niche evolution, and diversification of the "bird-cage" evening primroses (Oenothera, sections Anogra and Kleinia). American Naturalist, 173, 225-240.

Revell, L. J. (2013) Two new graphical methods for mapping trait evolution on phylogenies. Methods in Ecology and Evolution, 4, 754-759.

Revell, L. J. (2014) Graphical methods for visualizing comparative data on phylogenies. Chapter 4 in Modern phylogenetic comparative methods and their application in evolutionary biology: Concepts and practice (L. Z. Garamszegi ed.), pp. 77-103.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Revell, L. J., K. Schliep, E. Valderrama, and J. E. Richardson (2018) Graphs in phylogenetic comparative analysis: Anscombe's quartet revisited. Methods in Ecology and Evolution, 9, 2145-2154.

Examples

## load data from Garland et al. (1992)
data(mammal.tree)
data(mammal.data)
## extract character of interest
ln.bodyMass<-log(setNames(mammal.data$bodyMass,
  rownames(mammal.data)))
## plot traitgram
phenogram(mammal.tree,ln.bodyMass,ftype="i",
  spread.cost=c(1,0),fsize=0.7,color=palette()[4],
  xlab="time (ma)",ylab="log(body mass)",las=1)

Phylogenetic canonical correlation analysis

Description

Phylogenetic canonical correlation analysis, following Revell & Harrison (2008).

Usage

phyl.cca(tree, X, Y, lambda=1.0, fixed=TRUE)

Arguments

tree

a phylogenetic tree in "phylo" format.
X

a data matrix with traits in columns.
Y

data matrix with traits in columns, to be correlated with X.
lambda

optionally, a (fixed) value for λ\lambda.
fixed

optionally, a logical value indicating whether or not to estimate λ\lambda using likelihood.

Details

(Optional) joint optimization of λ\lambda is performed using optimize on the interval (0,1).

Value

An object of class "phyl.cca" containing the following elements:

cor

canonical correlations.
xcoef

coefficients for the canonical variables for X.
ycoef

coefficients for the canonical variables for Y.
xscores

matrix with the canonical scores for X.
yscores

matrix with the canonical scores for Y.
chisq

vector of χ2\chi^2 values.
p

P-values for the hypothesis test that the ith and all subsequent correlations are zero.

Author(s)

Liam Revell [email protected]

References

Revell, L. J., Harrison, A. S. (2008) PCCA: A program for phylogenetic canonical correlation analysis. Bioinformatics, 24, 1018-1020.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

phyl.pca

Phylogenetic paired t-test

Description

Phylogenetic paired t-test following Lindenfors et al. (2010).

Usage

phyl.pairedttest(tree, x1, x2=NULL, se1=NULL, se2=NULL, lambda=1.0, h0=0.0,
   fixed=FALSE, ...)

Arguments

tree

a phylogeny as an object of class "phylo".
x1

data vector for first trait, or matrix with two traits in columns.
x2

data vector for second trait (or null if x1 is a matrix).
se1

standard errors for x1.
se2

standard errors for x2.
lambda

starting value for Pagel's λ (or fixed value, if fixed=TRUE).
h0

null hypothesis (to be tested) for the mean difference between x1 and x2.
fixed

logical value specifying whether or not to optimize λ.
...

optional arguments.

Details

This function conducts a phylogenetic paired t-test, roughly following Lindenfors et al. (2010).

This is not a phylogenetic ANOVA, in which we want to compare the means of different sets of species on the tree. Instead, we are interested in the difference between two characters, or two measures of a character within a species, and we want to know if this difference is significantly different from zero controlling for the phylogenetic non-independence of species.

Likelihood optimization is performed using optim with method="L-BFGS-B" with box constraints on λ (0,1).

Value

An object of class "phyl.pairedttest" with the following elements:

dbar

phylogenetic mean difference.
se

standard error of dbar.
sig2

estimated evolutionary variance (of the difference).
lambda

fitted (or fixed) value of λ.
logL

log-likelihood of the fitted model.
t.dbar

t-value ((dbar-h0)/se where se is computed from the Hessian).
P.dbar

P-value.
df

the degrees of freedom.
h0

the null hypothesis that was tested.

Author(s)

Liam Revell [email protected]

References

Lindenfors, P., L. J. Revell, and C. L. Nunn (2010) Sexual dimorphism in primate aerobic capacity: A phylogenetic test. J. Evol. Biol., 23, 1183-1194.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Phylogenetic principal components analysis

Description

This function performs phylogenetic PCA following Revell (2009).

Usage

phyl.pca(tree, Y, method="BM", mode="cov", ...)
## S3 method for class 'phyl.pca'
biplot(x, ...)
scores(object, ...)
## S3 method for class 'phyl.pca'
scores(object, ...)
as.princomp(x, ...)
as.prcomp(x, ...)

Arguments

tree

phylogeny as an object of class "phylo".
Y

data matrix with traits in columns.
method

method to obtain the correlation structure: can be "BM" or "lambda".
mode

is the mode for the PCA: can be "cov" or "corr".
x

object of class "phyl.pca" for biplot, as.princomp, and as.prcomp methods.
object

object of class "phyl.pca" for scores method.
...

for S3 plotting method biplot.phyl.pca, other arguments to be passed to biplot.

Details

If method="lambda" then λ\lambda will be optimized on the interval (0,1) using optimize. Optimization method can be set using the option opt which can take values "ML", "REML", or "fixed". If the last of these is selected than the user should also specify a value of λ\lambda to use via the argument lambda.

S3 methods (print, summary, and biplot) are modified from code provided by Joan Maspons and are based on the same methods for objects of class "prcomp". Function biplot now permits the argument choices to be supplied, which should be a vector of length two indicated the two PC axes to be plotted.

S3 method scores extracts or computes (for a matrix of newdata) PC scores given an object of class "phyl.pca".

S3 methods as.prcomp and as.princomp convert the object of class "phyl.pca" to objects of class "prcomp" and "princomp", respectively.

Value

An object of class "phyl.pca" consisting of a list with some or all of the following elements:

Eval

diagonal matrix of eigenvalues.
Evec

matrix with eigenvectors in columns.
S

matrix with scores.
L

matrix with loadings.
lambda

fitted value of λ\lambda (method="lambda" only).
logL

log-likelihood for λ\lambda model (method="logL" only).

Author(s)

Liam Revell [email protected], Joan Maspons

References

Revell, L. J. (2009) Size-correction and principal components for interspecific comparative studies. Evolution, 63, 3258-3268.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

phyl.cca, phyl.resid, prcomp, princomp

Examples

## load data from Mahler et al. (2010)
data(anoletree)
data(anole.data)
## run phylogenetic PCA
anole.pca<-phyl.pca(anoletree,anole.data)
print(anole.pca)
## plot results
plot(anole.pca)
biplot(anole.pca)

Phylogenetic size-correction via GLS regression

Description

Computes the residuals from the phylogenetic regression of multiple y variables (in a matrix) on a single x.

Usage

phyl.resid(tree, x, Y, method="BM")

Arguments

tree

a phylogenetic tree in "phylo" format.
x

vector containing the single independent variable (e.g., size), or matrix with multiple independent variables in columns.
Y

vector or matrix with one or multiple dependent variables in columns.
method

method to obtain the correlation structure: can be "BM" or "lambda".

Details

This function fits one or multiple phylogenetic regressions (depending on the number of columns in Y) and computes the residuals. Designed for phylogenetic size correction using GLS regression (e.g., Revell 2009).

Optionally fits λ\lambda for each regression model. Likelihood optimization of λ\lambda is performed for method= "lambda" using optimize on the interval (0,1).

This function is theoretically redundant with residuals applied to a "gls" object class in which the correlation structure is based on corBrownian or corPagel; however some users may find this method simpler, and it provides a good way to cross-check your results & make sure that you are using gls correctly.

Value

A list with the following elements:

beta

a vector or matrix of regression coefficients.
resid

a vector or matrix of residuals for species.
lambda

a vector of λ\lambda values (method="lambda" only).
logL

a vector of log-likelihoods (method="lambda" only).

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2009) Size-correction and principal components for interspecific comparative studies. Evolution, 63, 3258-3268.

Revell, L. J. (2010) Phylogenetic signal and linear regression on species data. Methods in Ecology and Evolution, 1, 319-329.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

phyl.pca, gls

Phylogenetic reduced major axis (RMA) regression

Description

Phylogenetic reduced major axis (RMA) regression.

Usage

phyl.RMA(x, y, tree, method="BM", lambda=NULL, fixed=FALSE, h0=1.0)
## S3 method for class 'phyl.RMA'
coef(object, ...)
## S3 method for class 'phyl.RMA'
plot(x, ...)

Arguments

x

vector with names. In the case of the S3 plot method x is an object of class "phyl.RMA".
y

vector with names.
tree

a phylogenetic tree in "phylo" format.
method

method to obtain the correlation structure: can be "BM" or "lambda".
lambda

value of lambda for fixed λ\lambda.
fixed

logical value indicating whether or not λ\lambda should be optimized using likelihood.
h0

null hypothesis for β\beta. Defaults to 1.0. Note that a null hypothesis of 0.0 is not allowed.
object

for coef method, an object of class "phyl.RMA".
...

optional arguments for S3 methods.

Details

Optionally jointly estimates λ\lambda if method="lambda". Likelihood optimization of λ\lambda is performed using optimize on the interval (0,1).

The statistical hypothesis testing is based on Clarke (1980; reviewed in McArdle 1988), which differs from some other implementations of non-phylogenetic major axis regression in R.

Note that some statistician think there is never a condition in which a reduced-major-axis regression is appropriate.

Value

An object of class "phyl.RMA" consisting of a list with the following elements:

RMA.beta

a vector of RMA regression coefficients.
V

a VCV matrix for the traits.
lambda

fitted value of λ\lambda (method="lambda" only).
logL

log-likelihood (method="lambda" only).
test

a vector containing results for hypothesis tests on β\beta.
resid

a vector of residuals for y given x.

Author(s)

Liam Revell [email protected]

References

Clarke, M. R. B. (1980) The reduced major axis of a bivariate sample. Biometrika, 67, 441-446.

McArdle, B. H. (1988) The structural relationship: Regression in biology. Can. J. Zool., 66, 2329-2339.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

phyl.cca, phyl.pca, phyl.resid

Examples

## load data from Garland et al. (1992)
data(mammal.data)
data(mammal.tree)
## pull out & log transform variables
lnBodyMass<-setNames(log(mammal.data$bodyMass),
  rownames(mammal.data))
lnHomeRange<-setNames(log(mammal.data$homeRange),
  rownames(mammal.data))
## fit RMA regression & print results
fitted.rma<-phyl.RMA(lnBodyMass,lnHomeRange,
  mammal.tree)
print(fitted.rma)
## plot fitted RMA
par(las=1,bty="n")
plot(fitted.rma,las=1,bty="n")

Compute evolutionary VCV matrix for a tree & dataset

Description

Internal function for phyl.pca.

Usage

phyl.vcv(X, C, lambda)

Arguments

lambda

value for λ\lambda transformation.
X

data matrix.
C

matrix containing the height above the root of each pair of species in the tree. Typically this will have been produced by calling vcv.phylo.

Details

Primarily designed as an internal function for phyl.pca; phyl.vcv can be used to compute the phylogenetic trait variance-covariance matrix given a phylogenetic VCV, λ\lambda, and a data matrix.

This function should not be confused with vcv.phylo in the ape package (although one of the objects returned is the output of vcv.phylo).

Note that prior to phytools 2.1-0 the matrix X was not sorted to match the rows of C since that was assumed to have been done in the function calling phyl.vcv internally; however, I recently discovered that this had caused the function to be used incorrectly resulting in a paper correction. This is now fixed such that X is checked for row names and (if present) C is sorted to match the rows of X. Hopefully this does not cause any problems for other functions using phyl.vcv!

Value

A list containing three elements, as follows: C, the matrix vcv.phylo transformed by lambda; R, the among trait variance-covariance matrix for the data in X; and alpha, a vector of ancestral states at the root node of the tree.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Phylogenetic ANOVA and post-hoc tests

Description

Simulation based phylogenetic ANOVA following Garland et al. (1993), with post-hoc tests.

Usage

phylANOVA(tree, x, y, nsim=1000, posthoc=TRUE, p.adj="holm")

Arguments

tree

a phylogenetic tree in "phylo" format.
x

a vector containing the groups.
y

a vector containing the response variable (continuously valued).
nsim

an integer specifying the number of simulations (including the observed data).
posthoc

a logical value indicating whether or not to conduct posthoc tests to compare the mean among groups.
p.adj

method to adjust P-values for the posthoc tests to account for multiple testing. Options same as p.adjust.

