Bayesian linkage and segregation analysis: Factoring the problem

Rosalind J. Neuman, Nancy L. Saccone, Peter Holmans, John P. Rice, Lingwei Sun

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

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. (C) 2000 Wiley-Liss, Inc.

Original languageEnglish
Pages (from-to)S50-S56
JournalGenetic Epidemiology
Volume19
Issue numberSUPPL. 1
DOIs
StatePublished - 2000

Keywords

  • Bayesian
  • Linkage analysis
  • Markov Chain Monte Carlo (MCMC)
  • Numerical integration
  • Segregation analysis

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