GWAF (version 2.2)

geepack.quant.int.batch.imputed: function to test gene-environment or gene-gene interactions between a continuous trait and a batch of imputed SNPs in families using Generalized Estimation Equation model

Description

Fit Generalized Estimation Equation (GEE) model to test gene-environment or gene-gene interactions for a continuous phenotype and all imputed SNPs in a genotype file in family data under additive genetic model. The interaction term is the product of SNP genotype (allelic dosage) and a covariate for interaction (cov.int). The covariate for interaction (cov.int) can be SNP genotype (gene-gene interaction) or an environmental factor (gene-environment interaction). Only one interaction term is allowed. When cov.int is dichotomous, stratified analyses can be requested by specifying sub="Y". The covariance between the main effect (SNP) and the interaction effect is provided in the output when stratified analysis is not requested. Each pedigree is treated as a cluster, with independence working correlation matrix used in the robust variance estimator. This function applies the same interaction test to all imputed SNPs in the genotype data. In each test for interaction, the geese function from geepack package is used.

Usage

geepack.quant.int.batch.imputed(phenfile,genfile,pedfile,phen,covars,cov.int,sub="N",
outfile,col.names=T,sep.ped=",",sep.phe=",",sep.gen=",")

Arguments

phenfile

a character string naming the phenotype file for reading (see format requirement in details)

genfile

a character string naming the (imputed) genotype file for reading (see format requirement in details)

pedfile

a character string naming the pedigree file for reading (see format requirement in details)

outfile

a character string naming the result file for writing

phen

a character string for a phenotype name in phenfile

covars

a character vector for covariates in phenfile

cov.int

a character string naming the covariate for interaction, the covariate has to be included in covars

sub

"N" (default) for no stratified analysis, and "Y" for requesting stratified analyses (only when cov.int is dichotomous)

col.names

a logical value indicating whether the output file should contain column names

sep.ped

the field separator character for pedigree file

sep.phe

the field separator character for phenotype file

sep.gen

the field separator character for genotype file

Value

Please see value in geepack.quant.int.batch function.

Details

Similar to the details for geepack.quant.int.batch function but here the SNP data contains imputed genotypes (allele dosages) that are continuous and range from 0 to 2.

References

Liang, K.Y. and Zeger, S.L. (1986) Longitudinal data analysis using generalized linear models. Biometrika, 73 13--22.

Zeger, S.L. and Liang, K.Y. (1986) Longitudinal data analysis for discrete and continuous outcomes. Biometrics, 42 121--130.

Yan, J and Fine, J. (2004) Estimating equations for association structures. Stat Med, 23 859--874.

Examples

## Not run: 
# geepack.quant.int.batch.imputed(phenfile="simphen.csv",genfile="simgen.csv",
# pedfile="simped.csv",phen="SIMQT",outfile="simout.csv",col.names=T,covars=c("sex",age"),
# cov.int="sex",sub="Y",sep.ped=",",sep.phe=",",sep.gen=",")
# ## End(Not run)