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Simulating natural selection through time in a bi-allelic gene

Source: R/NatSelSim.R
NatSelSim.Rd

NatSelSim simulates natural selection in a bi-allelic gene through n.gen generations.

Usage

NatSelSim(
  w11 = 1,
  w12 = 1,
  w22 = 0.9,
  p0 = 0.5,
  n.gen = 10,
  plot.type = "animateall",
  print.data = FALSE,
  knitr = FALSE
)

Arguments

w11

Number giving the fitness of genotype A1A1. Values will be normalized if any genotype fitness exceeds one.

w12

Number giving the fitness of genotype A1A2. Values will be normalized if any genotype fitness exceeds one.

w22

Number giving the fitness of genotype A2A2. Values will be normalized if any genotype fitness exceeds one.

p0

Initial (time = 0) allelic frequency of A1. A2's initial allelic frequency is 1-p0.

n.gen

Number of generation that will be simulated.

plot.type

String indicating if plot should be animated. The default, "animateall" animate all possible panels. Other options are "static" (no animation), "animate1", "animate3", or "animate4". Users can animate each panel individually (using plot.type = "animateX", with X being the panel which one wants to animate (so options are "animate1", "animate3", and "animate4" (see return for more info).

print.data

Logical indicating whether all simulation results should be returned as a data.frame. Default value is FALSE.

knitr

Logical indicating if plot is intended to show up in RMarkdown files made by the Knitr R package.

Value

If print.data = TRUE, it returns a data.frame containing the number of individuals for each genotype through time. The plots done by the function shows (1) Allele frequency change through time. (2) The adaptive landscape (which remains static during the whole simulation, so can't be animated), (3) Time series of mean population fitness, and (4) Time series of genotypic population frequencies.

Details

If any value of fitness (i.e., w11, w12, w22) is larger than one, fitness is interpreted as absolute fitness and values are re-normalized.

References

Fisher, R. A. (1930). The Fundamental Theorem of Natural Selection. In: The genetical theory of natural selection. The Clarendon Press

Plutynski, A. (2006). What was Fisher’s fundamental theorem of natural selection and what was it for?. Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences, 37(1), 59-82.

See also

Other microevolution: OneGenHWSim(), WFDriftSim(), plotNatSel(), plotWFDrift()

Author

Matheus Januario, Jennifer Auler, Dan Rabosky

Examples


#using the default values (w11=1, w12=1, w22=0.9, p0=0.5, n.gen=10)
NatSelSim()

# Continuing a simulation for extra time:
# Run the first simulation
sim1=NatSelSim(w11 = .4, w12 = .5, w22 = .4, p0 = 0.35, 
n.gen = 5, plot.type = "static", print.data = TRUE, knitr = TRUE)

# Then take the allelic frequency form the first sim:
new_p0 <- (sim1$AA[nrow(sim1)] + sim1$Aa[nrow(sim1)]*1/2) 
# and use as p0 for a second one:

NatSelSim(w11 = .4, w12 = .5, w22 = .4, p0 = new_p0, n.gen = 5, plot.type = "static", knitr = TRUE)