Infer transmission tree given a phylogenetic tree

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)
#> 
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#> Result from TransPhylo analysis
#> pi=7.36e-01 [5.65e-01;8.29e-01]
#> neg=5.33e-01 [1.28e-01;1.08e+00]
#> off.r=9.83e-01 [2.80e-01;1.57e+00]
#> off.p=5.00e-01 [5.00e-01;5.00e-01]