Version: | 1.4.5 |
Date: | 2021-04-20 |
Title: | Inference of Transmission Tree from a Dated Phylogeny |
Maintainer: | Xavier Didelot <xavier.didelot@gmail.com> |
Description: | Inference of transmission tree from a dated phylogeny. Includes methods to simulate and analyse outbreaks. The methodology is described in Didelot et al. (2014) <doi:10.1093/molbev/msu121>, Didelot et al. (2017) <doi:10.1093/molbev/msw275>. |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
Depends: | R (≥ 3.0.0) |
Imports: | Rcpp (≥ 0.12.8), stats, graphics, ape |
Suggests: | knitr, testthat, purrr, coda, grDevices, lattice, rmarkdown |
LinkingTo: | Rcpp |
Encoding: | UTF-8 |
RoxygenNote: | 7.1.1 |
SystemRequirements: | C++11 |
VignetteBuilder: | knitr |
NeedsCompilation: | yes |
Packaged: | 2021-04-20 12:19:58 UTC; Xavier |
Author: | Xavier Didelot |
Repository: | CRAN |
Date/Publication: | 2021-04-20 13:30:03 UTC |
Inference of Transmission Tree from a Dated Phylogeny
Description
Inference of transmission tree from a dated phylogeny. Includes methods to simulate and analyse outbreaks.
Author(s)
Xavier Didelot xavier.didelot@gmail.com
References
Didelot et al. (2014) <doi:10.1093/molbev/msu121> Didelot et al. (2017) <doi:10.1093/molbev/msw275>.
See Also
https://github.com/xavierdidelot/TransPhylo
Convert to coda mcmc format
Description
Convert to coda mcmc format
Usage
as.mcmc.resTransPhylo(x, burnin = 0.5)
Arguments
x |
Output from inferTTree |
burnin |
Proportion of the MCMC output to be discarded as burnin |
Value
mcmc object from coda package
Build a matrix indicating for each pairs of individuals how many intermediates there are in the transmission chain
Description
Build a matrix indicating for each pairs of individuals how many intermediates there are in the transmission chain
Usage
computeMatTDist(record, burnin = 0.5)
Arguments
record |
Output from inferTTree function |
burnin |
Proportion of the MCMC output to be discarded as burnin |
Value
Matrix of intermediates in transmission chains between pairs of hosts
Build a matrix of probability of who infected whom from a MCMC output
Description
Build a matrix of probability of who infected whom from a MCMC output
Usage
computeMatWIW(record, burnin = 0.5)
Arguments
record |
Output from inferTTree function |
burnin |
Proportion of the MCMC output to be discarded as burnin |
Value
Matrix of probability of who infected whom
Build a consensus transmission tree from a MCMC output
Description
Build a consensus transmission tree from a MCMC output
Usage
consTTree(record, burnin = 0.5, minimum = 0.2, debug = F)
Arguments
record |
Output from inferTTree function |
burnin |
Proportion of the MCMC output to be discarded as burnin |
minimum |
Minimum probability for inclusion of a partition in the consensus |
debug |
Used for debugging |
Value
The consensus transmission tree
Convert to coda mcmc format
Description
Convert to coda mcmc format
Usage
convertToCoda(record, burnin = 0.5)
Arguments
record |
Output from inferTTree function |
burnin |
Proportion of the MCMC output to be discarded as burnin |
Value
Object of class mcmc from coda package
Return the date of last sample from a ttree or ctree or ptree
Description
Return the date of last sample from a ttree or ctree or ptree
Usage
dateLastSample(x)
Arguments
x |
A transmission tree or colored tree or phylogenetic tree |
Value
date of the last sample
Return the combined tree corresponding to a given iteration of the TransPhylo results
Description
Return the combined tree corresponding to a given iteration of the TransPhylo results
Usage
extractCTree(res, iteration)
Arguments
res |
Output from inferTTree command |
iteration |
Number of the iteration to be extracted |
Value
The colored tree at the specified iteeatino
Extracts phylogenetic tree from a combined phylogenetic/transmission tree
Description
Extracts phylogenetic tree from a combined phylogenetic/transmission tree
Usage
extractPTree(ctree)
Arguments
ctree |
Combined tree |
Value
phylogenetic tree
Examples
extractPTree(simulateOutbreak())
Extracts transmission tree from a combined phylogenetic/transmission tree
Description
Extracts transmission tree from a combined phylogenetic/transmission tree
