single.snp.tests {snpMatrix} | R Documentation

## 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.

### 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.

### 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

### Note

The behaviour of this function for objects of class `X.snp.matrix` is as described by Clayton (2008). Males are treated as homozygous females and corrected variance estimates are used.

### Author(s)

David Clayton david.clayton@cimr.cam.ac.uk

### 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 this-is-escaped-codenormal-bracket52bracket-normal
    qq.chisq(results$chi2.1df)
    qq.chisq(results$chi2.2df)

[Package snpMatrix version 1.4.2 Index]