Medical College of Wisconsin
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A Bayesian approach to the transmission/disequilibrium test for binary traits. Genet Epidemiol 2002 Jan;22(1):41-51 PMID: 11754472

Pubmed ID

11754472

Abstract

The transmission/disequilibrium test (TDT) for binary traits is a powerful method for detecting linkage between a marker locus and a trait locus in the presence of allelic association. The TDT uses information on the parent-to-offspring transmission status of the associated allele at the marker locus to assess linkage or association in the presence of the other, using one affected offspring from each set of parents. For testing for linkage in the presence of association, more than one offspring per family can be used. However, without incorporating the correlation structure among offspring, it is not possible to correctly assess the association in the presence of linkage. In this presentation, we propose a Bayesian TDT method as a complementary alternative to the classical approach. In the hypothesis testing setup, given two competing hypotheses, the Bayes factor can be used to weigh the evidence in favor of one of them, thus allowing us to decide between the two hypotheses using established criteria. We compare the proposed Bayesian TDT with a competing frequentist-testing method with respect to power and type I error validity. If we know the mode of inheritance of the disease, then the joint and marginal posterior distributions for the recombination fraction (theta) and disequilibrium coefficient (delta) can be obtained via standard MCMC methods, which lead naturally to Bayesian credible intervals for both parameters.

Author List

George V, Laud PW

Author

Purushottam W. Laud PhD Professor in the Institute for Health and Equity department at Medical College of Wisconsin




Scopus

2-s2.0-0036137021   7 Citations

MESH terms used to index this publication - Major topics in bold

Alleles
Bayes Theorem
Computer Simulation
Humans
Linkage Disequilibrium
Models, Genetic
Nuclear Family
jenkins-FCD Prod-299 9ef562391eceb2b8f95265c767fbba1ce5a52fd6