Details

This function performs the simulation-based phylogenetic ANOVA of Garland et al. (1993) and (optionally) conducts all posthoc comparisons of means among groups (also obtaining the P-values by phylogenetic simulation).

This function uses a little bit of code from both phy.anova in the geiger package and pairwise.t.test.

Value

An object of class "phylANOVA" containing the following elements:

F

F from observed data.
Pf

P-value for F from simulation.
T

matrix of t-values.
Pt

matrix of multiple test corrected P-values from posthoc t-tests.

Author(s)

Liam Revell [email protected]

References

Garland, T., Jr., A. W. Dickerman, C. M. Janis, & J. A. Jones (1993) Phylogenetic analysis of covariance by computer simulation. Systematic Biology, 42, 265-292.

Harmon, L. J., J. T. Weir, C. D. Brock, R. E. Glor, W. Challenger (2008) GEIGER: investigating evolutionary radiations. Bioinformatics, 24, 129-131.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

anova, pairwise.t.test

Creates a phylogenetic heat map

Description

Multivariate phylogenetic heatmap plot.

Usage

phylo.heatmap(tree, X, fsize=1, colors=NULL, standardize=FALSE, ...)

Arguments

tree

an object of class "phylo".
X

a matrix containing data for multiple continuous characters in which rownames correspond to the tip labels of the tree.
fsize

an integer or vector of length 3 containing the font size for the tip labels, the trait labels, and the legend text. (If a single integer is supplied, then the value will be recycled.)
colors

a vector of colors to be passed to image. Can be a function call (e.g., heat.colors(n= 200)[200:1]).
standardize

a logical value indicating whether or not to standardize each column of X to have the same variance & mean prior to analysis.
...

optional arguments. So far these include: legend, a logical value indicating whether or not to plot a figure legend (defaults to legend=TRUE); labels, a logical value indicating whether or not to plot trait labels (defaults to labels=TRUE); split, a numeric vector indicating the fraction of the horizontal dimension to use for the tree & heatmap, respectively (defaults to split=c(0.5,0.5)); xlim, ylim, & mar, defined as in par; and ftype, lwd, and pts as defined in plotSimmap.

Value

Function creates a plot.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Examples

## load data
data(anoletree)
data(anole.data)
## compute phylogenetic residuals
anole.data<-as.matrix(anole.data)
anole.resids<-cbind(anole.data[,1],
  phyl.resid(anoletree,anole.data[,1,drop=FALSE],
    anole.data[,2:ncol(anole.data)])$resid)
colnames(anole.resids)[1]<-"SVL"
## plot phylogenetic heatmap
phylo.heatmap(anoletree,anole.resids,
  split=c(0.7,0.3),fsize=c(0.4,0.8,0.8),
  standardize=TRUE,pts=FALSE)
par(mar=c(5.1,4.1,4.1,2.1)) ## reset margins to default

Phylogenetic imputation for multivariate continuous character data

Description

This function performs phylogenetic multiple imputation using maximum likelihood.

Usage

phylo.impute(tree, X, ...)

Arguments

tree

an object of class "phylo".
X

data matrix with species names as row labels. Missing data to be imputed should be coded NA.
...

optional arguments.

Details

This function performs phylogenetic imputation in which the evolution of the characters in X is assumed to have occurred by correlation multivariate Brownian motion.

Missing values are imputed by maximizing their likelihood jointly with the parameters of the Brownian model. The function evol.vcv is used internally to compute the likelihood.

Note that the Rphylopars package also does phylogenetic imputation for multivariate trait data and it seems to be much faster.

Value

An object of class "phylo.impute" consisting of a complete data frame with missing values imputed.

Since optimization is performed numerically using likelihood, a summary of the optimization can be seen by evaluating attr(object,"optim"), in which object is of class "phylo.impute".

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

evol.vcv

Plot tree with tips linked to geographic coordinates

Description

Project a phylogeny on a geographic map.

Usage

phylo.to.map(tree, coords, rotate=TRUE, ...)
## S3 method for class 'phylo.to.map'
plot(x, type=c("phylogram","direct"), ...)

Arguments

tree

an object of class "phylo".
coords

a matrix containing the latitude (in column 1) and the longitude of all tip species in the tree. The row names should be the same as tree$tip.label; however, more than one set of coordinates per species can be supplied by duplicating some row names.
rotate

a logical value indicating whether or not to rotate nodes of the tree to better match longitudinal positions.
x

for plot.phylo.to.map, an object of class "phylo.to.map".
type

a string indicating whether to map the tips of the tree onto a geographic map from a square phylogram (type="phylogram") or to project the tree directly onto the map (type="direct").
...

various optional arguments. For the function phylo.to.map, which first creates an object of the special class "phylo.to.map" and then (optionally) plots this object, arguments include: database and regions (see map), as well as any arguments that should be passed to plot.phylo.to.map internally. For phylo.to.map, optional arguments xlim and ylim, which control the plot area for the map; fsize for the font size of plot labels and ftype for the font type (following plotSimmap; split which controls the proportion of vertical (or horizontal) space for the tree (first) and map, in a vector; psize the size of the plotted points on the map - or cex.points, a vector contain the size of the tip points and geographic coordinate points, respectively; from.tip a logical value indicating whether to plot the linking lines from the tips (if TRUE) or from the end of the tip label, the default; colors, a single value or a vector of colors for the points and the linking lines; pch a single value or a vector of point types; lwd and lty for the linking lines; and pts a logical value indicating whether or not to plot points at the tips of the tree. mar and asp are as in par.

Details

phylo.to.map creates an object of class "phylo.to.map" and (optionally) plots that object.

plot.phylo.to.map plots an object of class "phylo.to.map" in which the tips of the tree point to coordinates on a geographic map.

Value

phylo.to.map creates an object of class "phylo.to.map" and (if plot=TRUE) plots a phylogeny projected onto a geographic map.

plot.phylo.to.map plots on object of class "phylo.to.map".

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2014) Graphical methods for visualizing comparative data on phylogenies. Chapter 4 in Modern phylogenetic comparative methods and their application in evolutionary biology: Concepts and practice (L. Z. Garamszegi ed.), pp. 77-103.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Examples

## generally recommend using higher resolution map
## e.g., from mapdata package
data(tortoise.tree)
data(tortoise.geog)
tortoise.phymap<-phylo.to.map(tortoise.tree,
  tortoise.geog,plot=FALSE,direction="rightwards",
  regions="Ecuador")
plot(tortoise.phymap,direction="rightwards",pts=FALSE,
  xlim=c(-92.25,-89.25),ylim=c(-1.8,0.75),ftype="i",
  fsize=0.8,lty="dashed",map.bg="lightgreen",
  colors="slategrey")
## reset margins
par(mar=c(5.1,4.1,4.1,2.1))

Converts tree to backbone or vice versa

Description

Converts between "phylo" and "backbonePhylo".

Usage

phylo.toBackbone(x, trans, ...)
backbone.toPhylo(x)

Arguments

x

an object of class "phylo" (for the function phylo.toBackbone), or an object of the special class "backbonePhylo" (for backbone.toPhylo).
trans

data frame containing the attributes necessary to translate a backbone tree to an object of class "backbonePhylo". The data frame should contain the following variables: tip.label: the tip labels in the input tree (not all need be included); clade.label: labels for the unobserved subtrees; N: number of species in each subtree; and depth: desired depth of each subtree. depth for each terminal taxon in x cannot be greater than the terminal edge length for that taxon.
...

optional arguments.

Value

Either an object of class "phylo" or an object of class "backbonePhylo", depending on the method.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

plot.backbonePhylo

Compute design matrix for least squares analyses

Description

Primarily an internal function for optim.phylo.ls, this function creates a design matrix for least squares phylogenetic analysis.

Usage

phyloDesign(tree)

Arguments

tree

phylogenetic tree.

Details

This function returns a matrix containing the edges in the tree (in columns) and pairs of tip node numbers (in rows). Values in the matrix are either 1 if the edge is on the shortest path between the two tips; and 0 otherwise. Probably do not use unless you know what you're doing.

Value

A matrix.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Creates phylomorphospace plot

Description

Project a phylogeny into morphospace.

Usage

phylomorphospace(tree, X, A=NULL, label=c("radial","horizontal","off"),
    control=list(), ...)
project.phylomorphospace(tree, X, nsteps=200, sleep=0,
    direction=c("to","from","both"), ...)

Arguments

tree

a phylogenetic tree in "phylo" format, or a modified "phylo" object with a mapped discrete character.
X

an n x 2 matrix of tip values for two characters in n species.
A

an optional m x 2 matrix (for m nodes) of values for two traits at internal nodes in the tree - if not supplied, these values will be estimated using fastAnc.
label

string indicating whether to plot the tip labels in the same direction as the terminal edge (label="radial"), horizontally label="horizontal", or not at all "off". label=TRUE and label=FALSE are also acceptable, for compatibility with phytools <= 0.3-03.
control

a list containing the following optional control parameters: col.edge: a vector of edge colors; and col.node: a vector of node colors.
nsteps

for project.phylomorphospace the number of frames in the animation between the phylogeny & the phylomorphospace or vice versa.
sleep

for project.phylomorphospace the time between frames.
direction

for project.phylomorphospace whether to morph "to" a phylomorphospace, "from" a phylomorphospace, or there & back again ("both").
...

optional arguments for plotting, including xlim, ylim, xlab, ylab, lwd, colors, fsize, and node.by.map. colors is only used when there is a mapped discrete character on the tree, in which case control$col.edge is ignored. fsize is relative to the default, which is textxy(...,cx=0.75). node.by.map is a logical value (defaults to FALSE which tells the function whether or not to plot the node colors using the colors of the mapped discrete character. Setting this option to TRUE will cause control$col.node to be ignored. node.size is a vector containing the point size relative to the default (see par for plotted internal nodes and tips, respectively. Defaults to node.size=c(1,1.3). If only one number is provided it will be recycled. axes is a logical value indicating whether or not axes should be plotted (see plot.default. Finally, add indicates whether to add the phylomorphospace to the current plot.

Details

This function creates a phylomorphospace plot (a projection of the tree into morphospace) for two characters following Sidlauskas (2008; Evolution). It will also plot a discrete character mapped on tree.

project.phylomorphospace animates the phylomorphospace projection.

Value

This function creates a phylomorphospace plot

Author(s)

Liam Revell [email protected]

References

Paradis, E., J. Claude, and K. Strimmer (2004) APE: Analyses of phylogenetics and evolution in R language. Bioinformatics, 20, 289-90.

Revell, L. J. (2014) Graphical methods for visualizing comparative data on phylogenies. Chapter 4 in Modern phylogenetic comparative methods and their application in evolutionary biology: Concepts and practice (L. Z. Garamszegi ed.), pp. 77-103.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Sidlauskas, B. (2008) Continuous and arrested morphological diversification in sister clades of characiform fishes: A phylomorphospace approach. Evolution, 62, 3135-3156.

Examples

## load tree & data from Revell & Collar (2009)
data(sunfish.tree)
data(sunfish.data)
## set colors for mapped discrete character
cols<-setNames(c("blue","red"),
    levels(sunfish.data$feeding.mode))
phylomorphospace(sunfish.tree,sunfish.data[,3:2],
    colors=cols,bty="l",ftype="off",node.by.map=TRUE,
    node.size=c(0,1.2),xlab="relative buccal length",
    ylab="relative gape width")
title(main="Phylomorphospace of buccal morphology in Centrarchidae",
    font.main=3)

Creates three-dimensional phylomorphospace plot

Description

Creates a phylomorphospace plot in three dimensions.

Usage

phylomorphospace3d(tree, X, A=NULL, label=TRUE, control=list(), 
   method=c("dynamic","static"), ...)

Arguments

tree

a phylogenetic tree in "phylo" format.
X

an n x 3 matrix of tip values for two characters in n species.
A

an optional m x 3 matrix (for m nodes) of values for two traits at internal nodes in the tree - if not supplied, these values will be estimated using anc.ML.
label

logical value indicating whether to print tip labels next to terminal nodes in the plot (presently doesn't do anything, but labels can be dropped using control).
control

a list containing the following optional control parameters: spin: a logical value indicating whether to animate the plot when created; axes: a logical indicating whether to plot the axes; box: a logical value indicating whether to plot in box; simple.axes: logical value indicating whether to replace box and axes with simpler axes; lwd: line widths; ftype: font type ("off" turns off labels altogether); col.edge a vector of colors of length nrow(tree$edge).
method

a string either "dynamic" for a dynamic (animated) plot created using rgl; or "static" for a flat 3D plot created using scatterplot3d and base graphics. The latter has the advantage of being very easy to export in standard format.
...

optional arguments to be passed to scatterplot3d. Most options not available. angle is an important option that does work here.

Details

This function creates a phylomorphospace plot for three characters using the 3D visualization package, rgl (if available) or statically, by simulating 3D on a flat graphical device.

