title: Bayesian linkage and segregation analysis: factoring the problem.
abstract: Complex segregation analysis and linkage methods are mathematical techniques for the genetic dissection of complex diseases. They are used to delineate complex modes of familial transmission and to localize putative disease susceptibility loci to specific chromosomal locations. The computational problem of Bayesian linkage and segregation analysis is one of integration in high-dimensional spaces. In this paper, three available techniques for Bayesian linkage and segregation analysis are discussed: Markov Chain Monte Carlo (MCMC), importance sampling, and exact calculation. The contribution of each to the overall integration will be explicitly discussed.
authors.affiliation: Psychology Research Laboratory, Mailman Research Center, McLean Hospital, Belmont, Massachusetts 02478, USA. steven_matthysse@harvard.edu
authors.forename: S
authors.initials: S
authors.lastname: Matthysse
mesh_terms: D001499:Bayes Theorem; D008040:Genetic Linkage; D008957:Models, Genetic; D009010:Monte Carlo Method; D012494:Sampling Studies; D013223:Statistics as Topic