Calculates maxdist for all pairs of taxa in a phylogeny.

Description

allmaxdist Uses maxdist to calcualte the maximum phenotypic. distance between the ancestors of all pairs of taxa in a phylogeny. By default outputs these as a matrix, but can also output a list. Can take some time to run for large trees.

Usage

allmaxdist(phyl, phendata, mat = TRUE)

Arguments

Details

Regarding the output: the matrix is better organized, but the list avoids all the zeroes and is probably better for making histograms.

Value

A matrix or list of all maxdist values for all pairs of taxa in the phylogeny.

References

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

Revell, L. J. (2012) phytools: An R package for phylogenetic comparative biology (and other things). Methods Ecol. Evol. 3 217-223.

Examples

phyl<-rtree(10)
phendata<-fastBM(phyl,nsim=2)
answer<-allmaxdist(phyl,phendata,mat=TRUE)

Extracts lineages leading to two tips, t1 and t2, from their most recent common ancestor.

Description

Extracts lineages leading to two tips, t1 and t2, from their most recent common ancestor.

Usage

ancestrallineages(phyl, phendata, t1, t2)

Arguments

Details

None

Value

A list containing two matrices. Each matrix corresponds to a tip. The matrix consists of reconstructed ancestral values for all nodes leading from the mrca of both tips to the tip.

References

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

Revell, L. J. (2012) phytools: An R package for phylogenetic comparative biology (and other things). Methods Ecol. Evol. 3 217-223.

Stayton, C.T. (2015). The definition, recognition, and interpretation of convergent evolution, and two new measure for quantifying and assessing the significance of convergence. Evolution 69:2140-2153.

Examples

phyl<-rtree(10)
phendata<-fastBM(phyl,nsim=2)
answer<-ancestrallineages(phyl,phendata,"t1","t2")

Quantifies convergent evolution by the ratio of the current to maximum past phenotypic distance between two or more lineages, as described in Stayton (2015). Code written by Jonathan S. Mitchell for Zelditch et al. (2017).

Description

calcConv prepares arguements for the CalcCs function

Usage

calcConv(phy, traits, focaltaxa, anc = NULL, VERBOSE = FALSE)

Arguments

Details

calcConv is a wrapper function which formats data, performs ancestral state reconstructions, obtains distance matrices, and determines pairwise combinations of focal taxa, which are then used as arguements for the CalcCs function, which calculates values for C1-C4 of Stayton (2015) for each pair of putatively convergent taxa.

Value

C1-C4 convergence measures for all pairs of putatively convergent taxa.

References

Stayton, C.T. 2015. The definition, recognition, and interpretation of convergent evolution, and two new measures for quantifying and assessing the significance of convergence. Evolution 69:2140-2453.

Zelditch, M.L., J. Ye, J.S. Mitchell, and D.L. Swiderski. 2017. Rare ecomorphological convergence on a complex adaptive landscape: Body size and diet mediate evolution of jaw shape in squirrels (Sciuridae). Evolution 71:633-649.

Examples

phy<-rtree(100)
traits<-fastBM(phy,nsim=3)
focaltaxa<-c("t1","t50","t100")
answer<-calcConv(phy,traits,focaltaxa,anc=NULL,VERBOSE=FALSE)

Computes Ct-metric scores for putatively convergent tips (or groups of tips) given a set of user provided phenotypic characters and a time calibrated phylogeny.

Description

calcConvCt Computes Ct-metric scores for putatively convergent tips (or groups of tips) given a set of user provided phenotypic characters and a time calibrated phylogeny.

Usage

calcConvCt(
  phy,
  traits,
  focaltaxa,
  groups = NULL,
  ace = NULL,
  conservative = FALSE,
  VERBOSE = FALSE
)

Arguments

Details

Function incorporates the optimizations introduced by Zelditch et al. (2017), which significantly improve runtimes

Reconstructions part way along branches are obtained using equation 2 of Felsenstein (1985), following code modified from the phytools (Revell, 2012) function contMap

Value

A list of the following components:

mean a named vector of Ct-metrics averaged from all pairwise comparisons of focaltaxa. If user provided groups, this is based only on comparisons between taxa belonging to different groups.