Value

This function creates a three dimensional phylomorphospace plot. The function returns a function from spin3d (for method="dynamic"); or a series of functions from scatterplot3d (for method="static").

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2014) Graphical methods for visualizing comparative data on phylogenies. Chapter 4 in Modern phylogenetic comparative methods and their application in evolutionary biology: Concepts and practice (L. Z. Garamszegi ed.), pp. 77-103.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Sidlauskas, B. (2008) Continuous and arrested morphological diversification in sister clades of characiform fishes: A phylomorphospace approach. Evolution, 62, 3135-3156.

See Also

fancyTree, phenogram, phylomorphospace

Examples

data(anoletree)
data(anole.data)
anole.pca<-phyl.pca(anoletree,anole.data)
## Not run: 
phylomorphospace3d(anoletree,scores(anole.pca)[,1:3],
    control=list(spin=FALSE))
## End(Not run)
par(cex=0.5)
phylomorphospace3d(anoletree,scores(anole.pca)[,1:3],
    method="static",angle=-30)
par(cex=1)

Compute phylogenetic signal with two methods

Description

Calculate phylogenetic signal using two different methods (Pagel, 1999; Blomberg et al., 2003).

Usage

phylosig(tree, x, method="K", test=FALSE, nsim=1000, se=NULL, start=NULL,
   control=list(), niter=10)
## S3 method for class 'phylosig'
plot(x, ...)

Arguments

tree

a phylogenetic tree in "phylo" format.
x

vector containing values for a single continuously distributed trait. In the case of the plot method, x is an object of class "phylosig".
method

method to compute signal: can be "K" or "lambda".
test

logical indicating whether or not to conduct a hypothesis test of "K" or "lambda".
nsim

for method="K", number of simulations in randomization test.
se

named vector containing the standard errors for each species.
start

vector of starting values for optimization of (respectively) σ2\sigma^2 and λ\lambda. Only used in method="lambda" and se!=NULL.
control

list of control parameters for multidimensional optimization, implemented in optim. Only used in method="lambda" and se!=NULL.
niter

number of iterations for likelihood optimization of λ\lambda (if se!=NULL), or the number of intervals between 0 and the maximum possible value of λ\lambda for univariate optimization of λ\lambda (if se==NULL).
...

optional arguments for plot method.

Details

This function computes phylogenetic signal using two different methods. It can also conduct the hypothesis tests for significant phylogenetic signal, and estimate phylogenetic signal incorporating sampling error following Ives et al. (2007).

λ\lambda optimization is performed using optimize with the range of λ\lambda set between 0 and the theoretical upper limit of λ\lambda (determined by the relative height of the most recent internal node on the tree).

plot.phylosig creates either a plot of the null distribution of K or a likelihood surface, depending on the value of method.

Value

The function returns an object of class "phylosig". With default arguments (method="K", test=FALSE, and se=NULL), this will be a single numeric value. Otherwise, if (method="K"), it will consist of a list with up to the following elements:

K

value of the K-statistic.
sig2

rate of evolution, σ2\sigma^2, for estimation with sampling error.
logL

log-likelihood, for estimation with sampling error.
P

optionally, the P-value from the randomization test.

If (method="lambda"), it will be a list with up to the following elements:

lambda

fitted value of λ\lambda.
sig2

rate of evolution, σ2\sigma^2, for estimation with sampling error.
logL

log-likelihood.
logL0

log-likelihood for λ=0\lambda=0.
P

P-value of the likelihood ratio test.
convergence

value for convergence, for estimation with sampling error only. (See optim).
message

message from optim, for estimation with sampling error only.

Author(s)

Liam Revell [email protected]

References

Blomberg, S. P., T. Garland Jr., and A. R. Ives (2003) Testing for phylogenetic signal in comparative data: Behavioral traits are more labile. Evolution, 57, 717-745.

Ives, A. R., P. E. Midford, and T. Garland Jr. (2007) Within-species variation and measurement error in phylogenetic comparative biology. Systematic Biology, 56, 252-270.

Pagel, M. (1999) Inferring the historical patterns of biological evolution. Nature, 401, 877-884.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Examples

## load data from Garland et al. (1992)
data(mammal.tree)
data(mammal.data)
## extract characters of interest
ln.bodyMass<-log(setNames(mammal.data$bodyMass,
    rownames(mammal.data)))
ln.homeRange<-log(setNames(mammal.data$homeRange,
    rownames(mammal.data)))
## compute phylogenetic signal K
K.bodyMass<-phylosig(mammal.tree,ln.bodyMass,
    test=TRUE)
print(K.bodyMass)
plot(K.bodyMass)
K.homeRange<-phylosig(mammal.tree,ln.homeRange,
    test=TRUE)
print(K.homeRange)
plot(K.homeRange)
## compute phylogenetic signal lambda
lambda.bodyMass<-phylosig(mammal.tree,ln.bodyMass,
    method="lambda",test=TRUE)
print(lambda.bodyMass)
plot(lambda.bodyMass)
lambda.homeRange<-phylosig(mammal.tree,ln.homeRange,
    method="lambda",test=TRUE)
print(lambda.homeRange)
plot(lambda.homeRange)

Plots backbone tree with triangles as clades

Description

Plots a backbone tree (stored as an object of class "backbonePhylo") with triangles as subtrees.

Usage

## S3 method for class 'backbonePhylo'
plot(x, ...)

Arguments

x

an object of class "backbonePhylo".
...

optional arguments. Includes vscale (to rescale the vertical dimension in plotting), fixed.height (logical value to fix the plotted height of subtree triangles), print.clade.size (logical), fixed.n1 (logical value indicating whether or not to use the fixed triangle height for subtrees containing only one taxon, or to plot as a leaf - defaults to FALSE), and col (a single value, or a vector with names, giving the clade colors), as well as xlim, ylim, and lwd (as well as perhaps other standard plotting arguments).

Value

Plots a tree.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

phylo.toBackbone

Examples

## first create our backbone tree with
## random subtree diversities
tree<-phytools:::lambdaTree(pbtree(n=10),lambda=0.5)
## create a translation table
## leaving a couple of single-taxon clades for fun
tip.label<-sample(tree$tip.label,8)
clade.label<-LETTERS[1:8]
N<-ceiling(runif(n=8,min=1,max=20))
## set crown node depth to 1/2 the maximum depth
depth<-sapply(tip.label,function(x,y) 
    0.5*y$edge.length[which(tree$edge[,2]==
    which(y$tip.label==x))],y=tree)
trans<-data.frame(tip.label,clade.label,N,depth)
rownames(trans)<-NULL
## here's what trans looks like
print(trans)
## convert
obj<-phylo.toBackbone(tree,trans)
## plot
plot(obj)
par(mar=c(5.1,4.1,4.1,2.1)) ## reset par

Plot branch colors by a quantitative trait or value

Description

Function plots a tree with branches colored by the value for a quantitative trait or probability, by various methods.

Usage

plotBranchbyTrait(tree, x, mode=c("edges","tips","nodes"), palette="rainbow", 
   legend=TRUE, xlims=NULL, ...)

Arguments

tree

an object of class "phylo".
x

either a vector of states for the edges, tips, or nodes of the tree (for mode="edges", "tips", and "nodes", respectively).
mode

string indicating plotting mode. mode="edges", the default, requires that the mapping state of each edge in the tree should be provided. mode="tips" takes the tip values and estimates the state at each internal node. The mapped character value along each branch is the average of the nodes subtending that branch. mode="nodes" similar to "tips", except that the node values are provided instead of estimated.
palette

color palette to translate character values to color. Options are presently "rainbow" (the default), "heat.colors", and "gray". palette can also be a function produced by colorRampPalette.
legend

can be a logical value (TRUE or FALSE) or a numeric value greater than 0. In the latter case the numeric value gives the length of the plotted legend, which also acts as a scale bar for the branch lengths of the tree.
xlims

range for the translation map between trait values and the color map. Should be inclusive of all the values in x.
...

other optional arguments to be passed to plot.phylo - pretty much all arguments are available. In addition, there plotBranchbyTrait has the following additional optional arguments: tol a small tolerance value to be added to the range of x; prompt for legend=TRUE, a logical value indicating whether to prompt for the position of the legend (or not) - the default is to put the legend in the lower left hand size of the plot; title for legend=TRUE, the title of the legend; and digits for legend=TRUE, the number of digits in the quantitative scale of the legend. Finally, cex can be supplied as either a single numeric value, or as a vector of two different values. If the latter is true than the second element of cex will be passed internally to the function add.color.bar.

Details

Unlike most other tree plotting functions in phytools, this function calls plot.phylo (not plotSimmap) internally.

Note that if prompt=TRUE, the function will prompt for the position of the legend.

Value

Plots a phylogeny.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Plot stochastic character mapped tree

Description

Plots one or multiple stochastic character mapped trees.

Usage

plotSimmap(tree, colors=NULL, fsize=1.0, ftype="reg", lwd=2, pts=FALSE, 
   node.numbers=FALSE, mar=NULL, add=FALSE, offset=NULL,
   direction="rightwards", type="phylogram", setEnv=TRUE, 
   part=if(type=="arc") 0.5 else 1.0, xlim=NULL, ylim=NULL, 
   nodes="intermediate", tips=NULL, maxY=NULL, hold=TRUE, 
   split.vertical=FALSE, lend=2, asp=NA, outline=FALSE, 
   plot=TRUE, underscore=FALSE, arc_height=2)
## S3 method for class 'simmap'
plot(x, ...)
## S3 method for class 'multiSimmap'
plot(x, ...)

Arguments

tree

an object of class "simmap" or "multiSimmap" containing a stochastic mapping or set of mappings (e.g., see read.simmap & make.simmap).
colors

a vector with names translating the mapped states to colors - see Examples.
fsize

relative font size for tip labels.
ftype

font type - options are "reg", "i" (italics), "b" (bold), or "bi" (bold-italics).
lwd

line width for plotting.
pts

logical value indicating whether or not to plot filled circles at each vertex of the tree, as well as at transition points between mapped states. Default is FALSE.
node.numbers

a logical value indicating whether or not node numbers should be plotted.
mar

vector containing the margins for the plot to be passed to par. If not specified, the default margins are [0.1,0.1,0.1,0.1].
add

a logical value indicating whether or not to add the plotted tree to the current plot (TRUE) or create a new plot (FALSE, the default).
offset

offset for the tip labels in character widths.
direction

plotting direction. Options are "rightwards" (the default), "leftwards", "upwards" or "downwards". For method="fan" direction is ignored.
type

plot type. Can be "phylogram", "fan", or "cladogram". Only a subset of options are presently available for type="fan".
setEnv

logical value indicating whether or not to set the environment .PlotPhyloEnv. Setting this to TRUE (the default) will allow compatibility with ape labeling functions such as nodelabels.
part

value between 0 and 1 for type="fan" indicating what fraction of the full circular tree to use as plotting area. For instance, part=0.5 will plot a half fan phylogeny. It also affects the axis scaling used.
xlim

x-limits for the plot.
ylim

y-limits for the plot.
nodes

node placement following Felsenstein (2004; pp. 574-576). Can be "intermediate", "centered", "weighted", or "inner". So far only works for type="phylogram".
tips

labeled vector containing the vertical position of tips. Normally this will be 1:N for N tips in the tree.
maxY

maximum value of y to use before rotating a tree into fan configuration. This will only make a difference if different from Ntip(tree).
hold

logical argument indicating whether or not to hold the output to the graphical device before plotting. Defaults to hold=TRUE.
split.vertical

split the color of the vertically plotted edges by the state of the daughter edges. Only applies if the edge state changes exactly at a node.
lend

line end style. See par.
asp

aspect ratio. See plot.window.
outline

logical value indicating whether or not to draw a black outline around the plotted edges of the tree.
plot

logical value indicating whether or not to actually plot the tree. (See equivalent argument in plot.phylo.)
underscore

logical value indicating whether to plot the underscore character, "_" (if underscore=TRUE) or substitute for a space. Defaults to underscore=FALSE.
arc_height

for type="arc" trees, the height of the arc in units of total tree depth.
x

for S3 plotting method, object of class "simmap" or "multiSimmap".
...

for S3 plotting method, other arguments to be passed to plotSimmap.

Value

Plots a tree.

Author(s)

Liam Revell [email protected]

References

Bollback, J. P. (2006) Stochastic character mapping of discrete traits on phylogenies. BMC Bioinformatics, 7, 88.

Felsenstein, J. (2004) Inferring Phylogenies. Sinauer.

Huelsenbeck, J. P., R. Neilsen, and J. P. Bollback (2003) Stochastic mapping of morphological characters. Systematic Biology, 52, 131-138.

