run.espresso.G: Runs a full ESPRESSO analysis

In agaye/ESPRESSO.G: Power Analysis and Sample Size Calculation for a model with a main effect genetic covariate

Description

This function calls the functions required to run a full ESPRESSO analysis where the model consists of an outcome (binary or continuous) determinant by a binary or continuous environmental determinant.

Usage

run.espresso.G(simulation.params = NULL, pheno.params = NULL,
  geno.params = NULL, scenarios2run = 1)

Arguments

simulation.params	general parameters for the scenario(s) to analyse
pheno.params	paramaters for the outcome variable
geno.params	parameters for the genetic determinant
scenarios2run	the indices of the scenarios one wishes to analyse

Details

The function calls all the functions required to generate the error free data, add the error to obtain the observed data, run a glm analysis and calculate the sample size required and the empirical and theoretical power. The functions called to carry the various tasks are internal.

Value

a summary table that contains both the input parameters and the results of the analysis

Author(s)

Gaye A.

Examples

{

# load the table that hold the input parameters; each of the table
# hold parameters for 4 scenarios:
# scenario 1: a binary outcome determined by a binary SNP
# scenario 2: a binary outcome determined by an additive SNP
# scenario 3: a quantitative outcome determined by a binary SNP
# scenario 4: a quantitative outcome determined by an additive SNP
data(simulation.params)
data(pheno.params)
data(geno.params)

# run the function for the first two scenarios, two binomial models
run.espresso.G(simulation.params, pheno.params, geno.params, scenarios2run=c(1,2))

# run the function for the last two scenarios, two gaussian models
run.espresso.G(simulation.params, pheno.params, geno.params, scenarios2run=c(3,4))
}

agaye/ESPRESSO.G documentation built on May 10, 2019, 7:31 a.m.