expected.variance.effect {gnonadd}

Expected variance effect from additive effect

Description

This function interpolates data from a simple simulation to give an estimate of the variance effect induced by an additive effect. The simulation code is stored under inst/raw/. We assume that the trait has been inverse normal transformed. Under the simulation, there is no variance effect, so the variance effect is fully induced by the inverse normal transform.

Usage

expected.variance.effect(maf, beta_add)

Arguments

maf

Minor allele frequency of the variant, should be in the range 0 to 0.5.

beta_add

Additive effect of the variant, should be in the range 0 to 3.5. This variable can be a vector of values.

Value

The expected variance effect for the variant from the given maf, beta combination.

Examples

maf <- 0.1
beta_val <- 0.3
expected_var <- expected.variance.effect(maf, beta_val)

beta_vec <- seq(0.1,2, length.out = 20)
expected_var <- expected.variance.effect(maf, beta_vec)