pvalue.VCC3: Compute p-values for the VC-C3 method
In RVPedigree: Methods for Family-Based Rare-Variant Genetic Association Tests

Compute p-values for the VC-C3 method

1 2	pvalue.VCC3(P, G, W, Nperm, n, pedigree, haplotypes, generation.id, Ncores = 1)

`P`	a matrix which can be obtained as output of the function `Preparation.VCC`.
`G`	the genotype matrix
`Nperm`	(integer) The number of permutations to be done to calculate the empirical p-value if the VCC2 or VCC3 method is used. For other methods this parameter is ignored (default: 100).
`n`	Integer, the number of samples
`pedigree`	a pedigree as output by `read.pedigree`. This is a data frame consisting of four columns (family ID, individual ID, father ID and mother ID) as use in the traditional linkage format and e.g. Plink files.
`haplotypes`	a matrix of the haplotypes of the individuals
`generation.id`	a vector of length(sample size) which indicates if the subject is founder (`generation.id=0`), a child from first generation (`generation.id=1`), a child from second generation (`generation.id=2`), etc. This vector can be calculated by the `kinship2::kindepth()` function.
`Ncores`	(integer) Number of processor (CPU) cores to be used in parallel when doing the permutations to determine the p-value (default: 1).

the outcomes of the VC-C3 association test on the given region, which is a list with the following elements:

score: The score test
p.value.VCC2: The p-value as output by the VC-C2 method (pvalue.VCC2).
p.value.VCC3: This is the exact p-vlaue for small level size. The approach to obtain this second p-value approximates the distribution of the test statistic under the null model by a non-central chi-square using matching moments of the first, the second and the fourth moments. The estimation of the three moments are approximated empirically using the permutations that were used to calculate the VC-C2 p-value.

Karim Oualkacha

M'Hamed Lajmi Lakhal-Chaieb

RVPedigree documentation built on May 29, 2017, 10:19 p.m.