The nLTT
package facilitates plotting one or more nLTT plots,
using nllt_plot
and nllt_lines
.
These functions, however, do not show the average nLTT plot.
The function nltts_plot
plots multiple nLTT plots and shows
the average nLTT. This helps in getting a quick visualization
of your data.
For working with the raw values, get_nltt_values
is
preferably used.
Create two easy trees:
newick1 <- "((A:1,B:1):2,C:3);" newick2 <- "((A:2,B:2):1,C:3);" phylogeny1 <- ape::read.tree(text = newick1) phylogeny2 <- ape::read.tree(text = newick2)
There are very similar. phylogeny1
has short tips:
ape::plot.phylo(phylogeny1) ape::add.scale.bar() #nolint
This can be observed in the nLTT plot:
nLTT::nltt_plot(phylogeny1, ylim = c(0, 1))
phylogeny2
has longer tips:
ape::plot.phylo(phylogeny2) ape::add.scale.bar() #nolint
Also this can be observed in the nLTT plot:
nLTT::nltt_plot(phylogeny2, ylim = c(0, 1))
The average nLTT plot should be somewhere in the middle.
The same, now shown as a plot:
nLTT::nltts_plot(c(phylogeny1, phylogeny2), dt = 0.20, plot_nltts = TRUE)
Create two easy trees:
newick1 <- "((A:1,B:1):1,(C:1,D:1):1);" newick2 <- paste0("((((XD:1,ZD:1):1,CE:2):1,(FE:2,EE:2):1):4,((AE:1,BE:1):1,", "(WD:1,YD:1):1):5);" ) phylogeny1 <- ape::read.tree(text = newick1) phylogeny2 <- ape::read.tree(text = newick2)
There are different. phylogeny1
is relatively simple, with two branching events happening at the same time:
ape::plot.phylo(phylogeny1) ape::add.scale.bar() #nolint
This can be observed in the nLTT plot:
nLTT::nltt_plot(phylogeny1, ylim = c(0, 1))
phylogeny2
is more elaborate:
ape::plot.phylo(phylogeny2) ape::add.scale.bar() #nolint
Also this can be observed in the nLTT plot:
nLTT::nltt_plot(phylogeny2, ylim = c(0, 1))
The same, now shown as a plot:
nLTT::nltts_plot( c(phylogeny1, phylogeny2), dt = 0.20, plot_nltts = TRUE )
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