sim_phenoval: Simulate phenotypic values

In neyhartj/qgsim: Simulations of Plant Breeding Experiments

Simulate phenotypic values

Description

Simulates phenotypic observations given the genotypic value of individuals and the heritability of a quantitative trait.

Usage

sim_phenoval(pop, h2, n.env = 1, n.rep = 1, ...)

Arguments

pop	An object of class pop.
h2	The heritability of the trait or traits. May be a numeric vector of length 1 (heritability is the same for all traits) or a numeric vector of length n_trait.
n.env	The number of environments in which to phenotype.
n.rep	The number of replicates of each individual in each environment.
...	Other arguments. See Details.
return.eff	Should the variance components and effects be returned?

Details

Other arguments that can be specified are :

V_E

The variance of environmental effects. May be a scalar (V_E is the same for all traits) or a numeric vector of length n_trait.

V_R

The variance of the residual effects. May be a scalar (V_R is the same for all traits) or a numeric vector of length n_trait.

Environmental effects are drawn from a normal distribution such that e ~ N(0, V_E), where V_E is the environmental variance. If V_E is not provided, it is 8 times the genotypic variance. Genotype-environmental interaction effects are drawn from a normal distribution such that ge ~ N(0, V_GE), where V_GE is the genotype-environment interaction variance. If V_GE is not provided, it defaults to 2 times the genotypic variance. Residual effects are drawn from a normal distribution such that \epsilon ~ N(0, V_R), where V_R is the residual variance. If V_R is not provided, it is calculated from h2, where V_R = n.rep * n.env * (\frac{Vg}{h2} - Vg).

Value

An object of class pop with all information in the input pop object, plus simulated phenotypes.

Examples

# Create a genome
n.mar  <- c(505, 505, 505)
len <- c(120, 130, 140)

genome <- sim_genome(len, n.mar)

# Simulate a a trait with 15 QTL
qtl.model <- matrix(nrow = 15, ncol = 4)

genome <- sim_gen_model(genome, qtl.model, add.dist = "geometric", max.qtl = 15)

pop <- sim_pop(genome = genome, n.ind = 200)

## Default simulates environment and residual effects, but no GxE
pop1 <- sim_phenoval(pop = pop, h2 = 0.5, n.env = 2, n.rep = 2)


# Simulate GxE
# First simulate a population
pop <- sim_pop(genome = genome, n.ind = 200, ignore.gen.model = TRUE)

# Second, create a gene model with QxE
genome <- sim_gen_model(genome = genome, qtl.model = qtl.model, geno = pop$geno,
                        add.dist = "geometric", V_GE.scale = 2)
                        
# Re-save the population
pop <- create_pop(genome = genome, geno = do.call("cbind", pop$geno))

# Generate phenotypes 
pop1 <- sim_phenoval(pop = pop, h2 = 0.5, n.env = 2, n.rep = 2)

neyhartj/qgsim documentation built on Nov. 11, 2023, 4:08 p.m.