Bayesian estimates of linkage disequilibrium.
BACKGROUND
The maximum likelihood estimator of D'--a standard measure of linkage disequilibrium--is biased toward disequilibrium, and the bias is particularly evident in small samples and rare haplotypes.


RESULTS
This paper proposes a Bayesian estimation of D' to address this problem. The reduction of the bias is achieved by using a prior distribution on the pair-wise associations between single nucleotide polymorphisms (SNP)s that increases the likelihood of equilibrium with increasing physical distances between pairs of SNPs. We show how to compute the Bayesian estimate using a stochastic estimation based on MCMC methods, and also propose a numerical approximation to the Bayesian estimates that can be used to estimate patterns of LD in large datasets of SNPs.


CONCLUSIONS
Our Bayesian estimator of D' corrects the bias toward disequilibrium that affects the maximum likelihood estimator. A consequence of this feature is a more objective view about the extent of linkage disequilibrium in the human genome, and a more realistic number of tagging SNPs to fully exploit the power of genome wide association studies.
Sebastiani
Paola
P
Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA. sebas@bu.edu
Abad-Grau
María M
MM
D001499:Bayes Theorem; D006239:Haplotypes; D016045:Human Genome Project; D006801:Humans; D016013:Likelihood Functions; D015810:Linkage Disequilibrium; D008957:Models, Genetic; D020641:Polymorphism, Single Nucleotide