Usage
extractTTree(ctree)
Arguments
ctree |
Combined tree |
Value
transmission tree
Examples
extractTTree(simulateOutbreak())
Extract and return realised generation time distribution
Description
Extract and return realised generation time distribution
Usage
getGenerationTimeDist(
record,
burnin = 0.5,
maxi = 2,
numBins = 20,
show.plot = F
)
Arguments
record |
MCMC output produced by inferTTree |
burnin |
Proportion of the MCMC output to be discarded as burnin |
maxi |
Maximum generation time to consider |
numBins |
Number of time bins to compute and display distribution |
show.plot |
Show a barplot of the distribution |
Value
Vector of times between becoming infected and infecting others (generation times) in the posterior
Returns and/or plot numbers of sampled and unsampled cases over time
Description
Returns and/or plot numbers of sampled and unsampled cases over time
Usage
getIncidentCases(
record,
burnin = 0.5,
numBins = 10,
dateT = NA,
show.plot = FALSE
)
Arguments
record |
Output from inferTTree function |
burnin |
Proportion of the MCMC output to be discarded as burnin |
numBins |
Number of time bins to compute and display incident cases |
dateT |
Date when process stops (this can be Inf for fully resolved outbreaks) |
show.plot |
Show a plot of incident cases over time with stacked bars |
Value
List with four entries. Time is a vector of the time points. allCases is the average number of cases at each time in the posterior. sampledCases: average number of sampled cases. unsampCases: average number of unsampled cases.
Extract and return distribution of infection time of given sampled case(s)
Description
Extract and return distribution of infection time of given sampled case(s)
Usage
getInfectionTimeDist(record, burnin = 0.5, k, numBins = 10, show.plot = F)
Arguments
record |
MCMC output produced by inferTTree |
burnin |
Proportion of the MCMC output to be discarded as burnin |
k |
Case(s) whose posterior infection times are to be extracted. Either a string matching one of the case names in the data, or a vector of such strings |
numBins |
Number of bins to use for plot |
show.plot |
Show a barplot of the distribution |
Value
Posterior infection times for the case(s) in k. If length(k)==1 then a vector is returned, otherwise a matrix
Extract and return offspring distribution of given sampled case(s)
Description
Extract and return offspring distribution of given sampled case(s)
Usage
getOffspringDist(record, burnin = 0.5, k, show.plot = F)
Arguments
record |
MCMC output produced by inferTTree |
burnin |
Proportion of the MCMC output to be discarded as burnin |
k |
Case(s) whose offspring distribution are to be extracted. Either a string matching one of the case names in the data, or a vector of such strings |
show.plot |
Show a barplot of the distribution |
Value
Posterior offspring distribution for the case(s) in k. If length(k)==1 then a vector is returned, otherwise a matrix
Extract and return realised sampling time distribution
Description
Extract and return realised sampling time distribution
Usage
getSamplingTimeDist(
record,
burnin = 0.5,
maxi = 2,
numBins = 20,
show.plot = F
)
Arguments
record |
MCMC output produced by inferTTree |
burnin |
Proportion of the MCMC output to be discarded as burnin |
maxi |
Maximum generation time to consider |
numBins |
Number of time bins to compute and display distribution |
show.plot |
Show a barplot of the distribution |
Value
Vector of times between becoming infected and becoming sampled in the posterior
Infer transmission tree given a phylogenetic tree
Description
Infer transmission tree given a phylogenetic tree
Usage
inferTTree(
ptree,
w.shape = 2,
w.scale = 1,
ws.shape = NA,
ws.scale = NA,
w.mean = NA,
w.std = NA,
ws.mean = NA,
ws.std = NA,
mcmcIterations = 1000,
thinning = 1,
startNeg = 100/365,
startOff.r = 1,
startOff.p = 0.5,
startPi = 0.5,
updateNeg = TRUE,
updateOff.r = TRUE,
updateOff.p = FALSE,
updatePi = TRUE,
startCTree = NA,
updateTTree = TRUE,
optiStart = 2,
dateT = Inf,
verbose = F
)
Arguments
ptree |
Phylogenetic tree |
w.shape |
Shape parameter of the Gamma distribution representing the generation time |
