Phylogenetic tree exploration

Source: R/treespace.R

Compares phylogenetic trees using a choice of metrics / measures, and maps their pairwise distances into a small number of dimensions for easy visualisation and identification of clusters.

treespace(
  x,
  method = "treeVec",
  nf = NULL,
  lambda = 0,
  return.tree.vectors = FALSE,
  processors = 1,
  ...
)

Arguments

x

an object of the class multiPhylo

method

the method for summarising the tree as a vector. Choose from:

  • treeVec (default) the Kendall Colijn metric vector (for rooted trees)

  • BHV the Billera, Holmes Vogtmann metric using dist.multiPhylo from package distory (for rooted trees)

  • KF the Kuhner Felsenstein metric (branch score distance) using KF.dist from package phangorn (considers the trees unrooted)

  • RF the Robinson Foulds metric using RF.dist from package phangorn (considers the trees unrooted)

  • wRF the weighted Robinson Foulds metric using wRF.dist from package phangorn (considers the trees unrooted)

  • nNodes the Steel & Penny tip-tip path difference metric, (topological, ignoring branch lengths), using path.dist from package phangorn (considers the trees unrooted)

  • patristic the Steel & Penny tip-tip path difference metric, using branch lengths, calling path.dist from package phangorn (considers the trees unrooted)

  • Abouheif: performs Abouheif's test, inherited from distTips in adephylo. See Pavoine et al. (2008) and adephylo.

  • sumDD: sum of direct descendants of all nodes on the path, related to Abouheif's test, inherited from distTips in adephylo.

nf

the number of principal components to retain

lambda

a number in [0,1] which specifies the extent to which topology (default, with lambda=0) or branch lengths (lambda=1) are emphasised in the Kendall Colijn metric.

return.tree.vectors

if using the Kendall Colijn metric, this option will return the tree vectors as part of the output. Note that this can use a lot of memory so defaults to FALSE.

processors

value (default 1) to be passed to mcmapply specifying the number of cores to use. Must be 1 on Windows (see mcmapply for more details).

...

further arguments to be passed to method.

Author

Thibaut Jombart thibautjombart@gmail.com

Michelle Kendall michelle.louise.kendall@gmail.com

Examples


## generate list of trees
x <- rmtree(10, 20)
names(x) <- paste("tree", 1:10, sep = "")

## use treespace
res <- treespace(x, nf=3)
table.paint(as.matrix(res$D))

scatter(res$pco)
#> Error in s.label(dfxy = res$pco$li, xax = 1, yax = 2, plot = FALSE, storeData = TRUE,     pos = -3): non convenient selection for dfxy (can not be converted to dataframe)

data(woodmiceTrees)
woodmiceDists <- treespace(woodmiceTrees,nf=3)
plot(woodmiceDists$pco$li[,1],woodmiceDists$pco$li[,2])

woodmicedf <- woodmiceDists$pco$li
if(require(ggplot2)){
woodmiceplot <- ggplot(woodmicedf, aes(x=A1, y=A2)) # create plot
woodmiceplot + geom_density2d(colour="gray80") + # contour lines
geom_point(size=6, shape=1, colour="gray50") + # grey edges
geom_point(size=6, alpha=0.2, colour="navy") + # transparent blue points
xlab("") + ylab("") + theme_bw(base_family="") # remove axis labels and grey background
}
#> Loading required package: ggplot2


if (FALSE) {
if(require(rgl)){
plot3d(woodmicedf[,1], woodmicedf[,2], woodmicedf[,3], type="s", size=1.5,
col="navy", alpha=0.5, xlab="", ylab="", zlab="")
}
}