transtree: Create a consensus transmission tree.
In donkeyshot/phybreak: Analysis of Outbreaks with Sequence Data

Description Usage Arguments Details Value Author(s) References Examples

Various methods to create summary transmission trees from a phybreak-object containing posterior samples.

transtree(x, method = c("count", "edmonds", "mpc", "mtcc"),
  samplesize = Inf, infector.name = TRUE, support = c("proportion",
  "count"), infection.times = c("all", "infector", "infector.sd"),
  time.quantiles = c(0.025, 0.5, 0.975), phylo.class = FALSE)

`x`	An object of class `phybreak`.
`method`	The method used to create the tree (see details).
`samplesize`	The number of posterior samples that is used, taken from the tail.
`infector.name`	Whether to return the infector names, or the position in the vector of hosts.
`support`	Whether to return the support (= posterior probability) for each infector as a `"proportion"` or as a `"count"` of posterior trees in which that transmission link or transmission cluster is present.
`infection.times`	Whether to base the summary infection times on `"all"` samples, or only on samples in which the `"infector"` was the same as in the consensus tree. A third option is `"infector.sd"`, in which case only posterior trees with the same infector or transmission cluster as in the consensus tree were used to calculate a mean and standard deviation. In that case and if `method = "mpc"` or `method = "mtcc"`, also the infection times in the first sampled tree with consensus tree topology are given.
`time.quantiles`	Used only if `infection.times = "all"` or `"infector"`.
`phylo.class`	Whether to return an object of class `"phylo"`, in which case a single tree (`"mpc"` or `"mtcc"`) from the posterior is returned (not with summary infection times). This option is used by `plotPhylo`.

Four methods are supported for transmission tree reconstruction (who infected whom).

"count" gives the most frequent infector from the posterior samples. Note that this may result in an improper tree (multiple roots and/or cycles). Support is measured by the frequency of the infector in the posterior distribution.
"edmonds" starts from the most frequent infector (method "count"), multiple roots and cycles are removed by selecting one by one the next most frequent option that minimizes the loss in support (Edmonds' algorithm). Support is measured by the frequency of the infector in the posterior distribution.
"mpc" gives the maximum parent credibility tree as described in Hall et al (2015). This is the tree in the set of posterior samples that has maximum support = product of frequencies among all posterior samples. Support is measured by the frequency of the infector in the posterior distribution.
"mtcc" gives the maximum transmission cluster credibility tree. This is equivalent to the maximum clade credibility (mcc) phylogenetic tree, with clusters defined as host + all progeny. Support is measured by the frequency of the cluster in the posterior distribution.

If phylo.class = FALSE, a data.frame with per item (=host) its infector and support per infector (or cluster), and summary infection times. If phylo.class = TRUE, a class "phylo" object, a single tree ("mpc" or "mtcc") from the posterior is returned (not with summary infection times).

Don Klinkenberg don@xs4all.nl

Klinkenberg et al. (2017) Simultaneous inference of phylogenetic and transmission trees in infectious disease outbreaks. PLoS Comput Biol, 13(5): e1005495.

#First build a phybreak-object containing samples.
simulation <- sim_phybreak(obsize = 5)
MCMCstate <- phybreak(dataset = simulation)
MCMCstate <- burnin_phybreak(MCMCstate, ncycles = 20)
MCMCstate <- sample_phybreak(MCMCstate, nsample = 50, thin = 2)

transtree(MCMCstate, method = "edmonds")
transtree(MCMCstate, method = "mpc", infection.times = "infector.sd")
plot(MCMCstate, plot.which = "mpc")