w.scale |
Scale parameter of the Gamma distribution representing the generation time |
ws.shape |
Shape parameter of the Gamma distribution representing the sampling time |
ws.scale |
Scale parameter of the Gamma distribution representing the sampling time |
w.mean |
Mean of the Gamma distribution representing the generation time |
w.std |
Std of the Gamma distribution representing the generation time |
ws.mean |
Mean of the Gamma distribution representing the sampling time |
ws.std |
Std of the Gamma distribution representing the sampling time |
mcmcIterations |
Number of MCMC iterations to run the algorithm for |
thinning |
MCMC thinning interval between two sampled iterations |
startNeg |
Starting value of within-host coalescent parameter Ne*g |
startOff.r |
Starting value of parameter off.r |
startOff.p |
Starting value of parameter off.p |
startPi |
Starting value of sampling proportion pi |
updateNeg |
Whether of not to update the parameter Ne*g |
updateOff.r |
Whether or not to update the parameter off.r |
updateOff.p |
Whether or not to update the parameter off.p |
updatePi |
Whether or not to update the parameter pi |
startCTree |
Optional combined tree to start from |
updateTTree |
Whether or not to update the transmission tree |
optiStart |
Type of optimisation to apply to MCMC start point (0=none, 1=slow, 2=fast) |
dateT |
Date when process stops (this can be Inf for fully simulated outbreaks) |
verbose |
Whether or not to use verbose mode (default is false) |
Value
posterior sample set of transmission trees
Examples
inferTTree(ptreeFromPhylo(ape::rtree(5),2020),mcmcIterations=100)
Simultaneously infer transmission trees given phylogenetic trees User can specify any subset of parameters that will be shared by providing a character vector of parameter names to the argument "share".
Description
Simultaneously infer transmission trees given phylogenetic trees User can specify any subset of parameters that will be shared by providing a character vector of parameter names to the argument "share".
Usage
infer_multittree_share_param(
ptree_lst,
w.shape = 2,
w.scale = 1,
ws.shape = w.shape,
ws.scale = w.scale,
mcmcIterations = 1000,
thinning = 1,
startNeg = 100/365,
startOff.r = 1,
startOff.p = 0.5,
startPi = 0.5,
prior_pi_a = 1,
prior_pi_b = 1,
updateNeg = TRUE,
updateOff.r = TRUE,
updateOff.p = FALSE,
updatePi = TRUE,
share = NULL,
startCTree_lst = rep(NA, length(ptree_lst)),
updateTTree = TRUE,
optiStart = 2,
dateT = Inf,
verbose = F
)
Arguments
ptree_lst |
List of phylogenetic tree |
w.shape |
Shape parameter of the Gamma probability density function representing the generation time |
w.scale |
Scale parameter of the Gamma probability density function representing the generation time |
ws.shape |
Shape parameter of the Gamma probability density function representing the sampling time |
ws.scale |
Scale parameter of the Gamma probability density function representing the sampling time |
mcmcIterations |
Number of MCMC iterations to run the algorithm for |
thinning |
MCMC thinning interval between two sampled iterations |
startNeg |
Starting value of within-host coalescent parameter Ne*g |
startOff.r |
Starting value of parameter off.r |
startOff.p |
Starting value of parameter off.p |
startPi |
Starting value of sampling proportion pi |
prior_pi_a |
First shape parameter of Beta prior for pi |
prior_pi_b |
Second shape parameter of Beta prior for pi |
updateNeg |
Whether of not to update the parameter Ne*g |
updateOff.r |
Whether or not to update the parameter off.r |
updateOff.p |
Whether or not to update the parameter off.p |
updatePi |
Whether or not to update the parameter pi |
share |
Character vector of parameters to be shared. For example, share = c("off.r", "off.p") would share the offspring distribution. Allowed parameter names are "neg", "off.r", "off.p" and "pi". |
startCTree_lst |
Optional combined list of trees to start from |
updateTTree |
Whether or not to update the transmission tree |
optiStart |
Type of optimisation to apply to MCMC start point (0=none, 1=slow, 2=fast) |
dateT |
Date when process stops (this can be Inf for fully simulated outbreaks) |
verbose |
