GWAF (version 2.2)

geepack.lgst: function for testing association between a dichotomous trait and a genotyped SNP in family data using Generalized Estimation Equation model

Description

Fit logistic regression via GEE to test association between a dichotomous phenotype and one genotyped SNP in a genotype file with user specified genetic model. Each family is treated as a cluster, with independence working correlation matrix used in the robust variance estimator. The trait-SNP association test is carried out by the geese function from package geepack. This function is called in geepack.lgst.batch function to apply association test to all SNPs in the genotype data.

Usage

geepack.lgst(snp, phen, test.dat, covar = NULL, model = "a")

Arguments

snp

genotype data of a SNP

phen

a character string for a phenotype name in test.dat

test.dat

the product of merging phenotype, genotype and pedigree data, should be ordered by "famid"

covar

a character vector for covariates in test.dat

model

a single character of 'a','d','g', or 'r', with 'a'=additive, 'd'=dominant, 'g'=general and 'r'=recessive models

Value

Please see output in geepack.lgst.batch.

Details

The geepack.lgst function tests association between a dichtomous trait and a SNP from a dataset that contains phenotype, genotype and pedigree data (test.dat), where the dataset needs to be ordered by famid.

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.

See Also

geese function from package geepack

Examples

## Not run: 
# geepack.lgst(snp=data[,"rs123"],phen="CVD",test.dat=data,model="a",covar=c("age","sex"))
# ## End(Not run)