Description Usage Arguments Details Value Author(s) References Examples
Fit Generalized Estimation Equation (GEE) model to test associations between a continuous phenotype
and all imputed SNPs in a genotype file in family data under additive genetic model. Each family is treated as a cluster, with independence working correlation matrix used in the
robust variance estimator. The proportion of phenotype variation explained by the tested SNP is not provided.
This function applies the same trait-SNP association test to all imputed SNPs in the genotype data.
The trait-SNP association test is carried out by using the geese
function from package geepack
.
1 2 | geepack.quant.batch.imputed(phenfile,genfile,pedfile,phen,
covars=NULL,outfile,col.names=T,sep.ped=",",sep.phe=",",sep.gen=",")
|
phenfile |
a character string naming the phenotype file for reading (see format requirement in details) |
genfile |
a character string naming the genotype file for reading (see format requirement in details) |
pedfile |
a character string naming the pedigree file for reading (see format requirement in details) |
phen |
a character string for a phenotype name in |
covars |
a character vector for covariates in |
outfile |
a character string naming the result file for writing |
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 |
Similar to the details for geepack.quant.batch
function but here the SNP data contains imputed genotypes (allele dosages)
that are continuous and range from 0 to 2. In addition, the user specified genetic model argument is not available.
No value is returned. Instead, results are written to outfile
.
phen |
phenotype name |
snp |
SNP name |
N |
the number of individuals in analysis |
AF |
imputed allele frequency of coded allele |
beta |
regression coefficient of SNP covariate |
se |
standard error of |
pval |
p-value of testing |
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.
1 2 3 4 5 6 | ## Not run:
geepack.quant.batch.imputed(phenfile="simphen.csv",genfile="simgen.csv",
pedfile="simped.csv",phen="SIMQT",outfile="simout.csv",col.names=T,covars="sex",
sep.ped=",",sep.phe=",",sep.gen=",")
## End(Not run)
|
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