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

Source: R/hwe.cc.R
hwe.cc.Rd

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

Usage

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

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).

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.

Details

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

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 (2009). “A likelihood ratio test of population Hardy-Weinberg equilibrium for case-control studies.” Genet Epidemiol, 33(3), 275-80. doi:10.1002/gepi.20381 .

See also

hwe

Author

Chang Yu, Li Wang, Jing Hua Zhao

Examples

if (FALSE) { # \dontrun{
### 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)
} # }