Whether or not to use verbose mode (default is false) |
Value
list the same size as input, each element contains posterior transmission trees inferred from corresponding phylogenetic tree
Author(s)
Yuanwei Xu
Create a transmission tree compatible with the provided phylogenetic tree
Description
Create a transmission tree compatible with the provided phylogenetic tree
Usage
makeCTreeFromPTree(
ptree,
off.r = NA,
off.p = NA,
neg = NA,
pi = NA,
w.shape = NA,
w.scale = NA,
ws.shape = NA,
ws.scale = NA,
T = NA,
optiStart = 0
)
Arguments
ptree |
Phylogenetic tree |
off.r |
First parameter of the negative binomial distribution for offspring number |
off.p |
Second parameter of the negative binomial distribution for offspring number |
neg |
the within-host effective population size (Ne) timesgeneration duration (g) |
pi |
probability of sampling an infected individual |
w.shape |
Shape parameter of the Gamma probability density function representing the generation time |
w.scale |
Scale parameter of the Gamma probability density function representing the generation time |
ws.shape |
Shape parameter of the Gamma probability density function representing the sampling time |
ws.scale |
Scale parameter of the Gamma probability density function representing the sampling time |
T |
Date when process stops (this can be Inf for fully simulated outbreaks) |
optiStart |
Method used to optimised colored tree (0=none, 1=slow, 2=fast) |
Value
A minimal non-zero probability phylogenetic+transmission tree, or an optimised version if parameters are provided
Simulate a transmission tree
Description
Simulate a transmission tree
Usage
makeTTree(
off.r,
off.p,
pi,
w.shape,
w.scale,
ws.shape = w.shape,
ws.scale = w.scale,
maxTime = Inf,
nSampled = NA
)
Arguments
off.r |
First parameter of the negative binomial distribution for offspring number |
off.p |
Second parameter of the negative binomial distribution for offspring number |
pi |
probability of sampling an infected individual |
w.shape |
Shape parameter of the Gamma probability density function representing the generation time |
w.scale |
Scale parameter of the Gamma probability density function representing the generation time |
ws.shape |
Shape parameter of the Gamma probability density function representing the sampling time |
ws.scale |
Scale parameter of the Gamma probability density function representing the sampling time |
maxTime |
Duration of simulation (can be Inf) |
nSampled |
Number of sampled individuals (can be NA for any) |
Value
A N*3 matrix in the following format with one row per infected host, first column is time of infection, second column is time of sampling, third column is infector
Return the medoid from a MCMC output
Description
Return the medoid from a MCMC output
Usage
medTTree(record, burnin = 0.5)
Arguments
record |
Output from inferTTree function |
burnin |
Proportion of the MCMC output to be discarded as burnin |
Value
The index of the medoid
Converts a phylogenetic tree into an ape phylo object
Description
Converts a phylogenetic tree into an ape phylo object
Usage
phyloFromPTree(ptree)
Arguments
ptree |
phylogenetic tree |
Value
phylo object
Examples
phyloFromPTree(extractPTree(simulateOutbreak()))
Plotting for ctree
Description
Plotting for ctree
Usage
## S3 method for class 'ctree'
plot(x, ...)
Arguments
x |
Object of class ctree, ie a colored phylogenetic tree |
... |
Additional parameters are passed on |
Value
Plot of ctree
Examples
plot(simulateOutbreak())
Plotting for ptree
Description
Plotting for ptree
Usage
## S3 method for class 'ptree'
plot(x, ...)
Arguments
x |
Object of class ptree, ie a phylogenetic tree |
... |
Additional parameters are passed on to ape::plot.phylo |
Value
Plot of ptree
Examples
plot(ptreeFromPhylo(ape::rtree(5),2020))
Plotting for resTransPhylo
Description
Plotting for resTransPhylo
Usage
## S3 method for class 'resTransPhylo'
plot(x, ...)
Arguments
x |
Output from inferTTree |
... |
Additional parameters are passed on |
Value
Plot of TransPhylo results
Plotting for ttree
Description
Plotting for ttree
Usage
## S3 method for class 'ttree'
plot(x, type = "summarised", w.shape = NA, w.scale = NA, ...)