Cmat a matrix of Ct-metrics for each pairwise comparison.

path_df a list of dataframes, one per pairwise comparison of the focal taxa, each containing information from all timepoint measurements of the two putatively convergent lineages. These provide the nodes at which comparisons were drawn, the evolutionary path along which that node fell (i.e., leading to one of two tips), the node height, reconstructed ancestral states at that node for each phenotypic trait, reconstructed ancestral values for each trait along the opposite path, and the phenotypic distance between the two lineages at that point.

grp.mean a matrix of Ct-metrics summarized for inter-group comparisons, returned only if user defined groups were specified. Provides overall results matching those reported in "mean", results for each unique inter-group comparison, and results averaged with equal weight given to each unique inter-group comparison (i.e., ignoring differences in the number of tips in each group).

limits a list of tree heights used to constrain Dmax.t calculations for each pairwise comparison in conservative analyses. Only returned if conservative == TRUE.

References

Grossnickle DM, Brightly WH, Weaver LN, Stanchak KE, Roston RA, Pevsner SK, Stayton CT, Polly PD, Law CJ. 2022. A cautionary note on quantitative measures of phenotypic convergence. in revision Zelditch ML, Ye J, Mitchell JS, Swiderski DL. 2017. Rare ecomorphological convergence on a complex adaptive landscape: Body size and diet mediate evolution of jaw shape in squirrels (Sciuridae). Evolution 71: 633-649 Stayton CT. 2015. The definition, recognition, and interpretation of convergent evolution and two new measures for quantifying and assessing the significance of convergence. Evolution 69(8): 2140-2153. Revell, L. J. (2012) phytools: An R package for phylogenetic comparative biology (and other things). Methods Ecol. Evol., 3, 217-223. Felsenstein, J. 1985. Phylogenies and the comparative method. American Naturalist, 125, 1-15.

Examples

## Not run: 
library(phytools)
library(geiger)

# create time calibrated tree
mytree<-rtree(100)
mycalibration <- makeChronosCalib(mytree, node="root", age.max=50)
phy <- chronos(mytree, lambda = 1, model = "correlated", calibration = mycalibration, 
control = chronos.control() )
class(phy)<-"phylo"

# create three normally distributed phenotypic traits
traits <- cbind(rnorm(Ntip(phy)),rnorm(Ntip(phy)),rnorm(Ntip(phy)))
rownames(traits) <- phy$tip.label

#	select two random tips, excluding sister taxa
pairs <- apply(combn(phy$tip.label,2),2,function(x) nodepath(phy,which(phy$tip.label == x[1]),
which(phy$tip.label == x[2])))
nosis <- combn(phy$tip.label,2)[,unlist(lapply(pairs, function(x) length(x) > 3))]
focaltaxa <- nosis[,sample(1:ncol(nosis),1)]

system.time(run <- calcConvCt(phy, traits, focaltaxa))
system.time(run2 <- convSigCt(phy, traits, focaltaxa, nsim=10))

plotCt(output = run2,phy = phy,focaltaxa = focaltaxa)

## End(Not run)

Calculates the C1-C4 measures of convergent evolution between two lineages as described in Stayton (2015). All measures quantify convergence by the ratio of current to maximum past phenotypic distance between lineages. Can be used as-is but more often will be used within the calcConv script. Code written by Jonathan S. Mitchell for Zelditch et al. (2017)

Description

calcCs calculates the C1-C4 measures of convergent evolution

Usage

calcCs(tips, ancList, allDists, phy, VERBOSE = FALSE)

Arguments

Details

calcCs calculates values of C1-C4, all of which are fundamentally based on comparing the current phenotypic distance between two tips to the maximum past distances between the ancestors of those tips. Higher values indicate a greater amount of past phenotypic distance which has been "closed" by subsequent evolution, and thus greater convergence. C1 is the ratio of tip to maximum ancestral distance. C2 is the difference of those two values. C3 scales C2 by the total amount of evolution that has occured in the two lineages. C4 scales C2 by the total amount of evolution that has occurred in the entire phylogeny. The arguments for this function will usually be obtained from the calcConv script in convevol - this allows certain computationally-intensive steps (e.g., calculating ancestral states) to only be performed once, thus saving a great deal of time. This script also corrects an error in the calculation of C4 of previous versions of convevol.

Value

C1-C4 convergence measures for all pairs of putatively convergent taxa.

