README.md

In SharonLutz/gxeRC: Power analyses for gene by environment interactions of both rare and common variants

gxeRC

The gxeRC R package that examines gene by environment interactions of both rare and common variants.

Installation

install.packages("devtools") # devtools must be installed first

devtools::install_github("SharonLutz/gxeRC")

Input

For n subjects, the number of SNPs X inputted by the user (input: nSNP) are generated from binomial distributions with minor allele frequency specified by the user (input: MAF). The environmental factor Z is generated from a normal distribution with mean and variance inputted by the user. The outcome Y is generated from a normal distribution with mean as follows:

E[Y] = β0 + βz Z + ∑j βx Xj + βI ∑j Xj Z

for j=1,...,k where k= the number of SNPs.

See the manpage for more detail regarding the input of the gxeRC function.

library(gxeRC)
?gxeRC # For details on this function

Example

For 5,000 subjects, 3 SNPs X with MAF of 0.05, 0.01, and 0.005, respectively, and a normally distributed environmental factor Z, we generated the proportion of simulations the null hypothesis was rejected for the SNP by environment interaction on the outcome Y for each SNP independently and for the joint interaction using the following commands.

library(gxeRC)
gxeRC(n = 5000, nSNP = 3, MAF = c(0.05, 0.01, 0.005), betaX = c(0.25, 0.25, 0.25), 
betaI = c(0, 0.05, 0.1),zMu = 0, zVar = 1, yVar = 1, nSim = 1000, alpha = 0.05)

Output

For this example, we get the following matrix and corresponding plot which output proportion of simulations the null hypothesis was rejected when the null was true (row 1 of the matrix) and the proportion of simulations the null hypothesis was rejected when the alternative was true (row 2 and 3 of the matrix) for the SNP by environment interaction on the outcome. We can see from the plot below that largest proportion of simulations where the null hypothesis was rejected in this scenario are when the SNP by environment interaction is tested for all 3 SNPs instead of for each SNP individually.

      lmX1  lmX2  lmX3 lmAll
[1,] 0.016 0.015 0.020 0.052
[2,] 0.095 0.030 0.017 0.154
[3,] 0.439 0.091 0.045 0.578

SharonLutz/gxeRC documentation built on July 23, 2024, 11:39 p.m.