Revell, L. J. (2014) Graphical methods for visualizing comparative data on phylogenies. Chapter 4 in Modern phylogenetic comparative methods and their application in evolutionary biology: Concepts and practice (L. Z. Garamszegi ed.), pp. 77-103.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

densityMap, make.simmap, read.simmap

Examples

data(anoletree)
cols<-setNames(c("green","#E4D96F","darkgreen",
    "brown","black","darkgrey"),
    c("CG","GB","TC","TG","Tr","Tw"))
plot(anoletree,cols,fsize=0.5,ftype="i",outline=TRUE,
    lwd=3,ylim=c(0,Ntip(anoletree)),
    mar=c(0.1,0.1,1.1,0.1))
add.simmap.legend(colors=cols,prompt=FALSE,x=0,y=-0.5,
    vertical=FALSE)
title(main="Caribbean ecomorphs of anoles",font.main=3,
    line=0)
par(mar=c(5.1,4.1,4.1,2.1)) ## reset margins to default

Tree plotting with posterior probabilities of ancestral states from the threshold model

Description

Plots estimated posterior probabilities at nodes under the threshold model.

Usage

plotThresh(tree, x, mcmc, burnin=NULL, piecol, tipcol="input", legend=TRUE, 
   ...)

Arguments

tree

phylogenetic tree.
x

a named vector containing discrete character states; or a matrix containing the tip species, in rows, and probabilities of being in each state, in columns.
mcmc

list object returned by ancThresh.
burnin

number of generations (not samples) to exclude as burn in; if NULL then 20% of generations are excluded as burn-in.
piecol

a named vector containing the colors for the posterior probabilities plotted as pie charts at internal nodes.
tipcol

a string indicating whether the tip colors should be based on the input data ("input") or sampled tip liabilities ("estimated"). These will only differ if there is uncertainty in the tip states.
legend

logical value or text to be plotted in the legend.
...

other arguments to be passed to plot.phylo - label.offset should be >0 so that tip labels and species names do not overlap.

Details

This function uses the object returned by ancThresh to plot the posterior probabilities of ancestral states under the threshold model.

It is also called internally by ancThresh.

Value

Plots a tree.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2014) Ancestral character estimation under the threshold model from quantitative genetics. Evolution, 68, 743-759.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

ancThresh, plot.phylo

Plots rooted phylogenetic tree

Description

Essentially a wrapper for plotSimmap. Arguments in ... are passed to plotSimmap, with the exception of optional argument color which is used to determine the plotted color of the branch lengths of the tree.

Usage

plotTree(tree, ...)

Arguments

tree

a phylogenetic tree in "phylo" format; or multiple trees as an object of class "multiPhylo".
...

optional arguments.

Details

Plots a rooted phylogram or cladogram.

Value

This function plots a rooted phylogram or cladogram.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2014) Graphical methods for visualizing comparative data on phylogenies. Chapter 4 in Modern phylogenetic comparative methods and their application in evolutionary biology: Concepts and practice (L. Z. Garamszegi ed.), pp. 77-103.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

plot.phylo, plotSimmap

Examples

data(vertebrate.tree)
plotTree(vertebrate.tree,fsize=1.2,ftype="i")
par(mar=c(5.1,4.1,4.1,2.1)) ## reset margins to default

Plot a tree with a discrete (or continuous) character data matrix at the tips

Description

plotTree.datamatrix plots a phylogeny next to a matrix of discrete characters. plotFanTree.wTraits plots an arc or fan style tree with discrete or continuous data at the tips.

Usage

plotTree.datamatrix(tree, X, ...)
plotFanTree.wTraits(tree, X, type=c("arc","fan"), ...)

Arguments

tree

an object of class "phylo".
X

a data frame with columns as factors for plotTree.datamatrix, or a matrix of data frame containing continuous and/or discrete characters for plotFanTree.wTraits.
type

plot type for plotFanTree.wTraits.
...

optional arguments.

Value

plotTree.datamatrix invisibly returns a list containing the font size, a list of the colors used for each column of the plotted data matrix, and the x-coordinate of the rightmost edge of the matrix.

plotFanTree.wTraits invisibly returns the color palette used for plotting.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

dotTree, phylo.heatmap

Examples

data("liolaemid.data")
data("liolaemid.tree")
liolaemid.data[liolaemid.tree$tip.label,]->liolaemid.data
colors<-list(
  c("blue","white","red"),
  terrain.colors(n=10),
  setNames(c("#F0EAD6","#DF536B"),c("O","V")))
cols<-plotFanTree.wTraits(liolaemid.tree,
  liolaemid.data[,3:1],lwd=12,colors=colors,ftype="off",
  spacer=0)
legend(x=0,y=0.7*max(nodeHeights(liolaemid.tree)),
  names(colors[[3]]),lwd=8,col=colors[[3]],
  title="parity mode",bty="n",xjust=0.5,yjust=0.5)
add.color.bar(1.5*max(nodeHeights(liolaemid.tree)),cols[[2]],
  title="maximum altitude (m)",
  lims=range(liolaemid.data[,2]),digits=2,prompt=FALSE,
  x=-0.75*max(nodeHeights(liolaemid.tree)),
  y=0.2*max(nodeHeights(liolaemid.tree)),subtitle="",
  lwd=8,outline=FALSE)
add.color.bar(1.5*max(nodeHeights(liolaemid.tree)),cols[[1]],
  title="environmental temp.",
  lims=range(liolaemid.data[,3]),digits=2,prompt=FALSE,
  x=-0.75*max(nodeHeights(liolaemid.tree)),
  y=-0.15*max(nodeHeights(liolaemid.tree)),subtitle="",
  lwd=8,outline=FALSE)
par(mar=c(5.1,4.1,4.1,2.1)) ## reset margins to default

Plot a tree with error bars around divergence dates

Description

Plots a tree with error bars around divergence times (nodes).

Usage

plotTree.errorbars(tree, CI, ...)

Arguments

tree

an object of class "phylo".
CI

confidence intervals around internal nodes of the tree, measured in time since the present.
...

optional arguments to be passed to plotTree.

Details

The matrix CI show contain (in rows) the lower & upper confidence bounds in time since the present.

Optional arguments specific to the error bar plot include gridlines, bar.lwd,cex (for the points plotted at nodes), and bar.col.

Value

Plots a tree with error bars around internal nodes..

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

ltt, plotTree

Plot a tree with one or more matched lollipop plots

Description

Plots an upward facing phylogenetic tree with one or more matched lollipop plots. Inspired by a plotting style used by Title et al. (2024).

Usage

plotTree.lollipop(tree, x, args.plotTree=list(), args.lollipop=list(), ...)

Arguments

tree

an object of class "phylo".
x

a matrix, data frame, or vector of numeric values.
args.plotTree

list of arguments to be passed to plotTree.
args.lollipop

list of arguments for the lollipop plot(s).
...

optional arguments.

Value

Creates a plot.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Title, P. O., Singhal, S., Grundler, M. C., Costa, G. C., Pyron, R. A., Colston, T. J., Grundler, M. R., Prates, I., Stepanova, N., Jones, M. E. H., Cavalcanti, L. B. Q., Colli, G. R., Di-Poi, N., Donnellan, S. C., Moritz, C., Mesquita, D. O., Pianka, E. R., Smith, S. A., Vitt, L. J., and Rabosky, D. L. (2024) The macroevolutionary singularity of snakes. Science, 383, 918-923.

See Also

phylo.heatmap, plotTree.barplot

Examples

data(anoletree)
anole_tree<-as.phylo(anoletree)
data(anole.data)
anole_data<-cbind(phyl.resid(anole_tree,
  x=as.matrix(anole.data[,"SVL",drop=FALSE]),
  Y=as.matrix(anole.data[,c(6,4,2)]))$resid,
  exp(anole.data[,"SVL",drop=FALSE]))
plotTree.lollipop(anole_tree,anole_data,
  ylab=c("relative (TL)","relative (FLL)",
    "relative (HL)","SVL"))
par(mar=c(5.1,4.1,4.1,2.1))

Plot a tree with bars at the tips

Description

Plots a phylogenetic tree with adjacent boxplot or barplot.

Usage

plotTree.wBars(tree, x, scale=NULL, width=NULL, type="phylogram", 
    method="plotTree", tip.labels=FALSE, col="grey", border=NULL, 
    ...)
plotTree.barplot(tree, x, args.plotTree=list(), args.barplot=list(), 
    ...)
plotTree.boxplot(tree, x, args.plotTree=list(), args.boxplot=list(),
    ...)

Arguments

tree

an object of class "phylo".
x

a named vector or matrix of trait values. For plotTree.boxplot, the names should repeat for multiple observations per species. For plotTree.boxplot x can also be supplied as a formula, though in that case the factor levels need to be provided in a valid cladewise order of the tips in tree. This order doesn't need to correspond with the current order of the tip labels. For plotTree.barplot x can be a matrix (or a data frame) in which columns are the values of multiple traits to be simultaneously plotted on the tree.
scale

scaling factor for the tip bars (relative to the total tree height). If left as NULL a reasonable scaling factor is computed automatically.
width

width of the tip bars.
type

plot type. Can be "phylogram" or "fan".
method

plotting method to use. Can be "plotTree" (for plotTree) or "plotSimmap" (for plotSimmap).
tip.labels

argument indicating whether or not tip labels should be plotted. Defaults to tip.labels=FALSE.
col

colors of the plotted bars. Can be a single value or a vector with length equal to the number of tips in the tree.
border

single value specifying the color of the border for the plotted bars. Defaults to border=NULL, which means that black borders will be plotted.
args.plotTree

in plotTree.barplot, arguments to be passed to plotTree.
args.barplot

in plotTree.barplot, arguments to be passed to barplot.
args.boxplot

in plotTree.boxplot, arguments to be passed to boxplot.
...

optional arguments to be passed to plotTree or plotSimmap in the case of plotTree.wBars. For plotTree.barplot, the only optional arguments are add and ylim. Generally add should not be used; however it can be employed to tell the function to draw the tree & barplot, respectively, in the next two open plotting devices - rather than creating a table of figures in the current plotting device. ylim (which is also an optional argument for plotTree.boxplot should be supplied here rather than using args.plotTree, args.boxplot, or args.barplot because y axis limits must match exactly between the two plots.

Details

plotTree.wbars plots a phylogeny in phylogram or fan style with bars at the tips representing the values for a phenotypic trait.

plotTree.barplot creates a split plot in which a right-facing phylogram is on the left, and a bar plot is shown on the right.

plotTree.boxplot creates a split plot in which a right-facing phylogram is on the left, and a box plot is shown on the right.

Value

Plots a tree with an associated bar plot for a continuously valued character at the tips.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

barplot, dotTree, plotSimmap, plotTree

Examples

## load data from Mahler et al. (2010)
data(anoletree)
data(anole.data)
## extract overall body size (SVL)
svl<-setNames(anole.data$SVL,rownames(anole.data))
## plotTree.wBars
plotTree.wBars(anoletree,svl,type="fan",scal=0.5)
par(mar=c(5.1,4.1,4.1,2.1))
## plotTree.barplot
plotTree.barplot(anoletree,exp(svl),
    args.plotTree=list(fsize=0.5),
    args.barplot=list(xlab="SVL (mm)"))
	
## load vertebrate tree and data
data(vertebrate.tree)
data(vertebrate.data)
## plotTree.barplot
options(scipen=4) ## change sci-notation
par(cex.axis=0.8)
plotTree.barplot(vertebrate.tree,
    setNames(vertebrate.data$Mass,
    rownames(vertebrate.data)),
    args.barplot=list(
    log="x",
    xlab="mass (kg)",
    xlim=c(0.01,500000),
    col=palette()[4]))
options(scipen=0)

## reset par to defaults
par(mfrow=c(1,1),mar=c(5.1,4.1,4.1,2.1),cex.axis=1)

Analysis of the posterior sample from evol.rate.mcmc

Description

Analyzes posterior sample from evol.rate.mcmc.

Usage

posterior.evolrate(tree, ave.shift, mcmc, tips, showTree=FALSE)

Arguments

tree

a phylogenetic tree in "phylo" format.
ave.shift

mean or median shift-point from the posterior sample (see minSplit.
mcmc

matrix $mcmc from evol.rate.mcmc (probably with burn-in excluded).
tips

list of tips in state σ12\sigma_1^2 for each sampled generation of MCMC.
showTree

optional logical value indicating whether or not to plot the stretched and shrunken tree generated by the pre-processing algorithm implemented in this function (default is FALSE).

Details

This function takes a phylogenetic tree, an average split position, and a raw MCMC output from evol.rate.mcmc and returns a posterior sample of evolutionary rates rootward (σ12\sigma_1^2) and tipward (σ22\sigma_2^2) from the average split.

