gsimC: Simulate Genetic Data Based on Given Parameters

In psoerensen/qgg: Statistical Tools for Quantitative Genetic Analyses

Simulate Genetic Data Based on Given Parameters

Description

This function simulates phenotype data by random sampling of markers available on 'Glist'. Default parameters for the simulated phenotype reflect the genetic architecture assumed by BayesC prior(Habier et al., 2011). This function is under active development.

Usage

gsimC(Glist = NULL, h2 = NULL, m = NULL, prp.cau = NULL, n = NULL)

Arguments

Glist	A list containing genetic data. If NULL, the function will stop with an error.
h2	Heritability. If NULL, heritability of 0.5 is assumed.
m	Number of causal markers. The values for either 'm' or 'prp.cau' should be provided at any given time. If the list of quality controlled markers is not available then list of raw markers is used. If 'm' is NULL and 'prp.cau' is also NULL, 'prp.cau' will default to 0.001.
prp.cau	Proportion of causal markers. The values for either 'm' or 'prp.cau' should be provided at any given time.
n	Number of individuals randomly sampled from 'Glist'. If NULL, all the individuals on 'Glist' is used.

Value

A list containing:

• y: Vector of simulated phenotypes.

• g: Vector of simulated genetic values.

• e: Vector of simulated residual effects.

• b: Vector of effect sizes of the simulated causal markers.

• causal: Vector of ids for the simulated causal markers.

• h2: Estimated heritability of the simulated phenotype.

Author(s)

Peter Soerensen

Merina Shrestha

psoerensen/qgg documentation built on March 9, 2024, 10:02 p.m.