INT_RAN: Gene-environment interaction test treating genetic main effects as random

Description

Perform the interaction term only test for gene-environment interaction, assuming random genetic main effects.

Usage

INT_RAN(phenotype, genotypes, covariates, mainweights = wuweights, 
interweights = wuweights, family = "gaussian", binomialimpute = FALSE)

Arguments

phenotype

a numeric vector of phenotype values.

genotypes

a matrix or a data frame for all SNPs in the test gene or genomic region. The order of rows must match the order in phenotype.

covariates

a matrix, a data frame or a vector of covariates to adjust for. The interaction between SNPs and the first column of covariates is tested. The order of rows must match the order in phenotype.

mainweights

the weight function or vector of genetic main effects (default = wuweights).

interweights

the weight function or vector of gene-environment interaction effects (default = wuweights).

family

"gaussian" for quantitative traits and "binomial" for dichotomous traits (default = "gaussian").

binomialimpute

impute missing genotypes randomly using a binomial distribution with 2 trials and success probability equal to the minor allele frequency. If FALSE, then impute missing genotypes to 0 (default = FALSE).

Value

p-value.

References

Chen H, Meigs JB, Dupuis J. (2014) Incorporating gene-environment interaction in testing for association with rare genetic variants. Hum Hered 78, 81-90.

Wu MC, Lee S, Cai T, Li Y, Boehnke M, Lin X. (2011) Rare-variant association testing for sequencing data with the sequence kernel association test. Am J Hum Genet 89, 82-93.

Examples

Run this code

data(rareGEgeno)
data(rareGEpheno)
# quantitative traits - testing for gene-BMI interactions
INT_RAN(rareGEpheno$y1, rareGEgeno, rareGEpheno[, c("bmi", "age", "sex")])
# dichotomous traits - testing for gene-BMI interactions
INT_RAN(rareGEpheno$y2, rareGEgeno, rareGEpheno[, c("bmi", "age", "sex")], 
	family = "binomial")