R: GRAMMAR test for association in samples with genetic...

grammar {GenABEL} | R Documentation

## GRAMMAR test for association in samples with genetic structure

### Description

Fast approximate test for association between a trait and genetic polymorphisms, in samples with genetic sub-structure (e.g. relatives). The function implements several varieties of GRAMMAR ('gamma','gc', and 'raw').

### Usage

      grammar(polyObject, data,
        method = c("gamma", "gc", "raw"), propPs = 1, ...)

### Arguments

`polyObject` | object returned by `polygenic` function
`data` | object of `gwaa.data-class`
`method` | to be used, one of 'gamma','gc', or 'raw'
`propPs` | proportion of non-corrected P-values used to estimate the inflation factor Lambda, passed directly to the `estlambda`
`...` | arguments passed to the function used for computations, (`qtscore`)

### Details

With 'raw' argument, the original GRAMMAR (Aulchenko et al., 2007) is implemented. This method is conservative and generates biased estimates of regression coefficients.

With 'gc' argument, the GRAMMAR-GC (Amin et al., 2007) is implemented. This method solves the conservativity of the test, but the Genomic Control (GC) lambda is by definition "1" and can not serve as an indicator of goodness of the model; also, the estimates of regression coefficients are biased (the same as in 'raw' GRAMMAR).

GRAMMAR-Gamma (default 'gamma' argument) solves these problems, producing a correct distribution of the test statistic, interpretable value of GC Lambda, and unbiased estimates of the regression coefficients. All together, the default 'gamma' method is recommended for use.

### Value

Object of scan.gwaa-class

### Author(s)

Gulnara Svischeva, Yurii Aulchenko

### References

GRAMMAR-Raw: Aulchenko YS, de Koning DJ, Haley C. Genomewide rapid association using mixed model and regression: a fast and simple method for genomewide pedigree-based quantitative trait loci association analysis. Genetics. 2007 Sep;177(1):577-85.

GRAMMAR-GC: Amin N, van Duijn CM, Aulchenko YS. A genomic background based method for association analysis in related individuals. PLoS One. 2007 Dec 5;2(12):e1274.

GRAMMAR-Gamma: Svischeva G, Axenovich TI, Belonogova NM, van Duijn CM, Aulchenko YS. Rapid variance components-based method for whole-genome association analysis. Nature Genetics. 2012 44:1166-1170. doi:10.1038/ng.2410

### See Also

`polygenic`, `mmscore`, `qtscore`

### Examples

    # Using clean ge03d2 data
    require(GenABEL.data)
    data(ge03d2.clean)
    # take only a small piece for speed
    ge03d2.clean <- ge03d2.clean[1:200,]
    # estimate genomic kinship
    gkin <- ibs(ge03d2.clean[,sample(autosomal(ge03d2.clean),1000)], w="freq")
    # perform polygenic analysis
    h2ht <- polygenic(height ~ sex + age, kin=gkin, ge03d2.clean)
    h2ht$est
    # compute mmscore stats
    mm <- mmscore(h2ht, data=ge03d2.clean)
    # compute grammar-gc
    grGc <- grammar(h2ht, data=ge03d2.clean, method="gc")
    # compute grammar-gamma
    grGamma <- grammar(h2ht, data=ge03d2.clean, method="gamma")
    # compare lambdas
    lambda(mm)
    estlambda(mm[,"chi2.1df"])
    lambda(grGamma)
    estlambda(grGamma[,"chi2.1df"])
    lambda(grGc)
    estlambda(grGc[,"chi2.1df"])
    # compare top results
    summary(mm)
    summary(grGamma)
    summary(grGc)

[Package GenABEL version 1.8-0 Index]