chopsticks (version 1.36.0)

single.snp.tests: 1-df and 2-df tests for genetic associations with SNPs

Description

This function carries out tests for association between phenotype and a series of single nucleotide polymorphisms (SNPs), within strata defined by a possibly confounding factor. SNPs are considered one at a time and both 1-df and 2-df tests are calculated. For a binary phenotype, the 1-df test is the Cochran-Armitage test (or, when stratified, the Mantel-extension test).

Usage

single.snp.tests(phenotype, stratum, data = sys.parent(), snp.data, subset, snp.subset)

Arguments

phenotype

A vector containing the values of the phenotype

stratum

Optionally, a factor defining strata for the analysis

data

A dataframe containing the phenotype and stratum data. The row names of this are linked with the row names of the snps argument to establish correspondence of phenotype and genotype data. If this argument is not supplied, phenotype and stratum are evaluated in the calling environment and should be in the same order as rows of snps

snp.data

An object of class "snp.matrix" containing the SNP genotypes to be tested

subset

A vector or expression describing the subset of subjects to be used in teh analysis. This is evaluated in the same environment as the phenotype and stratum arguments

snp.subset

A vector describing the subset of SNPs to be considered. Default action is to test all SNPs.

Value

A dataframe, with columns

chi2.1df

Cochran-Armitage type test for additive genetic component

chi2.2df

Chi-squared test for both additive and dominance components

N

The number of valid data points used

Details

Formally, the test statistics are score tests for generalized linear models with canonical link. That is, they are inner products between genotype indicators and the deviations of phenotypes from their stratum means. Variances (and covariances) are those of the permutation distribution obtained by randomly permuting phenotype within stratum.

The subset argument can either be a logical vector of length equal to the length of the vector of phenotypes, an integer vector specifying positions in the data frame, or a character vector containing names of the selected rows in the data frame. Similarly, the snp.subset argument can be a logical, integer, or character vector.

References

Clayton (2008) Testing for association on the X chromosome Biostatistics (In press)

See Also

snp.lhs.tests, snp.rhs.tests

Examples

data(testdata)
results <- single.snp.tests(cc, stratum=region, data=subject.data,
   snp.data=Autosomes, snp.subset=1:10)
summary(results)
# QQ plot - see \code{\link{qq.chisq}}
qq.chisq(results$chi2.1df)
qq.chisq(results$chi2.2df)