Arguments
x |
Object of class ttree, ie a transmission tree |
type |
Type of plot to display, can be 'detailed' or 'summarised' (default) |
w.shape |
Shape parameter of the generation time, needed for detailed plot only |
w.scale |
Scale parameter of the generation time, needed for detailed plot only |
... |
Additional parameters are passed on |
Value
Plot of ttree
Examples
plot(extractTTree(simulateOutbreak()))
Plot both phylogenetic and transmission trees using colors on the phylogeny
Description
Plot both phylogenetic and transmission trees using colors on the phylogeny
Usage
plotCTree(
tree,
showLabels = TRUE,
showStars = TRUE,
cols = NA,
maxTime = NA,
cex = 1
)
Arguments
tree |
Combined phylogenetic/transmission tree |
showLabels |
Whether or not to show the labels |
showStars |
Whether or not to show stars representing transmission events |
cols |
Colors to use for hosts |
maxTime |
Maximum time to show on the x axis |
cex |
Expansion factor |
Value
Returns invisibly the first parameter
Examples
plotCTree(simulateOutbreak())
Plot a transmission tree in a detailed format
Description
Plot a transmission tree in a detailed format
Usage
plotTTree(ttree, w.shape, w.scale, showLabels = TRUE, maxTime = NA, cex = 1)
Arguments
ttree |
Transmission tree |
w.shape |
Shape parameter of the Gamma probability density function representing the generation time |
w.scale |
Scale parameter of the Gamma probability density function representing the generation time |
showLabels |
Whether or not to show the labels |
maxTime |
Maximum value of time to show on x axis |
cex |
Expansion factor |
Value
Returns invisibly the first parameter
Examples
plotTTree(extractTTree(simulateOutbreak()),2,1)
Plot a transmission tree in an economic format
Description
Plot a transmission tree in an economic format
Usage
plotTTree2(
ttree,
showLabels = TRUE,
showMissingLinks = 0,
maxTime = NA,
cex = 1
)
Arguments
ttree |
Transmission tree |
showLabels |
Boolean for whether or not to show the labels |
showMissingLinks |
Option for how to show missing links: (0) as dots, (1) as several gray levels, (2) as a single gray level |
maxTime |
Maximum value of time to show on x axis |
cex |
Expansion factor |
Value
Returns invisibly the first parameter
Examples
plotTTree2(extractTTree(simulateOutbreak()))
Plot MCMC traces
Description
Plot MCMC traces
Usage
plotTraces(record, burnin = 0, extend = F)
Arguments
record |
Output from inferTTree function |
burnin |
Proportion of the MCMC output to be discarded as burnin |
extend |
Whether to also show traces of off.r and off.p |
Value
Returns invisibly the first parameter
Print function for ctree objects
Description
Print function for ctree objects
Usage
## S3 method for class 'ctree'
print(x, ...)
Arguments
x |
Object of class ctree, ie a colored phylogenetic tree |
... |
Additional parameters are passed on |
Value
Print out details of the ctree
Examples
print(simulateOutbreak())
Print function for ptree objects
Description
Print function for ptree objects
Usage
## S3 method for class 'ptree'
print(x, ...)
Arguments
x |
Object of class ptree, ie a phylogenetic tree |
... |
Additional parameters are passed on |
Value
Print out details of the ptree
Examples
print(extractPTree(simulateOutbreak()))
Print function for resTransPhylo objects
Description
Print function for resTransPhylo objects
Usage
## S3 method for class 'resTransPhylo'
print(x, ...)
Arguments
x |
output from inferTTree |
... |
Additional parameters are passed on |
Value
Print out details of TransPhylo results
Print function for ttree objects
Description
Print function for ttree objects
Usage
## S3 method for class 'ttree'
print(x, ...)
