knitr::opts_chunk$set(fig.width=6, fig.height=4)
If you want to reproduce exactly the same results as the ones shown in this tutorial, you need to set the seed of your random number generator to zero:
library(TransPhylo) set.seed(0)
A pathogen has an effective within-host population size of $N_e=100$ and a generation time $g=1$ day, so that $N_e g=100/365$ year. The offspring distribution is negative binomial with mean equal to the basic reproduction number $R=5$. Both the generation time and the sampling time are Gamma distributed with parameters (10,0.1) which has a mean of 1 year. The density of sampling is $\pi=0.25$. The following commands specify these parameters:
neg=100/365 off.r=5 w.shape=10 w.scale=0.1 pi=0.25
We simulate an outbreak that starts in 2005 and which and is observed up to 2008:
simu <- simulateOutbreak(neg=neg,pi=pi,off.r=off.r,w.shape=w.shape, w.scale=w.scale,dateStartOutbreak=2005,dateT=2008)
This simulation contains both the transmission tree between infected hosts and the within-host phylogenetic tree of each host. This can be visualised as a colored phlogenetic tree, where each host is represented by a unique color:
plot(simu)
The transmission tree can be extracted and plotted separately from the phylogeny:
ttree<-extractTTree(simu) plot(ttree)
A more detailed plot can be displayed as follows:
plot(ttree,type='detailed',w.shape,w.scale)
The phylogenetic tree can be extracted and plotted separately from the transmission tree:
ptree<-extractPTree(simu) plot(ptree)
The extracted phylogenetic tree can also be converted into a phylo object from the ape package:
library(ape) p<-phyloFromPTree(ptree) plot(p) axisPhylo(backward = F)
You can save this tree into a Newick file for further analysis. This is the tree that is used as the starting poit of the tutorial on inference of a transmission tree from a dated phylogeny.
write.tree(p,'tree.nwk')
The content of this Newick file is:
write.tree(p,'')
This phylogeny is scaled in years, but time is measured only relatively to the date of the last sample which is at 0 on the x-axis of the figure above. To use this tree again we also need to know exactly when was the last sample taken:
dateLastSample(simu)
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