gLRTH_A: The function for the likelihood ratio test for genome-wide...

In gLRTH: Genome-Wide Association and Linkage Analysis under Heterogeneity

Description

We consider a binary trait and focus on detecting association with disease at a single locus with two alleles A and a. The likelihood ratio test is based on a binomial mixture model of J components (J ≥ 2) for diseased cases:

P_{η}(X_D=g)=∑_{j=1}^J α_j B_2(g, θ_j), \; g=0, 1, 2, \; J ≥q 2, \; ∑_{j=1}^J α_j=1, \; θ_j, α_j \in (0, 1),

where η=(η_j)_{j ≤q J}, η_j=(θ_j, α_j)^T, j=1, …, J, B_2(g, θ_j) is the probability mass function for a binomial distribution X \sim Bin(2, θ_j), and θ_i=θ_j if and only if i=j. θ_j is the probability of having the allele of interest on one chromosome for a subgroup of case j. In particular, J is likely to be quite large for many of the complex disease with genetic heterogeneity. Note that the LRT-H can be applied to association studies without the need to know the exact value of J while allowing J ≥ 2.

Usage

gLRTH_A(n0, n1, n2, m0, m1, m2)

Arguments

n0	AA genotype frequency in case
n1	Aa genotype frequency in case
n2	aa genotype frequency in case
m0	AA genotype frequency in control
m1	Aa genotype frequency in control
m2	aa genotype frequency in control

Value

The test statistic and asymptotic p-value for the likelihood ratio test for GWAS under genetic heterogeneity

Author(s)

Xiaoxia Han and Yongzhao Shao

References

Qian M., Shao Y. (2013) A Likelihood Ratio Test for Genome-Wide Association under Genetic Heterogeneity. Annals of Human Genetics, 77(2): 174-182.

Examples

gLRTH_A(n0=2940, n1=738, n2=53, m0=3601, m1=1173, m2=117)

gLRTH documentation built on May 1, 2019, 9:33 p.m.