dominance.calc {gnonadd}

Genetic dominance effects

Description

This function estimates the dominance effect of a genetic variant on a quantitatvie trait Nothing fancy here. We apply a simple linear regression model to estimate dominance effects. We include a linear term, coded as 0,1 and 2 for non-carriers, heterozygotes and homozygous carriers of the effect allele. We also include a dominance term, coded as 1 for homozygous carriers and 0 for others. Effect size and significance is based on the dominance term.

Usage

dominance.calc(
  qt,
  g,
  round_imputed = FALSE,
  covariates = as.data.frame(matrix(0, nrow = 0, ncol = 0))
)

Arguments

qt

A numeric vector

g

A vector with (possibly imputed) genotype values. All entries should be larger than 0 and smaller than 2.

round_imputed

A boolian variable determining whether imputed genotype values should be rounded to the nearest integer in the analysis

covariates

A dataframe containing any covariates that should be used; one column per covariate.

Value

A list with the dominanc effect and corresponding standard error, t statistic and p-value

Examples

g_vec <- rbinom(100000, 2, 0.3)
qt_vec <- rnorm(100000) + 0.2 * g_vec^2
res <- dominance.calc(qt_vec, g_vec)