birthDeathMCMC {cloneRate}

Growth rate estimate using MCMC

Description

Uses Rstan and the No U-turn sampler to approximate the growth rate using the likelihood from Stadler 2009 "On incomplete sampling under birth–death models and connections to the sampling-based coalescent"

Usage

birthDeathMCMC(
  tree,
  maxGrowthRate = 4,
  alpha = 0.05,
  verbose = TRUE,
  nChains = 4,
  nCores = 1,
  chainLength = 2000
)

Arguments

tree

An ultrametric tree subset to include only the clone of interest. Alternatively, a list with several such trees.

maxGrowthRate

Sets upper bound on birth rate. Default is 4 but this will depend on the nature of the data

alpha

Used for calculation of confidence intervals. 1-alpha confidence intervals used with default of alpha = 0.05 (95 percent confidence intervals)

verbose

TRUE or FALSE, should the Rstan MCMC intermediate output and progress be printed?

nChains

Number of chains to run in MCMC. Default is 4

nCores

Number of cores to perform MCMC. Default is 1, but chains can be run in parallel

chainLength

Number of iterations for each chain in MCMC. Default is 2000 (1000 warm-up + 1000 sampling), increase if stan tells you to

Value

A dataframe including the net growth rate estimate, confidence intervals, and other important details (clone age estimate, runtime, n, etc.)

See Also

internalLengths maxLikelihood which use alternative methods for growth rate estimation from an ultrametric tree.

Examples

df <- birthDeathMCMC(cloneRate::exampleUltraTrees[[1]])