sim.pheno.qtl.GxE: Simulates continuous outcome data

In kwesterman/ESPRESSO.GxE.RV: Power analysis and sample size calculation for a multi-variant gene-environment interaction model

Simulates continuous outcome data

Description

Uses the effects data of the determinants to construct a linear predictor(LP). The outcome is normally distributed variable generated with a mean equal to LP and a standard deviation of 1. Some error is then added to the simulated outcome to obtained the observed outcome.

Usage

sim.pheno.qtl.GxE(
  numsubjects = NULL,
  pheno.mean = NULL,
  pheno.sd = NULL,
  genotype = NULL,
  geno.efkt = NULL,
  geno.frac_causal = NULL,
  environment = NULL,
  env.efkt = NULL,
  interaction = NULL,
  int.efkt = NULL
)

Arguments

pheno.mean	statistical mean
pheno.sd	standard deviation
genotype	Genotype matrix (N x g.nvar)
geno.efkt	Effect of the genetic variant
geno.frac_causal	Fraction of causal genetic variants
environment	Exposure data for environment
env.efkt	Effect of the environmental determinants
interaction	Interaction matrix (N x g.nvar)
int.efkt	Interaction effect
num.subjects	Number of subjects to simulate

Value

A dataframe of phenotype

Author(s)

Gaye A.; Westerman K.

kwesterman/ESPRESSO.GxE.RV documentation built on Aug. 27, 2023, 4:44 a.m.