# mcmc.popsize

From ape v2.6-3
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##### Reversible Jump MCMC to Infer Demographic History

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.

Keywords
manip
##### 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 hierarchicalis 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 gi
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
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.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.

##### 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.

skyline and skylineplot.

##### Aliases
• mcmc.popsize
• extract.popsize
• plot.popsize
• lines.popsize
##### Examples
# get tree
data("hivtree.newick") # example tree in NH format

# 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)
Documentation reproduced from package ape, version 2.6-3, License: GPL (>= 2)

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