Arguments
x |
Object of class ttree, ie a transmission tree |
... |
Additional parameters are passed on |
Value
Print out details of the ttree
Examples
print(extractTTree(simulateOutbreak()))
Calculate the probability of a phylogenetic tree given a transmission tree
Description
Calculate the probability of a phylogenetic tree given a transmission tree
Usage
probPTreeGivenTTree(ctree, neg, w = integer(0))
Arguments
ctree |
Combined phylogenetic/transmission tree |
neg |
Within-host coalescent rate |
w |
Vector of hosts for which to calculate the probability, or nothing for all |
Value
Probability of phylogeny given transmission tree
Calculate the probability of a phylogenetic tree given a transmission tree
Description
Calculate the probability of a phylogenetic tree given a transmission tree
Usage
probPTreeGivenTTreeR(ctree, neg, w = NULL)
Arguments
ctree |
Combined phylogenetic/transmission tree |
neg |
Within-host coalescent rate |
w |
Vector of hosts for which to calculate the probability, or NULL for all |
Value
Probability of phylogeny given transmission tree
Calculates the log-probability of a transmission tree
Description
Calculates the log-probability of a transmission tree
Usage
probTTree(
ttree,
rOff,
pOff,
pi,
shGen,
scGen,
shSam,
scSam,
dateT,
delta_t = 0.01
)
Arguments
ttree |
Transmission tree |
rOff |
First parameter of the negative binomial distribution for offspring number |
pOff |
Second parameter of the negative binomial distribution for offspring number |
pi |
probability of sampling an infected individual |
shGen |
Shape parameter of the Gamma probability density function representing the generation time |
scGen |
Scale parameter of the Gamma probability density function representing the generation time |
shSam |
Shape parameter of the Gamma probability density function representing the sampling time |
scSam |
Scale parameter of the Gamma probability density function representing the sampling time |
dateT |
Date when process stops (this can be Inf for fully simulated outbreaks) |
delta_t |
Grid precision |
Value
Probability of the transmission tree
Calculates the log-probability of a transmission tree
Description
Calculates the log-probability of a transmission tree
Usage
probTTreeR(
ttree,
off.r,
off.p,
pi,
w.shape,
w.scale,
ws.shape,
ws.scale,
dateT
)
Arguments
ttree |
Transmission tree |
off.r |
First parameter of the negative binomial distribution for offspring number |
off.p |
Second parameter of the negative binomial distribution for offspring number |
pi |
probability of sampling an infected individual |
w.shape |
Shape parameter of the Gamma probability density function representing the generation time |
w.scale |
Scale parameter of the Gamma probability density function representing the generation time |
ws.shape |
Shape parameter of the Gamma probability density function representing the sampling time |
ws.scale |
Scale parameter of the Gamma probability density function representing the sampling time |
dateT |
Date when process stops (this can be Inf for fully simulated outbreaks) |
Value
Probability of the transmission tree
Converts an ape phylo object into a phylogenetic tree
Description
Converts an ape phylo object into a phylogenetic tree
Usage
ptreeFromPhylo(tr, dateLastSample)
Arguments
tr |
phylo object |
dateLastSample |
date of the last sample |
Value
phylogenetic tree
Examples
ptreeFromPhylo(ape::rtree(5),2020)
Select the most representative transmission tree from a MCMC output
Description
Select the most representative transmission tree from a MCMC output
Usage
selectTTree(record, burnin = 0.5)
Arguments
record |
Output from inferTTree function |
burnin |
Proportion of the MCMC output to be discarded as burnin |
Value
The index of the selected transmission tree
Simulate an outbreak
Description
Simulate an outbreak
Usage
simulateOutbreak(
off.r = 1,
off.p = 0.5,
neg = 0.25,
nSampled = NA,
pi = 0.5,
w.shape = 2,
w.scale = 1,
ws.shape = NA,
ws.scale = NA,
w.mean = NA,
w.std = NA,
ws.mean = NA,
ws.std = NA,
dateStartOutbreak = 2000,
dateT = Inf
)
Arguments
off.r |
First parameter of the negative binomial distribution for offspring number |
off.p |
Second parameter of the negative binomial distribution for offspring number |
neg |
the within-host effective population size (Ne) timesgeneration duration (g) |
nSampled |
number of sampled infected individuals, or NA for any |
pi |
probability of sampling an infected individual |
w.shape |
Shape parameter of the Gamma probability density function representing the generation time |
w.scale |
Scale parameter of the Gamma probability density function representing the generation time |
ws.shape |
Shape parameter of the Gamma probability density function representing the sampling time |
ws.scale |
Scale parameter of the Gamma probability density function representing the sampling time |
w.mean |
Mean of the Gamma distribution representing the generation time |
w.std |
Std of the Gamma distribution representing the generation time |
ws.mean |
Mean of the Gamma distribution representing the sampling time |
ws.std |
Std of the Gamma distribution representing the sampling time |
dateStartOutbreak |
Date when index case becomes infected |
dateT |
Date when process stops (this can be Inf for fully simulated outbreaks) |
Value
Combined phylogenetic and transmission tree
Examples
simulateOutbreak()
simulateOutbreak(off.r=2,dateStartOutbreak=2010,dateT=2015)
Summary function for resTransPhylo objects
Description
Summary function for resTransPhylo objects
Usage
## S3 method for class 'resTransPhylo'
summary(object, ...)
Arguments
object |
output from inferTTree |
... |
Passed on to print.phylo |
Value
Print out details of TransPhylo results