Value

A matrix containing the posterior sample of evolutionary rates and shift-points between rates.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Revell, L. J., D. L. Mahler, P. Peres-Neto, and B. D. Redelings (2012) A new method for identifying exceptional phenotypic diversification. Evolution, 66, 135-146.

See Also

evol.rate.mcmc, minSplit

Generic post-hoc test

Description

Conducts posthoc test.

Usage

posthoc(x, ...)

Arguments

x

an object on which to conduct a post-hoc test.
...

optional arguments to be passed to method.

Details

So far is only implemented for object class "ratebytree".

Value

An object of the appropriate class containing the results of a posthoc test.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

ratebytree

Print method for backbone phylogeny

Description

Print method for an object of class "backbonePhylo".

Usage

## S3 method for class 'backbonePhylo'
print(x, ...)

Arguments

x

an object of class "backbonePhylo".
...

optional arguments.

Value

Prints to screen.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

phylo.toBackbone

Compute the parsimony score

Description

Calculates the parsimony score using the Fitch algorithm.

Usage

pscore(tree, x, ...)

Arguments

tree

object of class "phylo".
x

vector (e.g., factor vector), matrix, or data frame. Should contain names or row names.
...

optional arguments.

Details

Mostly for diagnostic purposes. Users interested in using Maximum Parsimony for phylogeny inference or ancestral state reconstruction should refer to the phangorn package.

Value

A numerical value or vector of values.

Author(s)

Liam Revell [email protected]

References

Felsenstein, J. (2004) Inferring Phylogenies. Sinauer.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

fitMk, sim.Mk

Examples

## load tree and data from Revell & Collar (2009)
data(sunfish.tree)
data(sunfish.data)
## extract discrete character (feeding mode)
fmode<-setNames(sunfish.data$feeding.mode,
    rownames(sunfish.data))
## compute the parsimony score
pscore(sunfish.tree,fmode)

Method for investigating the rate of one trait as a function of the state of another

Description

Statistical test of whether the rate of a continuous character might be influenced by the state of another.

Usage

ratebystate(tree, x, y, nsim=100, corr=c("pearson","spearman"), ...)

Arguments

tree

phylogenetic tree.
x

a continuous character - the dependent variable in the model.
y

a second continuous trait - the response variable.
nsim

number of simulations for hypothesis testing.
corr

correlation method to use. Same as in cor.
...

optional arguments which include sim.method ("fastBM" or "sim.corrs"; see fastBM and sim.corrs); method ("by.node" or "by.branch" indicating whether to assume the rate varies as a function of the node state or the mean branch state); message - a logical value indicating whether or not to return corr and method; finally logarithm - indicating whether or not to fit a model in which the variance of Brownian evolution in y changes as a multiplicative function of x. The default is logarithm=FALSE.

Details

This function attempts to ask if the rate of a continuous character, y, depends on the state of a separate continuous trait, x. This is accomplished by regressing the squared contrasts in y on the branch or node ancestral estimates of x.

Value

This function returns an object of class "ratebystate" with up to the following four elements:

beta

value of the regression coefficient for square of the contrasts in y regressed on the ancestral or branch-wise estimated states for x.
r

correlation coefficient for corr=corr.
corr

string giving the value of corr.
method

string giving the value of method.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

fastAnc, pic

Likelihood test for rate variation among trees, clades, or traits

Description

Multiple methods for comparing the rate or process of evolution between trees.

Usage

ratebytree(trees, x, ...)
## S3 method for class 'ratebytree'
posthoc(x, ...)

Arguments

trees

an object of class "multiPhylo". If x consists of a list of different traits to be compared, then trees could also be a simple set of duplicates of the same tree, e.g., rep(tree,length(x)).
x

a list of trait vectors for a continuous trait in which the names of each vectors correspond to the tip labels of trees. This is not used if type="diversification". In the case of posthoc.ratebytree, an object of class "ratebytree".
...

optional arguments, including the argument type ("continuous", "discrete", or "diversification"), which, if not specified, the function will attempt to ascertain. See Details for more information.

Details

This function essentially implements three different methods for comparing the rate or process of evolution between trees: one for continuously-valued traits, a second for discrete characters, and a third for the rate of diversification (speciation & extinction).

In all cases, the function takes an object of class "multiPhylo" containing two or more phylogenies (trees), and (for the first two analyses) a list of trait vectors (x).

For continuous traits, the function then proceeds to fit two models: one in which the rate (or regime, for models "OU" and "EB") of trait evolution is equal among all trees; and a second in which the rates or regimes can differ between trees.

The latter model corresponds to an extension of the censored approach of O'Meara et al. (2006; Revell et al. 2018) and should also be related to the method of Adams (2012) for comparing rates among traits. See brownie.lite for a different implementation of the noncensored approach of O'Meara et al. (2006).

For discrete traits, the function instead proceeds to fit two variants of the Mk model (Lewis 2001): one in which the parameters values (transition rates) of the process are free to vary between trees, and a second in which they are fixed to be the same.

For diversification alone, the function fits two different diversification (speciation & extinction) models (Nee et al. 1994; Stadler 2012): one in which the birth (speciation) and death (extinction) rates are identical between the trees, and a second in which they are permitted to differ in various ways depending on the value of "model" (Revell 2018).

The method posthoc conducts a post-hoc comparison of parameter estimates between trees in the multi-rate or multi-process model. The parameter that is compared depends on the fitted model. For instance, in model="BM" posthoc comparison is made of sig2; if model="OU" fitted values of alpha are compared; and so on. The argument p.adjust.method can be used to specify a method for adjusting P-values for multiple tests following p.adjust (defaults to p.adjust.method="none".

At present it is not possible to specify different models to fit for the different trees - although if (for instance) character evolution on tree 1 proceeded by a strong OU process while character evolution on tree 2 was by BM, we would probably reject a constant-process model and tree 2 should show a very low value of alpha.

To compute the standard errors for each fitted parameter value, the function computes the negative inverse of the Hessian matrix at the MLEs; however, if this matrix is computationally singular the generalized inverse (ginv) will be used instead without warning.

The function also conducts a likelihood-ratio test to compare the two models.

For continuous character, optional arguments presently include the following: model, the model of continuous trait evolution (options are "BM", the default, "OU", and "EB"). tol, used as a minimum value for the fitting rates, to prevent problems in optimization. trace, a logical value indicating whether or not to report progress in the optimization. test, the method for hypothesis testing (options are "chisq" and "simulation"). quiet, a logical value indicating whether or not to run perfectly quietly. Finally, se, a list of vectors containing the standard errors for each value of x.

For type="discrete" the optional arguments are slightly different. The argument model can be used, but it must assume the values "ER", "SYM", "ARD", or a numeric matrix following ace.

Finally, for type= "diversification" models are so far "birth-death", "equal-extinction", and "equal-specation", and "Yule". It is also important to consider supplying the sampling fractions, rho, which is a vector of values between 0 and 1 of the same length as trees. If not provided the method will assume a sampling fraction of 1.0 for all trees - which is seldom true of empirical studies.

Value

An object of class "ratebytree" or an object of class "posthoc.ratebytree" in the case of the method posthoc.

Author(s)

Liam Revell [email protected]

References

Adams, D. C. (2012) Comparing evolutionary rates for different phenotypic traits on a phylogeny using likelihood. Syst. Biol., 62, 181-192.

Lewis, P. O. (2001) A likelihood approach to estimating phylogeny from discrete morphological character data. Systematic Biology, 50, 913-925.

Nee, S., May, R. M. and Harvey, P. H. (1994) The reconstructed evolutionary process. Philosophical Transactions of the Royal Society of London B, 344, 305-311.

O'Meara, B. C., C. Ane, M. J. Sanderson, and P. C. Wainwright. (2006) Testing for different rates of continuous trait evolution using likelihood. Evolution, 60, 922-933.

Revell, L. J. (2018) Comparing the rates of speciation and extinction between phylogenetic trees. Ecology and Evolution, 8, 5303-5312.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Revell, L. J., Gonzalez-Valenzuela, L. E., Alfonso, A., Castellanos-Garcia, L. A., Guarnizo, C. E., and Crawford, A. J. (2018) Comparing evolutionary rates between trees, clades, & traits. Methods Ecol. Evol., 9, 994-1005.

Stadler, T. (2012) How can we improve the accuracy of macroevolutionary rate estimates? Systematic Biology, 62, 321-329.

See Also

brownie.lite, fitMk

Find the temporal position of one or more rate shifts

Description

Fits a model with one or more temporal rate shifts for a continuous trait on the tree.

Usage

rateshift(tree, x, nrates=1, niter=10, method="ML", ...)
## S3 method for class 'rateshift'
plot(x, ...)
likSurface.rateshift(tree, x, nrates=2, shift.range=NULL,
   density=20, plot=TRUE, ...)

Arguments

tree

object of class "phylo".
x

vector of phenotypic trait values for species. names(x) should contain the species names and match tree$tip.label. For plot method, x is an object of class "rateshift".
nrates

number of rates.
niter

number of iterations of optimization routine to ensure convergence.
method

optimization method. Can be "ML" (maximum likelihood) or "REML" (restricted maximum likelihood).
...

optional arguments. In the case of the plot method, these will be passed to plotSimmap. For rateshift, optional arguments include: tol, tolerance; plot & print, logical values indicating whether to plot or print the progress of the optimization (default to FALSE); quiet, logical argument indicating whether to suppress all notifications (defaults to FALSE); minL, numeric value; and fixed.shift, either a vector of fixed shift points, or a logical value.
shift.range

for likSurface.rateshift.
density

for likSurface.rateshift.
plot

logical argument for likSurface.rateshift. If plot=FALSE then the surface is returned.

Details

rateshift attempts to find the location of one or more rate shifts. This model is quite easy to compute the likelihood for, but quite difficult to optimize as the likelihood surface is often rugged. In addition, the model of rateshift is sometimes non-identifiable, i.e., more than one solution may have the same (maximum) likelihood, depending on the data, the tree, and the number of shifts in our model.

likSurface.rateshift plots the likelihood surface.

Value

A fitted object of class "rateshift", or, in the case of likSurface.rateshift, a likelihood surface for the shift points.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Revell, L. J. and L. J. Harmon (2022) Phylogenetic Comparative Methods in R. Princeton University Press.

See Also

brownie.lite

Newick or Nexus style tree reader

Description

Reads a phylogenetic tree from file.

Usage

read.newick(file="", text, ...)
readNexus(file="", format=c("standard","raxml"))

Arguments

file

name of text file with single Newick style tree or multiple trees, one per line. For readNexus this should be a Nexus format tree.
text

character string containing tree.
format

file format (source) for readNexus. In the case of format="standard", read.nexus from ape will be used internally. For format="raxml", the parser assumes that bootstrap values have been stored as node labels in the format [&label=bootstrap].
...

optional arguments to be passed to scan. Note that if the arguments sep or what are supplied this could generate an error. Useful optional arguments might include skip (number of lines to skip) and nlines (number of lines to read).

Details

The function read.newick reads a simple Newick style tree from file. This function is now almost completely redundant with read.tree. At the time of development, however, it was more 'robust' than read.tree in that it didn't fail if the tree contained so-called 'singles' (nodes with only one descendant); however, read.tree can now handle singleton nodes without difficulty.

The function readNexus reads a Nexus formatted tree, optionally with bootstrap values as node labels. This function can read a simple Nexus formatted tree from file (like read.nexus); however, it can also parse the node labels as bootstrap values. This is the output format from the software RAxML. For Nexus tree files with complex node labels (e.g., from the software MrBayes) it will probably fail to parse node labels correctly, if at all.

Value

An object of class "phylo", possibly containing singletons (see collapse.singles); or an object of class "multiPhylo".

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

read.tree, read.nexus

Examples

tree<-"((Human,Chimp),Gorilla),Monkey);"
phy<-read.newick(text=tree)

Read SIMMAP style trees from file

Description

This reads one or multiple SIMMAP style trees from file.

Usage

read.simmap(file="", text, format="nexus", rev.order=TRUE, version=1)

Arguments

file

name of text file with one or multiple SIMMAP v1.0 or v1.5 style trees containing the mapped history of a discrete character.
text

character string containing the tree. If version=1.5 this argument is ignored. (This format tree can only be read from file in the present version.)
format

format of the trees: either "phylip" or "nexus" - the latter is the default output from SIMMAP. If version=1.5 this argument is ignored.
rev.order

a logical value indicating whether the states and times along each branch is given (from root to tip) in right-to-left order (if TRUE) or in left-to-right order. If version=1.5 this argument is ignored.
version

version of SIMMAP for input tree. If the tree(s) was/were simulated in SIMMAP v1.0 or written to file by link{make.simmap} then version=1.0; if the tree(s) was/were simulated using SIMMAP v1.5 then version=1.5.

