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SPCompute

The goal of SPCompute is to compute power and sample size for replication GWAS study, while accommodates different kinds of covariate effects. The methodology used in the software is described in this paper by Ziang Zhang and Lei Sun. The detailed implementation guideline can be found in the vignette of this package.

Installation

You can install the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("AgueroZZ/SPCompute")

Example

This is a basic example which shows you how to solve a common problem of computing power for genetic association testing with a binary trait:

library(SPCompute)
## basic example code
parameters <- list(preva = 0.2, pG = 0.3, pE = 0.3, gammaG = 0.1, betaG = 0.1, betaE = 0.3)
Compute_Power(parameters, n = 8000, response = "binary", covariate = "none")
#> [1] 0.6404552

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.