References

Stayton, C.T. 2015. The definition, recognition, and interpretation of convergent evolution, and two new measures for quantifying and assessing the significance of convergence. Evolution 69:2140-2453.

Zelditch, M.L., J. Ye, J.S. Mitchell, and D.L. Swiderski. 2017. Rare ecomorphological convergence on a complex adaptive landscape: Body size and diet mediate evolution of jaw shape in squirrels (Sciuridae). Evolution 71:633-649.

Computes Ct values for a pair of tips. Internal, called in calcConv.

Description

calcCsCt Computes Ct values for a pair of tips. Internal, called in calcConv.

Usage

calcCsCt(
  tips,
  ancList,
  allDists,
  phy,
  VERBOSE = FALSE,
  allVals,
  edge,
  lim.height = NULL
)

Arguments

Details

Function incorporates the optimizations introduced by Zelditch et al. (2017), which significantly improve runtimes

Reconstructions part way along branches are obtained using equation 2 of Felsenstein (1985), following code modified from the phytools (Revell, 2012) function contMap

Value

A list of the Ct values

References

Grossnickle DM, Brightly WH, Weaver LN, Stanchak KE, Roston RA, Pevsner SK, Stayton CT, Polly PD, Law CJ. 2022. A cautionary note on quantitative measures of phenotypic convergence. in revision Zelditch ML, Ye J, Mitchell JS, Swiderski DL. 2017. Rare ecomorphological convergence on a complex adaptive landscape: Body size and diet mediate evolution of jaw shape in squirrels (Sciuridae). Evolution 71: 633-649 Stayton CT. 2015. The definition, recognition, and interpretation of convergent evolution and two new measures for quantifying and assessing the significance of convergence. Evolution 69(8): 2140-2153. Revell, L. J. (2012) phytools: An R package for phylogenetic comparative biology (and other things). Methods Ecol. Evol., 3, 217-223. Felsenstein, J. 1985. Phylogenies and the comparative method. American Naturalist, 125, 1-15.

Calculates all phenotypic changes that occur on all branches of a phylogeny.

Description

Calculates the Euclidean distance between all ancestors and descendants on a phylogeny to reconstruct the phenotypic changes that occur along all edges of a phylogeny.

Usage

calcchanges(phyl, phendata)

Arguments

Details

Calculates the Euclidean distance between all ancestors and descendants on a phylogeny to reconstruct the phenotypic changes that occur along all edges of a phylogeny.

Value

A vector in which each element represents an edge of the phylogeny, and the values are the magnitudes of evolutionary change that occur along those edges.

References

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

Revell, L. J. (2012) phytools: An R package for phylogenetic comparative biology (and other things). Methods Ecol. Evol. 3 217-223.

Examples

phyl<-rtree(10)
phendata<-fastBM(phyl,nsim=5)
changes<-calcchanges(phyl,phendata)

Uses simulations to assess the significance of C1-C4 measures of convergent evolution as described in Stayton (2015). Code written by Jonathan S. Mitchell for Zelditch et al. (2017)

Description

convSig calculates the significance of measures of convergent evolution.

Usage

convSig(phy, traits, focaltaxa, user.ace = NULL, nsim = 1000)

Arguments

Details

This script simulates data according to a Brownian motion model of evolution, and then assesses convergene on that simulated data. The number of times that the simulated data produces greater convergence than that observed in the empirical data is used to calculate a P-value.

Value

C1-C4 convergence measures for all pairs of putatively convergent taxa and their associated p-values.

References

Stayton, C.T. 2015. The definition, recognition, and interpretation of convergent evolution, and two new measures for quantifying and assessing the significance of convergence. Evolution 69:2140-2453.

Zelditch, M.L., J. Ye, J.S. Mitchell, and D.L. Swiderski. 2017. Rare ecomorphological convergence on a complex adaptive landscape: Body size and diet mediate evolution of jaw shape in squirrels (Sciuridae). Evolution 71:633-649.

Examples

phy<-rtree(100)
traits<-fastBM(phy,nsim=3)
focaltaxa<-c("t1","t50","t100")
answer<-convSig(phy,traits,focaltaxa,user.ace=NULL,nsim=10)

Computes and conducts significance tests on Ct-metric scores for putatively convergent tips (or groups of tips) given a set of user provided phenotypic characters and a time calibrated phylogeny.

