tdt.rr: Calculate haplotype relative risks in TDT studies

tdt.rrR Documentation

Calculate haplotype relative risks in TDT studies


The p-value is the conventional "exact" test based on the binomial distribution of transmissions. The estimated relative risks use a Bayesian method, recommended because of the multiplicity problem. the prior is a beta distribution of the second kind, defined by two "degrees of freedom" parameters. Note that the prior mean is prior.df[1]/prior.df[2] and that Bayes estimates based on small numbers of transmissions are pulled in towards this. A "realistic" choice of these parameters is recommended, and to aid this, the function returns credible intervals using the prior alone as well as the a posteriori interval for each haplotype.


tdt.rr(hap, prior.df=c(0.5, 0.5), prob=c(0.05, 0.95))



A list containing the transmitted and untransmitted haplotypes. This would normally be computed using


a vector of length two containing the degree of freedom parameters for the prior distribution of the haplotype relative risk - a beta distribution of the second kind.


The probability levels for Bayesian credibility intervals for the haplotype relative risks.


A matrix containing the numbers of transmitted and untransmitted haplotypes, the (binomial) p-values, the Bayes estimates of the haplotype relative risks, and the lower and upper bounds of the credible interval. The prior estimate and credible interval is also shown.


Spielman R., McGinnis R., and Ewens, W. (1993) Transmission tests for linkage disequilibrium. American Journal of Human Genetics, 52, 506-16.

See Also

hap.transmit,, tdt.quad


## Not run: 
# Select the sub-haplotype made up from the first two markers and 
# print tables of TDT tests and haplotype realtaive risks

	hap.use <-, markers=1:2)
	rr <- tdt.rr(hap.use)

## End(Not run)

tdthap documentation built on Oct. 29, 2022, 1:14 a.m.