tdt.snp {snpMatrix} | R Documentation

## 1-df and 2-df tests for genetic associations with SNPs (or imputed SNPs) in family data

### Description

Given large-scale SNP data for families comprising both parents and one or more affected offspring, this function computes 1 df tests (the TDT test) and a 2 df test based on observed and expected transmissions of genotypes. Tests based on imputation rules can also be carried out.

### Usage

    tdt.snp(ped, id, father, mother, affected, data = sys.parent(), snp.data,
        rules = NULL, snp.subset, check.inheritance = TRUE, robust = FALSE,
        score = FALSE)

### Arguments

`ped` | Pedigree identifiers
`id` | Subject identifiers
`father` | Identifiers for subjects' fathers
`mother` | Identifiers for subjects' mothers
`affected` | Disease status (TRUE if affected, FALSE otherwise)
`data` | A data frame in which to evaluate the previous five arguments
`snp.data` | An object of class `"snp.matrix"` containing the SNP genotypes to be tested
`rules` | An object of class `"snp.reg.imputation"`. If supplied, the rules coded in this object are used, together with `snp.data`, to calculate tests for imputed SNPs
`snp.subset` | A vector describing the subset of SNPs to be considered. Default action is to test all SNPs in `snp.data` or, in imputation mode, as specified by `rules`
`check.inheritance` | If TRUE, each affected offspring/parent trio is tested for Mendelian inheritance and excluded if the test fails. If FALSE, misinheriting trios are used but the "robust" variance option is forced
`robust` | If TRUE, forces the robust (Huber-White) variance option (with `ped` determining independent "clusters")
`score` | If `TRUE`, the output object will contain, for each SNP, the score vector and its variance-covariance matrix

### Details

Formally, the test statistics are score tests for the "conditioning on parental genotype" (CPG) likelihood. Parametrization of associations is the same as for the population-based tests calculated by `single.snp.tests` so that results from family-based and population-based studies can be combined using `pool`.

When the function is used to calculate tests for imputed SNPs, the test is still an approximate score test. The current version does not use the family relationships in the imputation. With this option, the robust variance estimate is forced.

The first five arguments are usually derived from a "pedfile". If a data frame is supplied for the `data` argument, the first five arguments will be evaluated in this frame. Otherwise they will be evaluated in the calling environment. If the arguments are missing, they will be assumed to be in their usual positions in the pedfile data frame i.e. in columns one to four for the identifiers and column six for disease status (with affected coded `2`). If the pedfile data are obtained from a dataframe, the row names of the `data` and `snp.data` files will be used to align the pedfile and SNP data. Otherwise, these vectors will be assumed to be in the same order as the rows of `snp.data`.

The `snp.subset` argument can be a logical, integer, or character vector.

If imputed rather than observed SNPs are tested, or if `check.inheritance` is set to `FALSE`, the "robust" variance estimate is used regardless of the value supplied for the `robust` argument.

### Value

An object of class `"snp.tests.single"`. If `score=TRUE`, the output object will be of the extended class `"snp.tests.single.score"` containing additional slots holding the score statistics and their variances (and covariances). This allows meta-analysis using the `pool` function.

### Note

When the snps are on the X chromosome (i.e. when the `snp.data` argument is of class `"X.snp.matrix"`), the tests are constructed in the same way as was described by Clayton (2008) for population-based association tests i.e. assuming that genotype relative risks for males mirror thos of homozygous females

### Author(s)

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

### References

Clayton (2008) Testing for association on the X chromosome Biostatistics, Advanced on-line access)

### See Also

`single.snp.tests`, `impute.snps`, `pool`, `snp.reg.imputation-class`, `snp.tests.single-class`, `snp.tests.single.score-class`

### Examples

    data(families)
    tdt.snp(data=pedfile, snp.data=genotypes)

[Package snpMatrix version 1.6.1 Index]