sim_backcrossing: Function to simulate data using a back crossing scheme

View source: R/sim_backcrossing.R

sim_backcrossingR Documentation

Function to simulate data using a back crossing scheme

Description

Individual based simulation of the accumulation of junctions, under a back crossing scheme

Usage

sim_backcrossing(
  population_size = 100,
  freq_ancestor_1 = 0.5,
  total_runtime = 5,
  size_in_morgan = 1,
  number_of_markers = 100,
  seed = 6,
  time_points = -1
)

Arguments

population_size

Population size

freq_ancestor_1

Frequency of ancestor 1 at t = 0

total_runtime

Number of generations to simulate

size_in_morgan

Mean number of crossovers per meiosis (e.g. size in Morgan of the chromosome)

number_of_markers

number of molecular markers

seed

Seed of the pseudo-random number generator

time_points

vector with time points at which local ancestry has to be recorded to be returned at the end of the simulation. If left at -1, ancestry is recorded at every generation (computationally heavy).

Value

List with five entries: average_junctions: average number of junctions over time, detected_junctions: average number of detected junctions, given the markers. markers: vector with the locations of the molecular markers, junction_distribution: distribution of junctions per time step average_heterozygosity: average heterozygosity.

Examples

sim_backcrossing(population_size = 100,
                       total_runtime = 5,
                       size_in_morgan = 1, number_of_markers = 100, seed = 6,
                       time_points = 1:5)

junctions documentation built on March 18, 2022, 6:28 p.m.