Description Usage Arguments Details Value Author(s) References See Also Examples
Fit logistic regression via Generalized Estimation Equation (GEE) to test gene-environment or gene-gene interaction between a dichotomous phenotype
and one genotyped SNP in a genotype file in family data under additive genetic model. The interaction term is the product of SNP genotype and the 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 family is treated as
a cluster, with independence working correlation matrix used in the robust variance estimator. The interaction
test is carried out by the geese
function from package geepack
. This function is called in geepack.lgst.int.batch
function to apply interaction test to all SNPs in a
genotype file.
1 | geepack.lgst.int(snp,phen,test.dat,covar,cov.int,sub="N")
|
snp |
genotype data of a SNP |
phen |
a character string for a phenotype name in |
test.dat |
the product of merging phenotype, genotype and pedigree data, should be ordered by "famid" |
covar |
a character vector for covariates in |
cov.int |
a character string naming the covariate for interaction, the covariate has to be included in |
sub |
"N" (default) for no stratified analysis, and "Y" for requesting stratified analyses (only when cov.int is dichotomous) |
The geepack.lgst.int
function tests gene-environment or gene-genn interaction 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. Please also see details in
details for geepack.lgst.int.batch
function.
Please see value in geepack.lgst.int.batch
function.
Qiong Yang <qyang@bu.edu> and Ming-Huei Chen <mhchen@bu.edu>
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.
geese
function from package geepack
1 2 3 4 5 | ## Not run:
geepack.lgst.int(snp=data[,"rs123"],phen="CVD",test.dat=data,covar=c("age",sex"),
cov.int="sex",sub="Y")
## End(Not run)
|
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