RVFam (version 1.1)

glmm.EC: function for testing a single/pooled variant for continuous traits with family data using generalized linear mixed effects model

Description

Fit generalized linear mixed effects model (GLMM) with logistic link that treats each pedigree as a cluster to test a single/pooled variant for associations against a continuous phenotype with family data. The glmer function from package lme4 is used.

Usage

glmm.EC(snp,phen,test.dat,covar,chr)

Arguments

snp

a numeric vector with genotype of a single/pooled variant

phen

a character string for the phenotype name of a binary trait of interest 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

chr

chromosome number

Value

ntotal

number of individuals with genotype, phenotype and covariates

nmiss

number of individuals with missing genotype among ntotal

maf_ntotal

minor allele frequency based on ntotal

beta

regression coefficient of single SNP test or burden test

se

standard error of beta

Z

Z statistic based on signed LRT

remark

additional information of the analysis

p

LRT p-value of a single variant test or burden test

MAC

minor allele count

n0

the number of individuals with 0 copy of coded alleles

n1

the number of individuals with 1 copy of coded alleles

n2

the number of individuals with 2 copies of coded alleles

Details

The glmm.EC function fits a generalized linear mixed effects model (GLMM) with logistic link that treats each pedigree as a cluster to test association between a binary trait and a single/pooled genetic variant with additive model. The trait-variant association test is carried out by the glmer function from package lme4. P-value from likelihood ratio test (LRT) is reported. This function is called in glmm.ped function to test all single/pooled variants.

References

Bates D, Maechler M, Bolker B and Walker S (2014). lme4: Linear mixed-effects models using Eigen and S4. R package version 1.1-7, http://CRAN.R-project.org/package=lme4.

Examples

## Not run: 
# glmm.EC(snp=rsnps.dat[,"snp1"],phen="disease",test.dat=rsnps.dat,
# covar=c("sex"),chr=1)
# ## End(Not run)