Description

calcConvCt Computes and conducts significance tests on Ct-metric scores for putatively convergent tips (or groups of tips) given a set of user provided phenotypic characters and a time calibrated phylogeny.

Usage

convSigCt(
  phy,
  traits,
  focaltaxa,
  groups = NULL,
  user.ace = NULL,
  nsim = 1000,
  ...
)

Arguments

Details

Function incorporates the optimizations introduced by Zelditch et al. (2017), which significantly improve runtimes

Reconstructions part way along branches are obtained using equation 2 of Felsenstein (1985), following code modified from the phytools (Revell, 2012) function contMap

Value

A list of the following components:

pvals a matrix containing Ct1 - Ct4 and p-values from significance tests for each

meas.Cmat a matrix of Ct values for each pairwise comparison of focaltaxa

meas.path a list of dataframes, one per pairwise comparison of focaltaxa, each containing information from all timepoint measurements of the two putatively convergent lineages. These provide the nodes at which comparisons were drawn, the evolutionary path along which that node fell (i.e., leading to one of two tips), the node height, reconstructed ancestral states at that node for each phenotypic trait, reconstructed ancestral values for each trait along the opposite path, and the phenotypic distance between the two lineages at that point.

sim.avg average Ct values from all pairwise comparisons between focaltaxa using simulated Brownian motion traits, number of columns corresponds to the user provided number of simulations

sim.path a list of dataframes as in meas.path, but obtained using simulated data. Length of object determined by number of pairwise comparisons multiplied by the number of simulated datasets.

grp.mean a matrix of Ct-metrics summarized for inter-group comparisons, returned only if user defined groups were specified. Provides overall results matching those reported in "mean", results for each unique inter-group comparison, and results averaged with equal weight given to each unique inter-group comparison (i.e., ignoring differences in the number of tips in each group).

grp.pvals a matrix of p-values associated with Ct values in grp.mean object. Returned only if user defined groups were specified.

limits a list of tree heights used to constrain Dmax.t calculations for each pairwise comparison in conservative analyses. Only returned if conservative == TRUE.

References

Grossnickle DM, Brightly WH, Weaver LN, Stanchak KE, Roston RA, Pevsner SK, Stayton CT, Polly PD, Law CJ. 2022. A cautionary note on quantitative measures of phenotypic convergence. in revision Zelditch ML, Ye J, Mitchell JS, Swiderski DL. 2017. Rare ecomorphological convergence on a complex adaptive landscape: Body size and diet mediate evolution of jaw shape in squirrels (Sciuridae). Evolution 71: 633-649 Stayton CT. 2015. The definition, recognition, and interpretation of convergent evolution and two new measures for quantifying and assessing the significance of convergence. Evolution 69(8): 2140-2153. Revell, L. J. (2012) phytools: An R package for phylogenetic comparative biology (and other things). Methods Ecol. Evol., 3, 217-223. Felsenstein, J. 1985. Phylogenies and the comparative method. American Naturalist, 125, 1-15.

Examples

## Not run: 
library(phytools)
library(geiger)

# create time calibrated tree
mytree<-rtree(100)
mycalibration <- makeChronosCalib(mytree, node="root", age.max=50)
phy <- chronos(mytree, lambda = 1, model = "correlated", calibration = mycalibration, 
control = chronos.control() )
class(phy)<-"phylo"

# create three normally distributed phenotypic traits
traits <- cbind(rnorm(Ntip(phy)),rnorm(Ntip(phy)),rnorm(Ntip(phy)))
rownames(traits) <- phy$tip.label

#	select two random tips, excluding sister taxa
pairs <- apply(combn(phy$tip.label,2),2,function(x) nodepath(phy,which(phy$tip.label == x[1]),
which(phy$tip.label == x[2])))
nosis <- combn(phy$tip.label,2)[,unlist(lapply(pairs, function(x) length(x) > 3))]
focaltaxa <- nosis[,sample(1:ncol(nosis),1)]

system.time(run <- calcConvCt(phy, traits, focaltaxa))
system.time(run2 <- convSigCt(phy, traits, focaltaxa, nsim=100))

plotCt(output = run2,phy = phy,focaltaxa = focaltaxa)

## End(Not run)

Quantify convergence by the number of convergent events

Description

This program takes in a set of taxa that are already suspected to be convergent in a particular area of morphospace. It then counts the number of times that a lineage has invaded that region of morphospace.

