gap (version 1.5-1)

hwe.cc: A likelihood ratio test of population Hardy-Weinberg equilibrium for case-control studies

Description

A likelihood ratio test of population Hardy-Weinberg equilibrium for case-control studies

Usage

hwe.cc(model, case, ctrl, k0, initial1, initial2)

Value

The returned value is a list with the following components.

Cox

statistics under a general model

t2par

under the null hypothesis

t3par

under the alternative hypothesis

lrt.stat

the log-likelihood ratio statistic

pval

the corresponding p value

Arguments

model

model specification, dominant, recessive.

case

a vector of genotype counts in cases.

ctrl

a vector of genotype counts in controls.

k0

prevalence of disease in the population.

initial1

initial values for beta, gamma, and q.

initial2

initial values for logit(p) and log(gamma).

Author

Chang Yu, Li Wang, Jing Hua Zhao

Details

This is a collection of utility functions. The null hypothesis declares that the proportions of genotypes are according to Hardy-Weinberg law, while under the alternative hypothesis, the expected genotype counts are according to the probabilities that particular genotypes are obtained conditional on the prevalence of disease in the population. In so doing, Hardy-Weinberg equilibrium is considered using both case and control samples but pending on the disease model such that 2-parameter multiplicative model is built on baseline genotype \(\alpha\), \(\alpha\beta\) and \(\alpha\gamma\).

References

Yu C, Zhang S, Zhou C, Sile S. A likelihood ratio test of population Hardy-Weinberg equilibrium for case-control studies. Genetic Epidemiology 33:275-280, 2009

See Also

hwe

Examples

if (FALSE) {

### Saba Sile, email of Jan 26, 2007, data always in order of GG AG AA, p=Pr(G),
### q=1-p=Pr(A)
case=c(155,27,4)
ctrl=c(408,55,15)
k0=.2
initial1=c(1.0,0.94,0.0904)
initial2=c(logit(1-0.0904),log(0.94))
hwe.cc("recessive",case,ctrl,k0, initial1, initial2)

### John Phillips III, TGFb1 data codon 10: TT CT CC, CC is abnormal and increasing
### TGFb1 activity
case=c(29,78,13)
ctrl=c(17,28,6)
k0 <- 1e-5
initial1 <- c(2.45,2.45,0.34)
initial2 <- c(logit(1-0.34),log(2.45))
hwe.cc("dominant",case,ctrl,k0,initial1,initial2)
}