compare.evol.rates(A, phy, gp, iter = 999, print.progress = TRUE)
read.tree
in library apegpagen
]. The approach is based on the distances
between species in morphospace after phylogenetic transformation (Adams 2014). From the data the rate of shape evolution
for each group is calculated, and a ratio of rates is obtained. If three or more groups of species are used, the ratio of
the maximum to minimum rate is used as a test statistic (see Adams 2014). Significance testing
is accomplished by phylogenetic simulation in which tips data are obtained under Brownian motion using a common
evolutionary rate pattern for all species on the phylogeny. Specifically, the common evolutionary rate matrix for all
species is used, with the multi-dimensional rate used along the diagonal elements (see Denton and Adams 2015). This procedure is
more general than the original simulation procedure, and retains the desirable statistical properties of earlier methods,
and under a wider array of data types.
If three or more groups of species are used, pairwise p-values are also calculated. The function can be used to obtain a
rate for the whole dataset of species by using a dummy group factor assigning all species to one group.
This function can be used with univariate data (i.e. centroid size) if imported as matrix with rownames
giving the taxa names.
The generic functions, print
, summary
, and plot
all work with compare.evol.rates
.
The generic function, plot
, produces a histogram of random rate-ratios associated with
the resampling procedure.Notes for geomorph 3.0 Compared to older versions of geomorph, the order of input variables has changed, so that it is consistent with other functions in the program. Additionally, for 3 or more groups, the pairwise p-values are found in the output object.
Denton, J.S.S., and D.C. Adams. 2015. A new phylogenetic test for comparing multiple high-dimensional evolutionary rates suggests interplay of evolutionary rates and modularity in lanternfishes (Myctophiformes; Myctophidae). Evolution. 69:2425-2440.
data(plethspecies)
Y.gpa<-gpagen(plethspecies$land) #GPA-alignment
gp.end<-factor(c(0,0,1,0,0,1,1,0,0)) #endangered species vs. rest
names(gp.end)<-plethspecies$phy$tip
ER<-compare.evol.rates(A=Y.gpa$coords, phy=plethspecies$phy,gp=gp.end,iter=999)
summary(ER)
plot(ER)
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