jaatha (version 2.7.0)

dm.addMutation: Adds mutations to a demographic model

Description

This functions adds the assumption to the model that neutral mutations occur in the genomes at a constant rate. The rate is quantified through a parameter usually named theta in population genetics. It equals 4*N0*mu, where N0 is the effective diploid population size of population one at the time of sampling and mu is the neutral mutation rate for an entire locus.

Usage

dm.addMutation(dm, lower.range, upper.range, fixed.value, par.new = T,
  new.par.name = "theta", parameter, group = 0, variance = 0)

Arguments

dm

The demographic model to which mutations should be added

lower.range

If you want to estimate the mutation rate, this will be used as the smallest possible value.

upper.range

If you want to estimate the mutation rate, this will be used as the largest possible value.

fixed.value

If specified, the mutation rate will not be estimated, but assumed to be fixed at the given value.

par.new

If 'TRUE' a new parameter will be created using the arguments 'lower.range' and 'upper.range' or 'fixed.value'. It will be named 'new.par.name'. If 'FALSE' the argument 'parameter' will be evaluated instead.

new.par.name

The name for the new parameter.

parameter

Instead of creating a new parameter, you can also set the mutation rate to an expression based on existing parameters. For example setting this to "theta" will use an parameter with name theta that you have previously created. You can also use R expressio

group

Group of loci for with this feature is added. 0 means that the feature applies to all groups, and 1 is the default group. Set to 1 or an greater integer to set this feature only for the corresponding group of loci.

variance

Set to a value different from 0 to introduce variation in the the parameter value for different loci. The variation follows a gamma distribution with mean equal to the value provided as parameter, and variance as given here. Can also be set t

Value

• The demographic model with mutation.

Examples

# Create a new parameter
dm <- dm.createDemographicModel(c(25,25), 100)
dm <- dm.addSpeciationEvent(dm, 0.01, 5)
dm <- dm.addMutation(dm, 1, 20)

# Create a new fixed parameter
dm <- dm.createDemographicModel(c(25,25), 100)
dm <- dm.addSpeciationEvent(dm, 0.01,5)
dm <- dm.addMutation(dm, fixed.value=7)

# Use an existing parameter
dm <- dm.createDemographicModel(c(25,25), 100)
dm <- dm.addParameter(dm, "theta", 0.01, 5)
dm <- dm.addMutation(dm, par.new=FALSE, parameter="2*log(theta)+1")