Usage

convnum(
  phy,
  phendata,
  convtips,
  plot = TRUE,
  ellipse = NULL,
  plotellipse = NULL
)

Arguments

Details

This function will construct an ellipse around all convergent taxa. Then it will reconstruct ancestral states throughout the phylogeny, and use those to determine how many lineages have crossed into this ellipse from the outside.

Value

The number of lineages that have crossed into the region of trait space occupied by the convergent taxa.

References

Maechler, M., Rousseeuw, P., Struyf, A., Hubert, M., Hornik, K.(2013). cluster: Cluster Analysis Basics and Extensions. R package version 1.14.4.

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

Revell, L. J. (2012) phytools: An R package for phylogenetic comparative biology (and other things). Methods Ecol. Evol. 3 217-223.

Examples

phy<-rtree(10)
phendata<-fastBM(phy,nsim=2)
convtips<-c("t1","t2","t3")
answer<-convnum(phy,phendata,convtips,plot=TRUE,ellipse=NULL,plotellipse=NULL)

Assess the significance of convergent evolution using simulations and the convnum metric

Description

Simulates evolution along a given phylogeny, using parameters derived from observed data, and calculates the convnum metric for each simulation for a set of user-defined taxa. Then compares the observed convnum value to the simulated values to assess the significance of the observed levels of convergent evolution.

Usage

convnumsig(
  phy,
  phendata,
  convtips,
  nsim,
  ellipse = NULL,
  plot = FALSE,
  plotellipse = NULL
)

Arguments

Details

None

Value

A list, consisting first of the p-value for the observed convnum, and second of a vector containing all of the simulated convnum values. Also displays a histogram of all of the simulated convnum values.

References

Maechler, M., Rousseeuw, P., Struyf, A., Hubert, M., Hornik, K.(2013). cluster: Cluster Analysis Basics and Extensions. R package version 1.14.4.

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

Revell, L. J. (2012) phytools: An R package for phylogenetic comparative biology (and other things). Methods Ecol. Evol. 3 217-223.

Examples

phy<-rtree(10)
phendata<-fastBM(phy,nsim=2)
convtips<-c("t1","t2","t3")
answer<-convnumsig(phy,phendata,convtips,10,plot=FALSE,ellipse=NULL,plotellipse=NULL)

Quantifies convergent evolution using the C1, C2, C3, and C4 measures as described by Stayton (2015).

Description

Calculates the current phenotypic distance (Euclidean) between two taxa. Then uses ancestral state reconstruction under a BM model to calculate the maximum phenotypic distance at any time between lineages leading from the most recent common ancestor of those two taxa to the tips. Also calculate the total amount of phenotypic evolution in the clade defined by the most recent common ancestor of those lineages, and the total amount of phenotypic evolution in the input tree. These quantities are used to calcualte C1-C4: C1 = 1-(current distance / maximum ancestral distance); C2 = maximum ancestral distance - current distance; C3=C2/(total phenotypic evolution in the clade defined by the two taxa); C4 = C2/(total amount of phenotypic evolution in the entire tree). If more than two convergent taxa are input, then C1-C4 are calculated for all possible pairs of taxa, and averaged.

Usage

convrat(phyl, phendata, convtips)

Arguments

Details

None

Value

Four numbers - C1, C2, C3, C4.

References

Maechler, M., Rousseeuw, P., Struyf, A., Hubert, M., Hornik, K.(2013). cluster: Cluster Analysis Basics and Extensions. R package version 1.14.4.

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

Revell, L. J. (2012) phytools: An R package for phylogenetic comparative biology (and other things). Methods Ecol. Evol. 3 217-223.

Stayton, C.T. (2015). The definition, recognition, and interpretation of convergent evolution, and two new measure for quantifying and assessing the significance of convergence. Evolution 69:2140-2153.

Examples

phyl<-rtree(10)
phendata<-fastBM(phyl,nsim=2)
convtips<-c("t1","t2","t3")
answer<-convrat(phyl,phendata,convtips)

Tests the signifiance of convergent evolution by the ratio of the current to maximum past phenotypic distance

Description

convratsig tests the significance of convergence (as quantified by convrat) using evolutionary simulations.

