Package 'TransPhylo' reference manual

Title:	Inference of Transmission Tree from a Dated Phylogeny
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>.
Authors:	Xavier Didelot [aut, cre] , Yuanwei Xu [ctb]
Maintainer:	Xavier Didelot <[email protected]>
License:	GPL (>=2)
Version:	1.4.10
Built:	2024-11-09 04:39:38 UTC
Source:	https://github.com/xavierdidelot/TransPhylo

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 [email protected]

References

Didelot et al. (2014) <doi:10.1093/molbev/msu121> Didelot et al. (2017) <doi:10.1093/molbev/msw275>.

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)
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)
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)
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

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)
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)
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)
extractPTree(ctree)

Arguments

ctree

Combined tree

Value

phylogenetic tree

Examples

extractPTree(simulateOutbreak())
extractPTree(simulateOutbreak())

Extracts transmission tree from a combined phylogenetic/transmission tree

Description

Extracts transmission tree from a combined phylogenetic/transmission tree

Usage

extractTTree(ctree)
extractTTree(ctree)

Arguments

ctree

Combined tree

Value

transmission tree

Examples

extractTTree(simulateOutbreak())
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
)
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
)
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)
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)
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
)
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

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,
  delta_t = 0.01,
  verbose = F
)
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,
  delta_t = 0.01,
  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)
`delta_t`	Grid precision (smaller is better but slower)
`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

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,
  qNeg = NA,
  qOff.r = NA,
  qOff.p = NA,
  qPi = NA,
  startCTree = NA,
  updateTTree = TRUE,
  optiStart = 2,
  dateT = Inf,
  delta_t = NA,
  verbose = F
)
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,
  qNeg = NA,
  qOff.r = NA,
  qOff.p = NA,
  qPi = NA,
  startCTree = NA,
  updateTTree = TRUE,
  optiStart = 2,
  dateT = Inf,
  delta_t = NA,
  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
`qNeg`	Proposal kernel range for parameter Ne*g
`qOff.r`	Proposal kernel range for parameter Off.r
`qOff.p`	Proposal kernel range for parameter Off.p
`qPi`	Proposal kernel range for 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)
`delta_t`	Grid precision (smaller is better but slower)
`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)
inferTTree(ptreeFromPhylo(ape::rtree(5),2020),mcmcIterations=100)

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
)
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
)
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)
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)
phyloFromPTree(ptree)

Arguments

ptree

phylogenetic tree

Value

phylo object

Examples

phyloFromPTree(extractPTree(simulateOutbreak()))
phyloFromPTree(extractPTree(simulateOutbreak()))

Plotting for ctree

Description

Plotting for ctree

Usage

## S3 method for class 'ctree'
plot(x, ...)
## 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())
plot(simulateOutbreak())

Plotting for ptree

Description

Plotting for ptree

Usage

## S3 method for class 'ptree'
plot(x, ...)
## 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))
plot(ptreeFromPhylo(ape::rtree(5),2020))

Plotting for resTransPhylo

Description

Plotting for resTransPhylo

Usage

## S3 method for class 'resTransPhylo'
plot(x, ...)
## 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, ...)
## 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(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
)
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())
plotCTree(simulateOutbreak())

Plot MCMC traces

Description

Plot MCMC traces

Usage

plotTraces(record, burnin = 0, extend = F)
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

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)
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)
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
)
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()))
plotTTree2(extractTTree(simulateOutbreak()))

Print function for ctree objects

Description

Print function for ctree objects

Usage

## S3 method for class 'ctree'
print(x, ...)
## 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(simulateOutbreak())

Print function for ptree objects

Description

Print function for ptree objects

Usage

## S3 method for class 'ptree'
print(x, ...)
## 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(extractPTree(simulateOutbreak()))

Print function for resTransPhylo objects

Description

Print function for resTransPhylo objects

Usage

## S3 method for class 'resTransPhylo'
print(x, ...)
## 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, ...)
## 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()))
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))
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)
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
)
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
)
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)
ptreeFromPhylo(tr, dateLastSample)

Arguments

`tr`	phylo object
`dateLastSample`	date of the last sample

Value

phylogenetic tree

Examples

ptreeFromPhylo(ape::rtree(5),2020)
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)
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
)
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)
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, ...)
## S3 method for class 'resTransPhylo'
summary(object, ...)

Arguments

`object`	output from inferTTree
`...`	Passed on to print.phylo

Value

Print out details of TransPhylo results

Package 'TransPhylo'

Help Index

Inference of Transmission Tree from a Dated Phylogeny

Description

Author(s)

References

See Also

Convert to coda mcmc format

Description

Usage

Arguments

Value

Build a matrix indicating for each pairs of individuals how many intermediates there are in the transmission chain

Description

Usage

Arguments

Value

Build a matrix of probability of who infected whom from a MCMC output

Description

Usage

Arguments

Value

Build a consensus transmission tree from a MCMC output

Description

Usage

Arguments

Value

Convert to coda mcmc format

Description

Usage

Arguments

Value

Return the date of last sample from a ttree or ctree or ptree

Description

Usage

Arguments

Value

Return the combined tree corresponding to a given iteration of the TransPhylo results

Description

Usage

Arguments

Value

Extracts phylogenetic tree from a combined phylogenetic/transmission tree

Description

Usage

Arguments

Value

Examples

Extracts transmission tree from a combined phylogenetic/transmission tree

Description

Usage

Arguments

Value

Examples

Extract and return realised generation time distribution

Description

Usage

Arguments

Value

Returns and/or plot numbers of sampled and unsampled cases over time

Description

Usage

Arguments

Value

Extract and return distribution of infection time of given sampled case(s)

Description

Usage

Arguments

Value

Extract and return offspring distribution of given sampled case(s)

Description

Usage

Arguments

Value

Extract and return realised sampling time distribution

Description

Usage

Arguments

Value

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".