Details

This function now accepts trees in both SIMMAP v1.0 and SIMMAP v1.5 format. In addition, it can read a more flexible format than is produced by SIMMAP (for instance, multi-character mapped states and more than 7 mapped states).

The function uses some modified code from read.nexus from the ape package to read the NEXUS block created by SIMMAP. Also creates the attribute "map.order" which indicates whether the stochastic map was read in from left to right or right to left. This attribute is used by default by write.simmap to write the tree in the same order.

Value

An object of class "simmap" (or list of such objects with class "multiSimmap"), consisting of a modified object of class "phylo" with at least the following additional elements:

maps

a list of named vectors containing the times spent in each state on each branch, in the order in which they occur.
mapped.edge

a matrix containing the total time spent in each state along each edge of the tree.

Author(s)

Liam Revell [email protected]

References

Bollback, J. P. (2006) Stochastic character mapping of discrete traits on phylogenies. BMC Bioinformatics, 7, 88.

Paradis, E., J. Claude, and K. Strimmer (2004) APE: Analyses of phylogenetics and evolution in R language. Bioinformatics, 20, 289-290.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

brownie.lite, evol.vcv, read.tree, read.nexus

Reorders a backbone phylogeny

Description

Function reorders an object of class "backbonePhylo".

Usage

## S3 method for class 'backbonePhylo'
reorder(x, order="cladewise", ...)

Arguments

x

an object of class "backbonePhylo".
order

order. See reorder.phylo for possible orderings.
...

optional arguments.

Value

An object of class "backbonePhylo".

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

phylo.toBackbone

Reorder edges of a "simmap" tree

Description

Function returns a reordered modified "phylo" object by using reorder.phylo but then sorting the additional elements $mapped.edge and $maps to have the same order as $edge.

Usage

reorderSimmap(tree, order="cladewise", index.only=FALSE, ...)

Arguments

tree

a modified object of class "phylo".
order

"cladewise", "pruningwise", or any other allowable order permitted by reorder.phylo.
index.only

logical value indicating whether only an index should be returned.
...

other arguments.

Value

A modified object of class "phylo".

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

reorder.phylo, plotSimmap

Replicate a tree or set of trees

Description

rep method for object of class "phylo" or "multiPhylo".

Usage

## S3 method for class 'phylo'
rep(x, ...)
## S3 method for class 'multiPhylo'
rep(x, ...)
repPhylo(tree, times)

Arguments

tree

object of class "phylo".
times

number of times to replicate tree.
x

for S3 method an object of class "phylo" or "multiPhylo".
...

other arguments for rep (specifically, times).

Details

repPhylo is just an alias for rep.phylo and rep.multiPhylo.

Value

An object of class "multiPhylo".

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

c.phylo, rep

Examples

tree<-pbtree(n=100)
trees<-rep(tree,100)

Re-root a tree along an edge

Description

Re-roots a phylogenetic tree at an arbitrary position along an edge.

Usage

reroot(tree, node.number, position=NULL, interactive=FALSE, ...)

Arguments

tree

a phylogenetic tree in "phylo" format.
node.number

number of the node descending from the target branch in tree$edge - this can also be a tip in which case the node number is the index number of the tip in tree$tip.label.
position

position along the target edge at which to re-root the tree. If not supplied, then the tree will be re-rooted at the node or tip.
interactive

logical value indicating whether to use interactive mode (defaults to interactive= FALSE).
...

arguments to be passed to plotTree for interactive=TRUE only.

Details

This function had an error for rootings along edges descended from the root node for phytools<=0.2-47. This should be fixed in the present version. Now uses paste.tree, root, and splitTree internally. Earlier versions also had an error related to node labels. This should be fixed in phytools>=0.4-47.

Value

A phylogenetic tree in "phylo" format.

Author(s)

Liam Revell [email protected]

References

Paradis, E., J. Claude, and K. Strimmer (2004) APE: Analyses of phylogenetics and evolution in R language. Bioinformatics, 20, 289-290.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

splitTree, paste.tree, root

Get marginal ancestral state reconstructions by re-rooting

Description

Computes marginal ancestral states for a discrete character using the re-rooting method of Yang et al. (1995).

In general, this function is redundant with ancr for circumstances in which it is valid (i.e., symmetric Q matrices), and improper otherwise. In general ancr should be preferred.

Usage

rerootingMethod(tree, x, model=c("ER","SYM"), ...)

Arguments

tree

an object of class "phylo".
x

a vector of tip values for species, or a matrix containing the prior probability that the tip is in each state. If x is a vector, then names(x) should be the species names. If x is a matrix of prior probabilities, then rownames should be species names, column names should be states for the discrete character, and rows of the matrix should sum to 1.0.
model

any reversible model. model=c("ER","SYM") recommended.
...

optional arguments. Presently the logical argument tips. If tips=TRUE, then the function will also compute the empirical Bayes posterior probabilities of the tips following Yang (2006). Note that ... is passed internally to fitMk, but should be used in this way with caution because any arguments that conflict with the default arguments of the method will cause the function execution to fail. The most practical use of this would be to force a particular value of the transition matrix, Q, via the argument fixedQ.

Details

This function uses the re-rooting method of Yang et al. (1995) to get the marginal ancestral state estimates for each internal node of the tree using likelihood. This method get the conditional scaled likelihoods for the root node (which is the same as the marginal ancestral state reconstruction for that node) and successively moves the root to each node in the tree. The function can also return the posterior probabilities for the tip nodes of the tree.

rerootingMethod calls fitMk internally. fitMk uses some code adapted from ace in the ape package.

Value

An object of class "rerootingMethod" containing at least the following elements:

loglik

the log-likelihood.
Q

the fitted transition matrix between states.
marginal.anc

the marginal ancestral state reconstructions for each node (and, optionally, each tip).

Author(s)

Liam Revell [email protected]

References

Paradis, E., J. Claude, and K. Strimmer (2004) APE: Analyses of phylogenetics and evolution in R language. Bioinformatics, 20, 289-290.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Yang, Z., Kumar, S., Nei, M. (1995) A new method of inference of ancestral nucleotide and amino acid sequences. Genetics, 141, 1641-1650.

See Also

ace, ancr, fitMk, make.simmap

Rescale phylogenetic objects of different types

Description

Generic method for rescaling different types of phylogenetic trees.

Usage

rescale(x, ...)

Arguments

x

phylogenetic tree object to be rescaled: e.g., object of class "phylo" or "simmap".
...

other arguments to be used in rescaling, depending on the object class. (E.g., see rescale.phylo in geiger and rescale.simmap.)

Details

See rescale.phylo in geiger and rescale.simmap for details.

Value

A rescaled phylogenetic tree object.

Author(s)

Liam Revell [email protected]

References

Pennell, M.W., J. M. Eastman, G. J. Slater, J. W. Brown, J. C. Uyeda, R. G. FitzJohn, M. E. Alfaro, and L. J. Harmon (2014) geiger v2.0: an expanded suite of methods for fitting macroevolutionary models to phylogenetic trees. Bioinformatics, 30, 2216-2218.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

rescale.phylo, rescale.simmap

Rescale object of class "simmap"

Description

Scales a tree with a mapped discrete character ("simmap" object), or a set of such trees, to an arbitrary total height, preserving the relative time spent in each state along each edge.

Usage

## S3 method for class 'simmap'
rescale(x, model="depth", ...)
## S3 method for class 'multiSimmap'
rescale(x, model="depth", ...)
rescaleSimmap(tree, ...)

Arguments

x

object of class "simmap" or "multiSimmap" to be rescaled.
model

model to use to rescale the tree. Currently the only option is "depth".
...

parameter of the model to use in rescaling. Currently the only parameter is depth for model="depth".
tree

for rescaleSimmap, object of class "simmap" to be rescaled.

Details

Replaces rescaleTree (now rescale.phylo) in the geiger package for the "simmap" object class. rescaleSimmap is now a redundant alias for the method rescale.simmap.

Value

An object of class "simmap" or "multiSimmap".

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

make.simmap, read.simmap

Examples

## load anoletree
data(anoletree)
## rescale to have total depth of 50
rescaled_anoletree<-rescale(anoletree,depth=50)
## plot rescaled tree
plot(rescaled_anoletree,ftype="i",fsize=0.6,
	mar=c(5.1,1.1,1.1,1.1))
axis(1,at=seq(0,50,by=10))
par(mar=c(5.1,4.1,4.1,2.1)) ## reset margin to default

Compute all possible resolutions of a node or all nodes in a multifurcating tree

Description

Resolves a single multifurcation or all multifurcations in all possible ways.

Usage

resolveNode(tree,node)
resolveAllNodes(tree)

Arguments

tree

an object of class "phylo".
node

for resolveNode, the node with a polytomy to resolve.

Details

This functions resolves a single multifurcation or all multifurcations in a tree in all possible ways. If the input tree has edge lengths, then the resolutions will use internal edges of zero length.

For resolveNode applied to a multifurcation with n descendants, the number of resolved trees will be equal to the number of possible rooted trees of n taxa. (For instance, three for a trifurcation, 15 for a quadrifurcation, and so on.)

For resolveAllNodes the number of fully resolved trees will be equal to the product of numbers for resolveNode applied to each multifurcation separately. (For instance, 45 for a tree containing one trifurcation and one quadrifurcation.)

Value

An object of class "multiPhylo" - or, if the input tree is already fully resolved, an object of class "phylo" identical to tree.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

multi2di

Rotates a node or set of nodes in a phylogenetic tree

Description

The function rotateNodes is a simple wrapper for rotate which rotates a set of nodes or all nodes.

The function rotate.multi finds all possible rotations around a multifurcating node, given by node. This will be an object of class "multiPhylo", assuming that the node specified is indeed a multifurcation.

The function allRotations computes all possible rotated trees for a given input phylogeny. For a binary tree, this is generally two raised to the power of the number of internal nodes (so a very large number, if N is even modest in size).

Usage

rotateNodes(tree, nodes, polytom=c(1,2), ...)
rotate.multi(tree, node)
allRotations(tree)

Arguments

tree

object of class "phylo".
nodes

either a single node number to rotate, a vector of node numbers, or the string "all".
polytom

a vector of mode numeric and length two specifying the two clades that should be exchanged in a polytomy (see rotate).
node

a single node to rotate (in the case of rotate.multi).
...

optional arguments.

Details

All three functions also address the problem that the product of multiple rotations from rotate can be non-compliant with the implicit "phylo" standard because the tip numbers in tree$edge are not in numerical order 1:n for n tips.

Value

An object of class "phylo" (i.e., a phylogenetic tree), in the case of rotateNodes, or an object of class "multiPhylo" for rotate.multi or allRotations.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Rounds the branch lengths of a tree

Description

Rounds the branch lengths of a phylogenetic tree.

Usage

roundBranches(tree, digits)

Arguments

tree

an object of class "phylo", "multiPhylo", "simmap", or "multiSimmap".
digits

number of digits for rounding. Passed to round.

Details

This function rounds the branch lengths of a tree or trees to a precision indicated by digits, and reconciles any mappings for objects of class "simmap" or "multiSimmap".

Value

An object of class "phylo", "multiPhylo", "simmap", or "multiSimmap", with rounded edge lengths.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Plot a round, sigmoidal, or spline phylogram or cladogram

Description

Plots one or multiple round phylograms, a sigmoidal phylogram or cladogram, or a phylogram draw using cubic splines through the nodes.

Usage

roundPhylogram(tree, fsize=1.0, ftype="reg", lwd=2, mar=NULL, offset=NULL, 
   direction="rightwards", type="phylogram", xlim=NULL, ylim=NULL, ...)
sigmoidPhylogram(tree, ...)
splinePhylogram(tree, ...)

Arguments

tree

an object of class "phylo" or "multiPhylo" containing one or multiple phylogenies.
fsize

relative font size for tip labels.
ftype

font type - options are "reg", "i" (italics), "b" (bold), or "bi" (bold-italics).
lwd

line width for plotting.
mar

vector containing the margins for the plot to be passed to par. If not specified, the default margins are [0.1,0.1,0.1,0.1].
offset

offset for the tip labels.
direction

plotting direction. Only the option direction="rightwards" is presently supported.
type

plot type. Can be "phylogram" or "cladogram". If type="cladogram" then the branch lengths are not necessary (and, indeed, are not used).
xlim

x-limits for the plot.
ylim

y-limits for the plot.
...

optional arguments. In the case of roundPhylogram, these are mostly as in plotTree and plotSimmap.

Details

The underscore character "_" is automatically swapped for a space in tip labels, as in plotSimmap.