Usage

convratsig(phyl, phendata, convtips, nsim)

Arguments

Details

The function simulates evolution via Brownian motion using the input tree and parameters derived from the observed data. It calculates a convergence metric for each simulation and calculates statistics from the number of times the simulated value exceeds the observed value.

Value

The convergence metric of interest (C1, C2, etc...), a cutoff value (the value that the observed measure would have to exceed in order to be considered significant), a P-value for the statistic, and all simulated values.

References

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

Revell, L. J. (2012) phytools: An R package for phylogenetic comparative biology (and other things). Methods Ecol. Evol. 3 217-223.

Examples

phyl<-rtree(10)
phendata<-fastBM(phyl,nsim=2)
convtips<-c("t1","t2","t3")
answer<-convratsig(phyl,phendata,convtips,10)

Find the ancestor of a given node in a phylogeny

Description

This function will find the ancestor of a given node in a phylogeny. It will return a two-element vector, which will contain both the node of the ancestor and the number of the edge that connects the node and ancestor.

Usage

findanc(phyl, node)

Arguments

Details

Returns a two-element vector. The node of the ancestor is first; the edge that connects that node with its ancestor is second.

Value

A two-element vector, where the first element is the node of the ancestor and the second element is the number of the edge that connects the node and ancestor (i.e., the row number in phyl$edge).

References

Paradis, E., J. Claude, and K. Strimmer (2004) APE: Analyses of phylogenetics and evolution in R langauge. Bioinformatics, 20, 289-290. Paradis, E. (2012) Analysis of Phylogenetics and Evolution with R (Second Edition). New York: Springer.

Examples

phyl<-rtree(10)
ancestor<-findanc(phyl,1)

Converts taxon names to tip/edge numbers

Description

Converts taxon names to corresponding tip/edge numbers in the phylogeny.

Usage

labelstonumbers(phyl, tips)

Arguments

Details

Simply reads in taxon names, determines which tip or edge number they correspond to, and returns those values

Value

The numbers of all of the tips of interest.

References

Paradis, E., J. Claude, and K. Strimmer (2004) APE: Analyses of phylogenetics and evolution in R langauge. Bioinformatics, 20, 289-290. Paradis, E. (2012) Analysis of Phylogenetics and Evolution with R (Second Edition). New York: Springer.

Examples

phyl<-rtree(10)
nums<-labelstonumbers(phyl,c("t1","t2","t3"))

Calculates the maximum phenotypic distance between the lineages leading to a pair of taxa.

Description

maxdist uses ancestral state reconstruction to determine the maximum distance between any ancestors of those two taxa.

Usage

maxdist(phyl, phendata, t1, t2)

Arguments

Details

Returns the maximum Euclidean distance between any pair of ancestors of the two taxa, whether or not those two ancestors are contemporaries.

Value

The maximum phenotypic distance between the two taxa

References

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

Revell, L. J. (2012) phytools: An R package for phylogenetic comparative biology (and other things). Methods Ecol. Evol. 3 217-223.

Examples

phyl<-rtree(10)
phendata<-fastBM(phyl,nsim=2)
answer<-maxdist(phyl,phendata,1,10)

Reconstructs ancestral states for multiple characters

Description

Uses fastAnc to reconstruct ancestral states for multiple phenotypic characters

Usage

multianc(phy, phendata)

Arguments

Details

None

Value

A matrix with the tips data in the first n rows and the ancestral data in the remaining n-1 rows.

References

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

Revell, L. J. (2012) phytools: An R package for phylogenetic comparative biology (and other things). Methods Ecol. Evol. 3 217-223.

Examples

phy<-rtree(10)

phendata<-fastBM(phy,nsim=2)

ancs<-multianc(phy,phendata)

Sample phylogeny for use in convevol examples and tutorial

Description

It's a sample phylogeny with 100 tips.

Format

A tree file

Plots calcConv or convSig output as a two-dimensional time series.

Description

plot2D Plots calcConv or convSig output as a two-dimensional time series.

