library(nLTT) #nolint require(ggplot2) require(knitr) # temporary fix to keep R-devel happy. # should be updated upon release of version 3.6 suppressWarnings(RNGversion("3.5.0"))
Calculating the average nLTT plot of multiple phylogenies is not a trivial tasks.
The function get_nltt_values
collects the nLTT values of a collection of
phylogenies as tidy data.
This allows for a good interplay with ggplot2.
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) phylogenies <- c(phylogeny1, phylogeny2)
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))
As a collection of timepoints:
t <- nLTT::get_phylogeny_nltt_matrix(phylogeny1) knitr::kable(t)
Plotting those timepoints:
df <- as.data.frame(nLTT::get_phylogeny_nltt_matrix(phylogeny1)) ggplot2::qplot( time, N, data = df, geom = "step", ylim = c(0, 1), direction = "vh", main = "NLTT plot of phylogeny 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))
As a collection of timepoints:
t <- nLTT::get_phylogeny_nltt_matrix(phylogeny2) knitr::kable(t)
Plotting those timepoints:
df <- as.data.frame(nLTT::get_phylogeny_nltt_matrix(phylogeny2)) ggplot2::qplot( time, N, data = df, geom = "step", ylim = c(0, 1), direction = "vh", main = "NLTT plot of phylogeny 2" )
The average nLTT plot should be somewhere in the middle.
It is constructed from stretched nLTT matrices.
Here is the nLTT matrix of the first phylogeny:
t <- nLTT::stretch_nltt_matrix( nLTT::get_phylogeny_nltt_matrix(phylogeny1), dt = 0.20, step_type = "upper" ) knitr::kable(t)
Here is the nLTT matrix of the second phylogeny:
t <- nLTT::stretch_nltt_matrix( nLTT::get_phylogeny_nltt_matrix(phylogeny2), dt = 0.20, step_type = "upper" ) knitr::kable(t)
Here is the average nLTT matrix of both phylogenies:
t <- nLTT::get_average_nltt_matrix(phylogenies, dt = 0.20) knitr::kable(t)
Observe how the numbers get averaged.
The same, now shown as a plot:
nLTT::nltts_plot(phylogenies, dt = 0.20, plot_nltts = TRUE)
Here a demo how the new function works:
t <- nLTT::get_nltt_values(c(phylogeny1, phylogeny2), dt = 0.2) knitr::kable(t)
Plotting options, first create a data frame:
df <- nLTT::get_nltt_values(c(phylogeny1, phylogeny2), dt = 0.01)
Here we see an averaged nLTT plot, where the original nLTT values are still visible:
ggplot2::qplot( t, nltt, data = df, geom = "point", ylim = c(0, 1), main = "Average nLTT plot of phylogenies", color = id, size = I(0.1) ) + ggplot2::stat_summary( fun.data = "mean_cl_boot", color = "red", geom = "smooth" )
Here we see an averaged nLTT plot, with the original nLTT values omitted:
ggplot2::qplot(t, nltt, data = df, geom = "blank", ylim = c(0, 1), main = "Average nLTT plot of phylogenies" ) + ggplot2::stat_summary( fun.data = "mean_cl_boot", color = "red", geom = "smooth" )
Create two harder 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) phylogenies <- c(phylogeny1, phylogeny2)
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))
As a collection of timepoints:
t <- nLTT::get_phylogeny_nltt_matrix(phylogeny2) knitr::kable(t)
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))
As a collection of timepoints:
t <- nLTT::get_phylogeny_nltt_matrix(phylogeny2) knitr::kable(t)
The average nLTT plot should be somewhere in the middle.
It is constructed from stretched nLTT matrices.
Here is the nLTT matrix of the first phylogeny:
t <- nLTT::stretch_nltt_matrix( nLTT::get_phylogeny_nltt_matrix(phylogeny1), dt = 0.20, step_type = "upper" ) knitr::kable(t)
Here is the nLTT matrix of the second phylogeny:
t <- nLTT::stretch_nltt_matrix( nLTT::get_phylogeny_nltt_matrix(phylogeny2), dt = 0.20, step_type = "upper" ) knitr::kable(t)
Here is the average nLTT matrix of both phylogenies:
t <- nLTT::get_average_nltt_matrix(phylogenies, dt = 0.20) knitr::kable(t)
Observe how the numbers get averaged.
Here a demo how the new function works:
t <- nLTT::get_nltt_values(c(phylogeny1, phylogeny2), dt = 0.2) knitr::kable(t)
Plotting options, first create a data frame:
df <- nLTT::get_nltt_values(c(phylogeny1, phylogeny2), dt = 0.01)
Here we see an averaged nLTT plot, where the original nLTT values are still visible:
ggplot2::qplot( t, nltt, data = df, geom = "point", ylim = c(0, 1), main = "Average nLTT plot of phylogenies", color = id, size = I(0.1) ) + ggplot2::stat_summary( fun.data = "mean_cl_boot", color = "red", geom = "smooth" )
Here we see an averaged nLTT plot, with the original nLTT values omitted:
ggplot2::qplot(t, nltt, data = df, geom = "blank", ylim = c(0, 1), main = "Average nLTT plot of phylogenies" ) + ggplot2::stat_summary( fun.data = "mean_cl_boot", color = "red", geom = "smooth" )
Create three random trees:
set.seed(42) phylogeny1 <- ape::rcoal(10) phylogeny2 <- ape::rcoal(20) phylogeny3 <- ape::rcoal(30) phylogeny4 <- ape::rcoal(40) phylogeny5 <- ape::rcoal(50) phylogeny6 <- ape::rcoal(60) phylogeny7 <- ape::rcoal(70) phylogenies <- c( phylogeny1, phylogeny2, phylogeny3, phylogeny4, phylogeny5, phylogeny6, phylogeny7 )
Here a demo how the new function works:
t <- nLTT::get_nltt_values(phylogenies, dt = 0.2) knitr::kable(t)
Here we see an averaged nLTT plot, where the original nLTT values are still visible:
ggplot2::qplot(t, nltt, data = df, geom = "point", ylim = c(0, 1), main = "Average nLTT plot of phylogenies", color = id, size = I(0.1) ) + ggplot2::stat_summary( fun.data = "mean_cl_boot", color = "red", geom = "smooth" )
Here we see an averaged nLTT plot, with the original nLTT values omitted:
ggplot2::qplot(t, nltt, data = df, geom = "blank", ylim = c(0, 1), main = "Average nLTT plot of phylogenies" ) + ggplot2::stat_summary( fun.data = "mean_cl_boot", color = "red", geom = "smooth" )
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.