Value

Plots a tree.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

plotSimmap, plotTree

Examples

## load mammal.tree
data(mammal.tree)
## plot using roundPhylogram
roundPhylogram(compute.brlen(mammal.tree),
    fsize=0.8,ftype="i")
## load anoletree
data(anoletree)
## plot using sigmoidPhylogram
sigmoidPhylogram(anoletree,fsize=0.6,
    ftype="i",direction="upwards")
par(mar=c(5.1,4.1,4.1,2.1)) ## reset margin to default

Pick a random state according to a vector of probabilities

Description

Internal function for make.simmap.

Usage

rstate(y)

Arguments

y

vector of probabilities. Must have names & should probably add to 1.0.

Details

This function picks a random element in a vector according to the probability assigned that element. It returns the name. Uses rmultinom.

Value

A character or string.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Sample from a set of distributions

Description

Samples from a set of normal distributions with parameters given in xbar and xvar.

Usage

sampleFrom(xbar=0, xvar=1, n=1, randn=NULL, type="norm")

Arguments

xbar

a named vector of means.
xvar

a named vector of variances.
n

a vector containing the sample sizes of each species.
randn

a range of sample sizes are to be random.
type

"norm" is the only distribution implemented so far.

Value

A vector, with labels.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Set color map for various phylogenetic objects of classes

Description

Changes the color map (ramp) in an object of class "contMap", "densityMap", "phyloScattergram", or "multirateBM_plot".

Usage

setMap(x, ...)
## S3 method for class 'contMap'
setMap(x, ...)
## S3 method for class 'densityMap'
setMap(x, ...)
## S3 method for class 'phyloScattergram'
setMap(x, ...)
## S3 method for class 'multirateBM_plot'
setMap(x, ...)

Arguments

x

an object of class "contMap", "densityMap", "phyloScattergram", or "multirateBM_plot".
...

arguments to be passed to colorRampPalette. Also, the argument invert which (if invert=TRUE) will just flip the current color ramp.

Value

An object of class "contMap", "densityMap", "phyloScattergram", or "multirateBM_plot".

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2012) phytools: An R package for phylogenetic comparative biology (and other things). Methods Ecol. Evol., 3, 217-223.

Revell, L. J. (2013) Two new graphical methods for mapping trait evolution on phylogenies. Methods in Ecology and Evolution, 4, 754-759.

Revell, L. J. (2014) Graphical methods for visualizing comparative data on phylogenies. Chapter 4 in Modern phylogenetic comparative methods and their application in evolutionary biology: Concepts and practice (L. Z. Garamszegi ed.), pp. 77-103.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

contMap, densityMap, multirateBM

Multivariate Brownian simulation with multiple correlations and rates

Description

Simulates multivariate Brownian motion evolution on a tree with multiple evolutionary correlation/covariance matrices.

Usage

sim.corrs(tree, vcv, anc=NULL, internal=FALSE)

Arguments

tree

an object of class "phylo" or "simmap".
vcv

is a square covariance matrix or named list of matrices (one for each mapped state on the tree).
anc

optional vector of values for the root state.
internal

logical value indicating whether to return states at internal nodes.

Details

This function conducts BM simulation on a tree with multiple rates and/or multiple evolutionary correlations between characters.

If vcv is a single matrix, instead of a list of matrices, sim.corrs will simulate multivariate BM with a single rate matrix.

Value

A matrix containing the multivariate tip states for the n species in the tree (and nodes if internal= TRUE).

Author(s)

Liam Revell [email protected]

References

Revell, L. J., and D. C. Collar (2009) Phylogenetic analysis of the evolutionary correlation using likelihood. Evolution, 63, 1090-1100.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

fastBM, make.simmap, read.simmap, sim.history, sim.rates

Simulate character history or a discrete character at the tips of the tree under some model

Description

Simulates discrete character evolution on a phylogenetic tree.

Usage

sim.history(tree, Q, anc=NULL, nsim=1, 
    direction=c("column_to_row","row_to_column"), ...)
sim.Mk(tree, Q, anc=NULL, nsim=1, ...)
sim.multiMk(tree, Q, anc=NULL, nsim=1, ...)

Arguments

tree

a phylogenetic tree as an object of class "phylo". For the case of sim.multiMk tree should be an object of class "simmap" in which the regimes for simulation have been mapped onto the tree.
Q

a matrix containing the instantaneous transition rates between states. Note that for sim.history by default (i.e., when direction="column_to_row", see below) normally this is the transpose of the matrix produced by fitDiscrete in the geiger package or make.simmap in phytools; that is to say the transition rate from i -> j should be given by Q[j,i]. However, if your matrix is properly conformed (i.e., rows or columns sum to 0), then sim.history will attempt to transpose your matrix correctly & will return an informative message (if message=TRUE, see below). For sim.Mk and sim.multiMk this matrix has the same conformation as in fitContinuous and make.simmap. For sim.multiMk Q should be a list of transition matrices with names that correspond to the states mapped onto the tree.
anc

an optional value for the state at the root node; if NULL, a random state will be assigned. anc can be a vector of states, in which one of the states will be chosen randomly for each simulation. For sim.history anc can be a vector of probabilities with names, in which case a state will be chosen in proportion to the given probabilities.
nsim

number of simulations.
direction

row/column direction of the input transition matrix, Q. "column_to_row" indicates that the transition rate from i -> j should be given by Q[j,i], while "row_to_column" indicates the converse.
...

other optional arguments. Currently only internal, a logical value indicating whether or not to return internal node states (defaults to internal=FALSE; and message, a logical indicating whether or not to turn on informational messages (defaults to message=TRUE).

Details

The function sim.history simulates a stochastic character history for a discretely valued character trait on the tree. The resultant tree is stored as a modified "phylo" object in stochastic character map (e.g., make.simmap) format.

The function sim.Mk simulates the states for a discrete character at the tips of the tree only.

Finally, the function sim.multiMk is the same as sim.Mk except that it permits the user to simulate under different values of Q in different parts of the tree.

Value

sim.history returns an object of class "simmap" (a tree with a mapped discrete character) or "multiSimmap" for nsim greater than one.

sim.Mk and sim.multiMk return a factor with the states of our discrete character at the tips of the tree only.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

fitMk, fitmultiMk, make.simmap, read.simmap, plotSimmap, sim.rates

Conduct simulation of state dependent rate variation

Description

Simulates two characters under a model in which the rate of one depends on the state of the other.

Usage

sim.ratebystate(tree, sig2x=1, sig2y=1, beta=c(0,1), ...)

Arguments

tree

phylogenetic tree.
sig2x

variance of the Brownian process of evolution for x, σx2\sigma_x^2.
sig2y

variance of the Brownian process of evolution for y when x-min(x)==1 (for logarithm=FALSE) or x==0 (for logarithm=TRUE).
beta

intercept and slope of the relationship between the value of x and the Brownian rate in y.
...

optional arguments which include method ("by.node" or "by.branch" indicating whether to assume the rate varies as a function of the node state or the mean branch state); plot, a logical value indicating whether or not to plot a traitgram ("phenogram") with the branches used for simulation of y after rescaling by the state of x; and logarithm, a logical value indicating whether or not simulate changes in the variance of Brownian evolution for y as an additive logarithm=FALSE or multiplicative function of x. The default is logarithm=FALSE.

Details

This function attempts to simulate two characters under a model in which the rate of evolution for the second (y) depends on the states for the first (x).

See ratebystate for more details.

Value

This function returns a matrix.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

fastBM, ratebystate

Brownian or OU simulation with multiple evolutionary regimes

Description

Simulates multi-rate or multi-regime continuous trait evolution on a phylogeny.

Usage

sim.rates(tree, sig2, anc=0, nsim=1, internal=FALSE, plot=FALSE)
multiOU(tree, alpha, sig2, theta=NULL, a0=NULL, nsim=1, internal=FALSE, ...)

Arguments

tree

is a stochastic map format phylogenetic tree in modified "phylo" format (e.g., see make.simmap).
sig2

a named vector containing the rates for each state; names should be states in mtree.
anc

optional value for the root state.
nsim

number of simulations.
internal

logical value indicating whether to return states at internal nodes.
plot

logical value indicating whether or not to visual the rate heterogeneity (default value is FALSE.
alpha

single value or vector of values of the OU α\alpha parameter.
theta

single value or vector of values of the OU θ\theta parameter.
a0

optional value of the root state. Defaults to zero.
...

optional arguments.

Details

The function sim.rates conducts BM simulation on a tree with multiple rates.

The function multiOU conducts multi-regime OU simulations on the tree under a range of conditions. multiOU uses a difference equation approximation of the OU process.

Value

A vector (for nsim=1) or matrix containing the tip states for the n species in the tree.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

fastBM, make.simmap, read.simmap, sim.history

Creates a graphical illustration of Brownian motion evolution on a phylogeny

Description

Simulates a discrete time phylogeny and Brownian motion trait, and generates a plot.

Usage

simBMphylo(n, t, sig2, plot=TRUE, ...)
## S3 method for class 'simBMphylo'
plot(x, ...)

Arguments

n

number of taxa to simulate in the output tree.
t

total time for the simulation.
sig2

the rate of evolution under Brownian motion, σ2\sigma^2, or a vector of rates. If the latter the length of the vector must exactly match t, otherwise the first element of sig2 will just be duplicated t times.
plot

optional logical value indicating whether or not the simulated object should be plotted.
...

optional arguments to be passed to the plot method.
x

in plot method, object of class "simBMphylo".

Details

The function simulates a discrete-time pure-birth phylogeny (for fixed N and t using rejection sampling) and then discrete-time Brownian motion on that tree. It then proceeds to generating a plot of the results.

Value

An object of class "simBMphylo" or a plot.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

bmPlot, fastBM, pbtree

Examples

set.seed(777)
simBMphylo(n=6,t=100,sig2=0.01)
## reset par to defaults
par(mfrow=c(1,1))
par(mar=c(5.1,4.1,4.1,2.1))

Matrix comparison using the method of random skewers

Description

Performs the random skewers matrix comparison method of Cheverud (1996).

Usage

skewers(X, Y, nsim=100, method=NULL)

Arguments

X

covariance matrix.
Y

covariance matrix.
nsim

number of random vectors.
method

method to generate a null distribution of the random skewers correlation between matrices. If method=NULL then the correlation will be compared to the correlation between random vectors; however this test has type I error substantially above the nominal level for ostensibly random matrices. Other values of method will be passed as covMethod to genPositiveDefMat for a more robust hypothesis test (see below). Recommended values include "unifcorrmat".

Details

This function performs the random skewers matrix comparison method of Cheverud (1996; also see Cheverud & Marroig 2007 for more details). In addition, it includes a more robust hypothesis test in which random covariance matrices are simulated under a variety of models, and then the mean correlation between response vectors to random skewers are computed.

Value

A list with the following components:

r

mean random skewers correlation.
p

p-value from simulation.

Author(s)

Liam Revell [email protected]

References

Cheverud, J. M. (1996) Quantitative genetic analysis of cranial morphology in the cotton-top (Saguinus oedipus) and saddle-back (S. fuscicollis) tamarins. J. Evol. Biol., 9, 5–42.

Cheverud, J. M. and G. Marroig (2007) Comparing covariance matrices: Random skewers method compared to the common principal components model. Genetics & Molecular Biology, 30, 461–469.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Split edge colors when descendant edges have different mapped states

Description

Splits the vertical linking-line color on a plotted tree to match the daughter edges.

Usage

splitEdgeColor(tree,colors,lwd=2)

Arguments

tree

object of class "simmap".
colors

named vector of colors to be used for plotting.
lwd

width of the plotted lines.

Details

This function splits the vertical line colors to match the daughter edges when the daughters have different states. Mostly to be used with trees generated using paintBranches or paintSubTree. Also used internally by plotSimmap.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

plotSimmap

Plots a phylogeny in two columns

Description

Plots a tree in two columns or windows.

Usage

splitplotTree(tree, fsize=1.0, ftype="reg", lwd=2, split=NULL, new.window=FALSE)
plotTree.splits(tree, splits=NULL, file=NULL, fn=NULL, ...)

Arguments

tree

an object of class "phylo".
fsize

relative font size for tip labels.
ftype

font type - options are "reg", "i" (italics), "b" (bold), or "bi" (bold-italics).
lwd

line width for plotting.
split

relative vertical position for splitting the tree (between 0 & 1).
new.window

whether or not to plot the split tree in a new window. If FALSE then the tree will be plotted in two columns within the same plotting window.
splits

for plotTree.splits relative positions (from 0 to 1) to split the tree across pages or devices.
file

filename if saving to a PDF file is desired. Otherwise will plot to the default plotting device.
fn

function to be executed on each plotted page. For instance, might be: function() cladelabels() if clade labels are desired.
...

other arguments to be passed to plotTree.

Value

Plots a tree.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

plotTree, plotSimmap

Split tree at a point

Description

Internal function for posterior.evolrate.

