overfitST function

Testing search.trend overfit

Testing the robustness of search.trend

(Castiglione et al. 2019a ) results to sampling effects and phylogenetic uncertainty.

overfitST(RR,y,oveRR,x1=NULL,x1.residuals=FALSE,node=NULL,cov=NULL,clus=0.5)

Arguments

• RR: an object produced by RRphylo.
• y: a named vector of phenotypes.
• oveRR: an object produced by applying overfitRR on the object provided to the function as RR.
• x1, node, cov: arguments as passed to overfitRR.
• x1.residuals: as passed to search.trend. Default is FALSE.
• clus: the proportion of clusters to be used in parallel computing. To run the single-threaded version of overfitST set clus = 0.

Returns

The function returns a 'RRphyloList' object containing:

$ST.list a 'RRphyloList' including the results of each search.trend performed within overfitST.

$trend.results a list including the percentage of simulations showing significant p-values for phenotypes versus age and absolute rates versus age regressions for the entire tree separated by slope sign ($tree). If one or more nodes are specified within trend.args, the list also includes the same results at nodes ($node) and the results for comparison between nodes ($comparison). For each node the proportion of tested trees (i.e. where the clade identity was preserved; always 1 if no phylo.list is supplied) is also indicated.

The output always has an attribute "Call" which returns an unevaluated call to the function.

Examples

## Not run:

cc<- 2/parallel::detectCores()
library(ape)

## Case 1
# load the RRphylo example dataset including Ornithodirans tree and data
data("DataOrnithodirans")
DataOrnithodirans$treedino->treedino
DataOrnithodirans$massdino->massdino
DataOrnithodirans$statedino->statedino

# extract Pterosaurs tree and data
extract.clade(treedino,746)->treeptero
massdino[match(treeptero$tip.label,names(massdino))]->massptero
massptero[match(treeptero$tip.label,names(massptero))]->massptero

# perform RRphylo and search.trend on body mass data
RRphylo(tree=treeptero,y=log(massptero),clus=cc)->RRptero
search.trend(RR=RRptero, y=log(massptero),node=143,clus=cc)->st2

## overfitST routine
# generate a list of subsampled and swapped phylogenies setting as node
# the clade under testing
treeptero.list<-resampleTree(RRptero$tree,s = 0.25,node=143,
                             swap.si = 0.1,swap.si2 = 0.1,nsim=10)

# test the robustness of search.trend
ofRRptero<-overfitRR(RR = RRptero,y=log(massptero),phylo.list=treeptero.list,clus=cc)
ofSTptero<-overfitST(RR=RRptero,y=log(massptero),oveRR=ofRRptero,node=143,clus=cc)

## Case 2
# load the RRphylo example dataset including Cetaceans tree and data
data("DataCetaceans")
DataCetaceans$treecet->treecet
DataCetaceans$masscet->masscet
DataCetaceans$brainmasscet->brainmasscet

# cross-reference the phylogenetic tree and body and brain mass data. Remove from
# both the tree and vector of body sizes the species whose brain size is missing
drop.tip(treecet,treecet$tip.label[-match(names(brainmasscet),
                                               treecet$tip.label)])->treecet.multi
masscet[match(treecet.multi$tip.label,names(masscet))]->masscet.multi

# peform RRphylo on the variable (body mass) to be used as additional predictor
RRphylo(tree=treecet.multi,y=masscet.multi,clus=cc)->RRmass.multi
RRmass.multi$aces[,1]->acemass.multi

# create the predictor vector: retrieve the ancestral character estimates
# of body size at internal nodes from the RR object ($aces) and collate them
# to the vector of species' body sizes to create
c(acemass.multi,masscet.multi)->x1.mass

# peform RRphylo and search.trend on brain mass by using body mass as additional predictor
RRphylo(tree=treecet.multi,y=brainmasscet,x1=x1.mass,clus=cc)->RRmulti
search.trend(RR=RRmulti, y=brainmasscet,x1=x1.mass,clus=cc)->STcet

## overfitST routine
# generate a list of subsampled and swapped phylogenies to test
treecet.list<-resampleTree(RRmulti$tree,s = 0.25,swap.si=0.1,swap.si2=0.1,nsim=10)

# test the robustness of search.trend with and without x1.residuals
ofRRcet<-overfitRR(RR = RRmulti,y=brainmasscet,phylo.list=treecet.list,clus=cc,x1 =x1.mass)
ofSTcet1<-overfitST(RR=RRmulti,y=brainmasscet,oveRR=ofRRcet,x1 =x1.mass,clus=cc)
ofSTcet2<-overfitST(RR=RRmulti,y=brainmasscet,oveRR=ofRRcet,x1 =x1.mass,x1.residuals = TRUE,clus=cc)
## End(Not run)

References

Castiglione, S., Tesone, G., Piccolo, M., Melchionna, M., Mondanaro, A., Serio, C., Di Febbraro, M., & Raia, P. (2018). A new method for testing evolutionary rate variation and shifts in phenotypic evolution. Methods in Ecology and Evolution, 9: 974-983.doi:10.1111/2041-210X.12954

Castiglione, S., Serio, C., Mondanaro, A., Di Febbraro, M., Profico, A., Girardi, G., & Raia, P. (2019a) Simultaneous detection of macroevolutionary patterns in phenotypic means and rate of change with and within phylogenetic trees including extinct species. PLoS ONE, 14: e0210101. https://doi.org/10.1371/journal.pone.0210101

See Also

c("list("overfitST")", " vignette") ; c("list("search.trend")", " vignette") ; c("list("Alternative-trees")", " vignette")

Author(s)

Silvia Castiglione, Carmela Serio, Giorgia Girardi, Pasquale Raia