mcmc.popsize {ape} | R Documentation

## Reversible Jump MCMC to Infer Demographic History

### Description

These functions implement a reversible jump MCMC framework to infer the demographic history, as well as corresponding confidence bands, from a genealogical tree. The computed demographic history is a continous and smooth function in time. `mcmc.popsize` runs the actual MCMC chain and outputs information about the sampling steps, `extract.popsize` generates from this MCMC output a table of population size in time, and `plot.popsize` and `lines.popsize` provide utility functions to plot the corresponding demographic functions.

### Usage

    mcmc.popsize(tree,nstep, thinning=1, burn.in=0,progress.bar=TRUE,
        method.prior.changepoints=c("hierarchical", "fixed.lambda"), max.nodes=30,
       lambda=0.5, gamma.shape=0.5, gamma.scale=2,
        method.prior.heights=c("skyline", "constant", "custom"),
        prior.height.mean,
        prior.height.var)
    extract.popsize(mcmc.out, credible.interval=0.95, time.points=200, thinning=1, burn.in=0)
    ## S3 method for class 'popsize'
    plot(x, show.median=TRUE, show.years=FALSE, subst.rate, present.year, ...)
    ## S3 method for class 'popsize'
    lines(x, show.median=TRUE,show.years=FALSE, subst.rate, present.year, ...)

### Arguments

`tree` | Either an ultrametric tree (i.e. an object of class `"phylo"`), or coalescent intervals (i.e. an object of class `"coalescentIntervals"`).
`nstep` | Number of MCMC steps, i.e. length of the Markov chain (suggested value: 10,000-50,000).
`thinning` | Thinning factor (suggest value: 10-100).
`burn.in` | Number of steps dropped from the chain to allow for a burn-in phase (suggest value: 1000).
`progress.bar` | Show progress bar during the MCMC run.
`method.prior.changepoints` | If `hierarchical`is chosen (the default) then the smoothing parameter lambda is drawn from a gamma distribution with some specified shape and scale parameters. Alternatively, for `fixed.lambda` the value of lambda is a given constant.
`max.nodes` | Upper limit for the number of internal nodes of the approximating spline (default: 30).
`lambda` | Smoothing parameter. For `method="fixed.lambda"` the specifed value of lambda determines the mean of the prior distribution for the number of internal nodes of the approximating spline for the demographic function (suggested value: 0.1-1.0).
`gamma.shape` | Shape parameter of the gamma function from which `lambda` is drawn for `method="hierarchical"`.
`gamma.scale` | Scale parameter of the gamma function from which `lambda` is drawn for `method="hierarchical"`.
`method.prior.heights` | Determines the prior for the heights of the change points. If `custom` is chosen then two functions describing the mean and variance of the heigths in depence of time have to be specified (via `prior.height.mean` and `prior.height.var` options). Alternatively, two built-in priors are available: `constant` assumes constant population size and variance determined by Felsenstein (1992), and `skyline` assumes a skyline plot (see Opgen-Rhein et al. 2004 for more details).
`prior.height.mean` | Function describing the mean of the prior distribution for the heights (only used if `method.prior.heights = custom`).
`prior.height.var` | Function describing the variance of the prior distribution for the heights (only used if `method.prior.heights = custom`).
`mcmc.out` | Output from `mcmc.popsize` - this is needed as input for `extract.popsize`.
`credible.interval` | Probability mass of the confidence band (default: 0.95).
`time.points` | Number of discrete time points in the table output by `extract.popsize`.
`x` | Table with population size versus time, as computed by `extract.popsize`.
`show.median` | Plot median rather than mean as point estimate for demographic function (default: TRUE).
`show.years` | Option that determines whether the time is plotted in units of of substitutions (default) or in years (requires specification of substution rate and year of present).
`subst.rate` | Substitution rate (see option show.years).
`present.year` | Present year (see option show.years).
`...` | Further arguments to be passed on to `plot`.

### Details

Please refer to Opgen-Rhein et al. (2005) for methodological details, and the help page of `skyline` for information on a related approach.

### Author(s)

Rainer Opgen-Rhein and Korbinian Strimmer (http://strimmerlab.org). Parts of the rjMCMC sampling procedure are adapted from R code by Karl Browman (http://kbroman.org/)

### References

Opgen-Rhein, R., Fahrmeir, L. and Strimmer, K. 2005. Inference of demographic history from genealogical trees using reversible jump Markov chain Monte Carlo. BMC Evolutionary Biology, 5, 6.

### See Also

`skyline` and `skylineplot`.

### Examples

    # get tree
    data("hivtree.newick") # example tree in NH format
    tree.hiv <- read.tree(text = hivtree.newick) # load tree

    # run mcmc chain
    mcmc.out <- mcmc.popsize(tree.hiv, nstep=100, thinning=1, burn.in=0,progress.bar=FALSE) # toy run
    #mcmc.out <- mcmc.popsize(tree.hiv, nstep=10000, thinning=5, burn.in=500) # remove comments!!

    # make list of population size versus time
    popsize  <- extract.popsize(mcmc.out)

    # plot and compare with skyline plot
    sk <- skyline(tree.hiv)
    plot(sk, lwd=1, lty=3, show.years=TRUE, subst.rate=0.0023, present.year = 1997)
    lines(popsize, show.years=TRUE, subst.rate=0.0023, present.year = 1997)

[Package ape version 3.5 Index]