title: The incorporation of prior genomic information does not necessarily improve the performance of Bayesian linkage methods: an example involving sex-specific recombination and the two-point PPL.
abstract: OBJECTIVE
  We continue statistical development of the posterior probability of linkage (PPL). We present a two-point PPL allowing for unequal male and female recombination fractions, thetaM and thetaF, and consider alternative priors on thetaM, thetaF.
  
  
  METHODS
  We compare the sex-averaged PPL (PPLSA), assuming thetaM = thetaF, to the sex-specific PPL (PPLSS) in (thetaM, thetaF), in a series of simulations; we also compute the PPLSS using alternative priors on (thetaM, thetaF).
  
  
  RESULTS
  The PPLSS based on a prior that ignores prior genomic information on sex specific recombination rates performs essentially identically to the PPLSA, even in the presence of large thetaM, thetaF differences. Moreover, adaptively skewing the prior, to incorporate (correct) genomic information on thetaM, thetaF differences, actually worsens performance of the PPLSS. We demonstrate that this has little to do with the PPLSS per se, but is rather due to extremely high levels of variability in the location of the maximum likelihood estimates of (thetaM, thetaF) in realistic data sets.
  
  
  CONCLUSIONS
  Incorporating (correct) prior genomic information is not always helpful. We recommend that the PPLSA be used as the standard form of the PPL regardless of the sex-specific recombination rates in the region of the marker in question.
authors.affiliation: Program in Public Health Genetics, College of Public Health, University of Iowa, Iowa City, Iowa 52242, USA. mark-logue@uiowa.edu
authors.forename: Mark W
authors.initials: MW
authors.lastname: Logue
authors.forename: Veronica J
authors.initials: VJ
authors.lastname: Vieland
mesh_terms: D001499:Bayes Theorem; D005260:Female; D008040:Genetic Linkage / Q000235:genetics*; D006801:Humans; D008297:Male; D008957:Models, Genetic; D011995:Recombination, Genetic / Q000235:genetics*; D012737:Sex Factors