lrt.G: Likelihood Ratio Tests for Identifying Disease Polymorphisms...
In IFP: Identifying Functional Polymorphisms

Description Usage Arguments Value References See Also Examples

Compute p-values and likelihoods of all possible models for a given number of disease SNP(s).

1	lrtG(n.fp, genoT, genoC)

`n.fp`	number of disease SNPs for tests.
`genoT`	matrix of control genotypes. Each row indicates a variant, and each column indicates a haplotype of an individual. Two alleles of 0 and 1 are allowed.
`genoC`	matrix of case genotypes. Each row indicates a variant, and each column indicates a haplotype of an individual. Two alleles of 0 and 1 are allowed.

matrix of likelihood ratio test results. First row indicates the index, and following n.fp rows indicate the model for each set of disease polymorphisms, and followed by p-values, -2 log(likelihood ratio) with corrections for variances, and the degree of freedom.

L. Park, J. Kim, Rare high-impact disease variants: properties and identification, Genetics Research, 2016 Mar; 98, e6.

allele.freq.G

## LRT tests for a dominant variant (15th variant)
## the odds ratio: 3, control: 100, case: 100.

data(apoeG)
lrtG(1,genoT[,1:20],genoC[,1:20])

# use "lrtG(1,genoT,genoC)" for the actual test.