diversity.range: Range of genetic diversity over time
In seedy: Simulation of Evolutionary and Epidemiological Dynamics

Description Usage Arguments Details Value See Also Examples

Generates multiple populations stochastically from an identical source, and measures the resulting diversity over time in each.

diversity.range(m.rate, runtime, equi.pop, iterations = 10, n.points = 100, 
genomelength = 1e+05, bottle.times=0, bottle.size=1, feedback = 1000, 
makeplot = TRUE, area = TRUE, colline = "blue", colarea = rgb(0, 0, 1, 0.4), 
ref.strain = NULL, init.freq = 1, libr=NULL, nuc=NULL, ...)

`m.rate`	Mutation rate (per genome per generation).
`runtime`	Number of bacterial generations over which to simulate.
`equi.pop`	Equilibrium effective population size.
`iterations`	Number of populations to simulate.
`n.points`	Number of equidistant points to sample diversity during `runtime`.
`genomelength`	Genome length.
`bottle.times`	Vector of population bottleneck times.
`bottle.size`	Size of population bottleneck.
`feedback`	Number of generations between each simulation report.
`makeplot`	Should resulting diversity be plotted?
`area`	Should 95% central quantile of genetic diversity be shaded? If `FALSE`, then individual diversity trajectories are plotted.
`colline`	Colour of lines (if `makeplot=TRUE`).
`colarea`	Colour of shaded area (if `makeplot=TRUE` and `area=TRUE`).
`ref.strain`	Reference strain, if required.
`init.freq`	Initial frequency of strains in starting population (if `libr` and `nuc` specified)
`libr`	Library of initial sequences.
`nuc`	Nucleotides at polymorphic sites, corresponding to `libr`.
`...`	Additional arguments to be passed to `plot`.

Provides an empirical estimate of the expected genetic diversity (pairwise SNP distance) over time, with associated uncertainty. Initial population can be specified using the libr, nuc and init.freq arguments, otherwise population is grown from a single genotype. Resolution can be improved by increasing n.points, and accuracy by increasing iterations (at the expense of accuracy).

A iterations by n.points matrix with diversity over time for each simulation.

plotdiversity

iterations <- 10
K <- diversity.range(m.rate=0.0005, runtime=1000, equi.pop=1000,
iterations=iterations, n.points=100, genomelength=100000, feedback=100, 
makeplot=TRUE, area=TRUE, colline="blue", colarea=rgb(0,0,1,0.4))