Usage

plot2D(
  Ct,
  phy,
  tip,
  foc.trt,
  trait,
  pca = FALSE,
  save = FALSE,
  filename = "frame",
  dir = NULL,
  leg = FALSE,
  leg.pos = "topleft",
  width = 480,
  height = 480,
  ...
)

Arguments

Details

None

Value

Plots tracking putatively convergent taxa in two-dimensional morphospace through time

A table with trait values, morphospace distance, and nodeheights conincident with Dmax.t. See meas.path output from calcConvCt and convSigCt

References

Grossnickle DM, Brightly WH, Weaver LN, Stanchak KE, Roston RA, Pevsner SK, Stayton CT, Polly PD, Law CJ. 2022. A cautionary note on quantitative measures of phenotypic convergence. in revision Zelditch ML, Ye J, Mitchell JS, Swiderski DL. 2017. Rare ecomorphological convergence on a complex adaptive landscape: Body size and diet mediate evolution of jaw shape in squirrels (Sciuridae). Evolution 71: 633-649 Stayton CT. 2015. The definition, recognition, and interpretation of convergent evolution and two new measures for quantifying and assessing the significance of convergence. Evolution 69(8): 2140-2153. Revell, L. J. (2012) phytools: An R package for phylogenetic comparative biology (and other things). Methods Ecol. Evol., 3, 217-223. Felsenstein, J. 1985. Phylogenies and the comparative method. American Naturalist, 125, 1-15.

Examples

## Not run: 
library(phytools)
library(geiger)

# create time calibrated tree
mytree<-rtree(100)
mycalibration <- makeChronosCalib(mytree, node="root", age.max=50)
phy <- chronos(mytree, lambda = 1, model = "correlated", 
calibration = mycalibration, control = chronos.control() )
class(phy)<-"phylo"

# create three normally distributed phenotypic traits
traits <- cbind(rnorm(Ntip(phy)),rnorm(Ntip(phy)),rnorm(Ntip(phy)))
colnames(traits) <- c("V1","V2","V3")
rownames(traits) <- phy$tip.label

#	select two random tips, excluding sister taxa
pairs <- apply(combn(phy$tip.label,2),2,function(x) nodepath(phy,
which(phy$tip.label == x[1]),which(phy$tip.label == x[2])))
nosis <- combn(phy$tip.label,2)[,unlist(lapply(pairs, function(x) length(x) > 3))]
focaltaxa <- nosis[,sample(1:ncol(nosis),1)]

system.time(run <- calcConvCt(phy, traits, focaltaxa))
system.time(run2 <- convSigCt(phy, traits, focaltaxa, nsim=100))

plot2D(run, phy, focaltaxa[1:2], colnames(traits)[1:2], traits)

## End(Not run)

Plots calcConv or convSig output.

Description

plotCt Plots calcConv or convSig output.

Usage

plotCt(
  output,
  phy,
  focaltaxa,
  nsim = 25,
  col = c("black", "forest green", "dodgerblue2", "firebrick1", "purple", "orange",
    "salmon", "goldenrod", "springgreen2", "plum1"),
  groups = NULL,
  ...
)

Arguments

Details

Creates a plot that shows the phenotypic distances between pairs of putatively convergent lineages over time. When these distances decrease, convergence has occurred. When more than two putatively convergent taxa are analyzed, all pairs are plotted.

Value

A plot identifying putatively convergent taxa in the provided phylogeny and tracking the change in phenotypic distance between taxa since their most recent common ancestor

References

Grossnickle DM, Brightly WH, Weaver LN, Stanchak KE, Roston RA, Pevsner SK, Stayton CT, Polly PD, Law CJ. 2022. A cautionary note on quantitative measures of phenotypic convergence. in revision Zelditch ML, Ye J, Mitchell JS, Swiderski DL. 2017. Rare ecomorphological convergence on a complex adaptive landscape: Body size and diet mediate evolution of jaw shape in squirrels (Sciuridae). Evolution 71: 633-649 Stayton CT. 2015. The definition, recognition, and interpretation of convergent evolution and two new measures for quantifying and assessing the significance of convergence. Evolution 69(8): 2140-2153. Revell, L. J. (2012) phytools: An R package for phylogenetic comparative biology (and other things). Methods Ecol. Evol., 3, 217-223. Felsenstein, J. 1985. Phylogenies and the comparative method. American Naturalist, 125, 1-15.