Usage

splitTree(tree, split)

Arguments

tree

phylogenetic tree.
split

split encoded as a list with two elements: node: the node number tipward of the split; and bp: the position along the branch to break the tree, measured from the rootward end of the edge.

Details

This function splits the tree at a given point, and returns the two subtrees as an object of class "multiPhylo".

Probably do not use this unless you can figure out what you are doing.

Value

Two trees in a list.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Create star phylogeny

Description

Creates a star phylogeny.

Usage

starTree(species, branch.lengths=NULL)

Arguments

species

a list of species.
branch.lengths

an optional list of branch lengths in the same order as species.

Details

Creates a star phylogeny with (optionally) user specified branch lengths.

Value

An object of class "phylo".

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

stree

Computes Strahler number for trees and nodes

Description

Computes the Strahler number of all nodes and tips in a phylogenetic tree.

Usage

strahlerNumber(tree, plot=TRUE)
extract.strahlerNumber(tree, i, plot=TRUE)

Arguments

tree

an object of class "phylo".
i

order of Strahler number to extract for extract.strahlerNumber.
plot

logical value indicating whether to plot the tree with Strahler numbers for node labels.

Details

The function strahlerNumber computes the Strahler number of all nodes and tips in the tree. For more information about Strahler numbers see https://en.wikipedia.org/wiki/Strahler_number. The function extract.strahlerNumber extracts all of the most inclusive clades of Strahler number i.

Value

Either a vector with the Strahler number for each tip and internal node; or (for extract.strahlerNumber the set of (most inclusive) subtrees with Strahler number i as an object of class "multiPhylo".

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Threshold model using Bayesian MCMC

Description

Fits the threshold model from quantitative genetics to data for two discrete characters or one discrete and one continuous trait, following Felsenstein (2012).

Usage

threshBayes(tree, X, types=NULL, ngen=10000, control=list(), ...)

Arguments

tree

an object of class "phylo".
X

a matrix or data frame containing values for a discrete character and a continuous character; or two discrete characters. The row names of X should be species names.
types

a vector of length ncol(X) containing the data types for each column of X, for instance c("discrete","continuous").
ngen

a integer indicating the number of generations for the MCMC.
control

a list of control parameters for the MCMC. Control parameters include: sample, the sampling interval for the MCMC; propvar, a vector containing (in this order) proposal variances for the two rates (if the type is "discrete" this will be ignored), the two ancestral states, and the correlation; propliab, a single proposal variance for the liabilities; pr.mean, a vector for the mean of the prior probability distributions for each parameter, in the same order as propvar; pr.liab, currently ignored; pr.var, a vector with variances for the prior densities for each parameter, in the same order as pr.mean - note that for the rates we use an exponential distribution so the first two means are currently ignored; and pr.vliab currently ignored.
...

other optional arguments. The argument auto.tune adjusts the proposal distribution to target an proposal acceptance rate (of 0.234, by default).

Details

This function uses Bayesian MCMC to fit the quantitative genetics threshold model (Felsenstein 2012) to data for two discrete characters or one discrete and one continuous character.

The plot method for the object class can be used to generate a three panel plot showing the likelihood profile, the mean acceptance rates (using a sliding window), and a profile plot for the correlation coefficient, r.

The density method for the object can be used to plot a posterior density of the correlation coefficient, r. This posterior density is of class "density.threshBayes" which can also be plotted using an plot method.

Discrete characters must be binary, but can be coded as any factor.

Value

This function returns an object of class "threshBayes" consisting of a list with at least the following two elements: par a matrix containing the posterior sample for the model parameters (evolutionary rates, ancestral states, and correlation); liab a matrix containing the posterior sample of the liabilities. For continuous characters, the liabilities are treated as known and so the posterior samples are just the observed values.

Author(s)

Liam Revell [email protected]

References

Felsenstein, J. (2012) A comparative method for both discrete and continuous characters using the threshold model. American Naturalist, 179, 145-156.

Revell, L. J. (2014) Ancestral character estimation under the threshold model from quantitative genetics. Evolution, 68, 743-759.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

anc.Bayes, bmPlot, evol.rate.mcmc

Examples

## Not run: 
## load data
data(bonyfish.tree)
data(bonyfish.data)
## run MCMC
mcmc<-threshBayes(bonyfish.tree,bonyfish.data,
    ngen=100000,plot=FALSE)
## visualize summary of MCMC
plot(mcmc)
## reset par
par(mfrow=c(1,1),mar=c(5.1,4.1,4.1,2.1))
## graph posterior density of correlation
plot(density(mcmc,bw=0.1))
## End(Not run)

Deviance Information Criterion from the threshold model

Description

Computes Deviance Information Criterion from the MCMC object returned by ancThresh.

Usage

threshDIC(tree, x, mcmc, burnin=NULL, sequence=NULL, method="pD")

Arguments

tree

phylogenetic tree.
x

a named vector containing discrete character states; or a matrix containing the tip species, in rows, and probabilities of being in each state, in columns.
mcmc

list object returned by ancThresh.
burnin

number of generations (not samples) to exclude as burn in; if not supplied then 20% of generations are excluded.
sequence

assumed ordering of the discrete character state. If not supplied and x is a vector then numerical-alphabetical order is assumed; if not supplied and x is a matrix, then the column order of x is used.
method

method for computing the effective number of parameters (options are "pD" and "pV").

Details

This function computes the Deviance Information Criterion from the MCMC object returned by ancThresh.

Value

A vector containing the mean deviance and deviance for the parameter means, the effective number of parameters, and the DIC.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2014) Ancestral character estimation under the threshold model from quantitative genetics. Evolution, 68, 743-759.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Spiegelhalter, D. J., N. G. Best, B. P. Carlin, and A. Van Der Linde (2002) Bayesian measures of model complexity and fit. Journal of the Royal Statistical Society Series B: Statistical Methodology, 64, 583-639.

See Also

ancThresh

Computes value for a threshold character from a liability and thresholds

Description

Internal function for ancThresh.

Usage

threshState(x, thresholds)

Arguments

x

liability.
thresholds

a named vector containing the thresholds.

Details

threshState can also be used to simulate threshold traits.

Value

A discrete character value.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2014) Ancestral character estimation under the threshold model from quantitative genetics. Evolution, 68, 743-759.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

ancThresh, threshDIC

Convert a character vector to a binary matrix

Description

Creates a binary matrix, normally from a factor.

Usage

to.matrix(x, seq)

Arguments

x

a vector of characters.
seq

the sequence for the columns in the output matrix.

Details

This function takes a vector of characters or a factor and computes a binary matrix.

Primarily designed to be used internally by make.simmap and rerootingMethod.

Value

A binary matrix of dimensions length(x) by length(seq).

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Creates an animation of a tree growing from left-to-right or upwards

Description

Animates a birth-death tree simulation.

Usage

tree.grow(..., res=200, direction="rightwards", ladderize=TRUE)

Arguments

...

arguments to pass to pbtree.
res

number of steps (the resolution of the animation). This also corresponds to the number of frames that will be created if the animation is to be converted to a .gif file.
direction

the direction to plot the tree. Only direction="rightwards" (the default) and direction="upwards" are supported.
ladderize

logical value indicating whether or not to 'ladderize' the plotted tree. (Defaults to TRUE.)

Details

This function simulates a birth-death tree under user-defined conditions and then creates an animation of that tree growing from left-to-right in the plotting device, or upwards.

Value

An object of class "phylo".

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

pbtree

Examples

## Not run: 
## to create a .gif with ImageMagick installed
png(file="pbtree-
tree.grow(b=0.06,d=0.02,t=100)
dev.off()
system("ImageMagick convert -delay 5 -loop 0 *.png pbtree-anim.gif")
## End(Not run)

Slices the tree at a particular point and returns all subtrees, or the tree rootward of the point

Description

Cut (or slice) a phylogenetic tree at a particular time point.

Usage

treeSlice(tree, slice, trivial=FALSE, prompt=FALSE, ...)

Arguments

tree

is a phylogenetic tree in "phylo" format.
slice

a real number indicating the height above the root at which to slice the tree.
trivial

a logical value indicating whether or not to return subtrees with a number of tips less than two (default is FALSE).
prompt

logical value indicating whether or not the height of the slice should be given interactively.
...

for prompt=TRUE, other arguments to be passed to plotTree. In addition, the argument orientation can be used to specify whether the "tipwards" subtrees or the "rootwards" phylogeny are/is to be returned by the function call (using those two argument values, respectively).

Details

This function slices a tree at a particular height above the root and returns all subtrees or all non-trivial subtrees (i.e., subtrees with more than 1 taxon). Uses extract.clade in the ape package.

treeSlice can also be used to crop the terminal fraction of a tree for orientation="rootwards".

Value

An object of class "phylo" or "multiPhylo".

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

extract.clade

Attempts to untangle crossing branches for plotting

Description

Attempts to "untangle" the branches of a tree that are tangled when plotting with plot.phylo, plotTree, or plotSimmap.

Usage

untangle(tree, method=c("reorder","read.tree"))

Arguments

tree

tree as an object of class "phylo" or "simmap".
method

method to use to attempt to untangle branches. method="reorder" uses two calls of reorder.phylo or reorderSimmap; method="read.tree" writes the tree to a text string and then reads it back into memory using read.tree.

Details

Generally speaking, this function is wraps several different internal functions that might be use to fix a badly conformed "phylo" or "simmap" object.

Value

An object of class "phylo" or "simmap", depending on the class of tree.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Calculates cophenetic (i.e., phylogenetic VCV) matrix

Description

Computes a phylogenetic variance-covariance matrix.

Usage

vcvPhylo(tree, anc.nodes=TRUE, ...)

Arguments

tree

object of class "phylo".
anc.nodes

logical value indicating whether or not to include ancestral nodes.
...

optional arguments including internal (synonym of anc.nodes) and model (can be "BM", "OU", or "lambda".

Details

This function returns a so-called phylogenetic variance covariance matrix (e.g., see vcv.phylo), but (optionally) including ancestral nodes, as well as under multiple evolutionary models.

vcvPhylo is designed primarily for internal use by other phytools functions.

Value

A matrix.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

Write a stochastic character mapped tree to file

Description

Writes one or multiple stochastic character mapped trees to file in several formats (following Bollback, 2006).

Usage

write.simmap(tree, file=NULL, append=FALSE, map.order=NULL, quiet=FALSE, 
    format="phylip", version=1.0)

Arguments

tree

an object of class "simmap" or "multiSimmap".
file

an optional filename.
append

a logical value indicating whether to append to file.
map.order

a optional value specifying whether to write the map in left-to-right or right-to-left order. Acceptable values are "left-to-right" or "right-to-left" or some abbreviation of either. If not provided, write.simmap will use attr(tree,"map.order") if available.
quiet

logical value indicating whether or not to print a warning message when map.order is neither specified by a function argument or as an attribute of tree.
format

file format for output.
version

version of SIMMAP. Note that the options are 1.0 and 1.5. version=1.5 is generally recommended because in this format the tree can also be parsed by typical tree readers, but absent its mapped trait.

Value

A file.

Author(s)

Liam Revell [email protected]

References

Bollback, J. P. (2006) Stochastic character mapping of discrete traits on phylogenies. BMC Bioinformatics, 7, 88.

Huelsenbeck, J. P., R. Neilsen, and J. P. Bollback (2003) Stochastic mapping of morphological characters. Systematic Biology, 52, 131-138.

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

make.simmap, read.simmap, plotSimmap

Write a tree to file with ancestral states and (optionally) CIs at nodes

Description

This function writes a tree to file with ancestral character states and (optionally) 95% confidence intervals stored as node value.

Usage

writeAncestors(tree, Anc=NULL, file="", digits=6, format=c("phylip","nexus"), 
   ...)

Arguments

tree

a phylogenetic tree or set of trees as an object of class "phylo" or "multiPhylo".
Anc

a vector of ancestral states, a list containing the ancestral states and 95% confidence intervals (as from fastAnc or ace, or a list of such results.
file

an optional string with the filename for output.
digits

an integer indicating the number of digits to print for branch lengths and ancestral character values.
format

a string indicating whether to output the result in simple Newick (i.e., "phylip") or Nexus format.
...

additional arguments including x: a vector of character values, in which case ancestral states are estimated internally using fastAnc; and CI: a logical value indicating whether or not to estimate 95% confidence intervals.

Value

A file, string, or vector of strings.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

ace, fastAnc, write.tree

Write a tree to file in Nexus format

Description

Writes one or multiple phylogenetic trees to file in NEXUS format.

Somewhat redundant with write.nexus.

Usage

writeNexus(tree, file="")

Arguments

tree

object of class "phylo" or "multiPhylo".
file

file name for output.

Value

Trees written to file.

Author(s)

Liam Revell [email protected]

References

Revell, L. J. (2024) phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ, 12, e16505.

See Also

write.simmap, write.nexus