Examples

#' create time calibrated tree
phy<-rcoal(100)

# create three normally distributed phenotypic traits
traits <- cbind(rnorm(Ntip(phy)),rnorm(Ntip(phy)),rnorm(Ntip(phy)))
rownames(traits) <- phy$tip.label
focaltaxa <- sample(phy$tip.label, 5)

system.time(run2 <- convSigCt(phy, traits, focaltaxa, nsim=10))

plotCt(output = run2,phy = phy,focaltaxa = focaltaxa)

Plots an ellipse

Description

Plots a minimum ellipse around a set of data

Usage

plotellipse(ellipse)

Arguments

Details

Routine adapted from a suggestion made on CrossValidated: http://stats.stackexchange.com/questions/9898/how-to-plot-an-ellipse-from-eigenvalues-and-eigenvectors-in-r

Value

Nothing - just plots the ellipse.

References

Maechler, M., Rousseeuw, P., Struyf, A., Hubert, M., Hornik, K.(2013). cluster: Cluster Analysis Basics and Extensions. R package version 1.14.4.

Extracts a vector of ancestors for a given taxon. Code written by Jonathan S. Mitchell for Zelditch et al. (2017)

Description

pullNodeSeq Extracts a vector of all ancestors of a given taxon in a phylogeny.

Usage

pullNodeSeq(phy, tip)

Arguments

Value

A vector of ancestors

References

Zelditch, M.L., J. Ye, J.S. Mitchell, and D.L. Swiderski. 2017. Rare ecomorphological convergence on a complex adaptive landscape: Body size and diet mediate evolution of jaw shape in squirrels (Sciuridae). Evolution 71:633-649.

Examples

phylogeny<-rtree(100)
answer<-pullNodeSeq(phy=phylogeny,tip="t1")

Calculates the number of measurements that can be made between two lineages for each pairwise comparison within a set of putatively convergent tips (group identity may also be taken into account). Useful for determining which comparisons are not informative, and constructing a group object before running calcConvCt or convSigCt.

Description

pwCheck Calculates the number of measurements that can be made between two lineages for each pairwise comparison within a set of putatively convergent tips (group identity may also be taken into account). Useful for determining which comparisons are not informative, and constructing a group object before running calcConvCt or convSigCt.

Usage

pwCheck(phy, focaltaxa, groups = NULL, conservative = FALSE)

Arguments

Value

A list of the following components:

taxa a matrix of uninformative tip comparisons

path a vector with the number of measurements for all pairwise comparisons - a summary of this is also printed when running the function

References

Grossnickle DM, Brightly WH, Weaver LN, Stanchak KE, Roston RA, Pevsner SK, Stayton CT, Polly PD, Law CJ. 2022. A cautionary note on quantitative measures of phenotypic convergence. in revision Zelditch ML, Ye J, Mitchell JS, Swiderski DL. 2017. Rare ecomorphological convergence on a complex adaptive landscape: Body size and diet mediate evolution of jaw shape in squirrels (Sciuridae). Evolution 71: 633-649 Stayton CT. 2015. The definition, recognition, and interpretation of convergent evolution and two new measures for quantifying and assessing the significance of convergence. Evolution 69(8): 2140-2153. Revell, L. J. (2012) phytools: An R package for phylogenetic comparative biology (and other things). Methods Ecol. Evol., 3, 217-223. Felsenstein, J. 1985. Phylogenies and the comparative method. American Naturalist, 125, 1-15.

Examples

## Not run: 
library(phytools)
library(geiger)

# create time calibrated tree
mytree<-rtree(100)
mycalibration <- makeChronosCalib(mytree, node="root", age.max=50)
phy <- chronos(mytree, lambda = 1, model = "correlated", calibration = mycalibration, 
control = chronos.control() )
class(phy)<-"phylo"

# create three normally distributed phenotypic traits
traits <- cbind(rnorm(Ntip(phy)),rnorm(Ntip(phy)),rnorm(Ntip(phy)))
rownames(traits) <- phy$tip.label

#	select two random tips, excluding sister taxa
pairs <- apply(combn(phy$tip.label,2),2,function(x) nodepath(phy,which(phy$tip.label == x[1]),
which(phy$tip.label == x[2])))
nosis <- combn(phy$tip.label,2)[,unlist(lapply(pairs, function(x) length(x) > 3))]
focaltaxa <- nosis[,sample(1:ncol(nosis),1)]

pwCheck(phy,focaltaxa)

## End(Not run)

Sample data for use in convevol examples and tutorial

Description

It's a data matrix with 6 variables measured across 100 tips of a phylogeny ("phy" - also included)

Format

I'll need to look into this