title: Risk prediction with linked markers: theory.
abstract: A Bayesian method to predict disease recurrence risks based on distance information between loci and allowing for uncertain gene location is presented. The methodology allows derivation of the posterior distribution of recurrence risks, from which point estimates and associated precision measures can be calculated. The resulting risk distribution accounts for all available information concerning location and relative distance, and can be updated as additional data become available.
authors.affiliation: Fox Chase Cancer Center, Philadelphia, Pennsylvania 19111, USA.
authors.forename: A
authors.initials: A
authors.lastname: Rogatko
mesh_terms: D001499:Bayes Theorem; D030342:Genetic Diseases, Inborn / Q000235:genetics*; D008040:Genetic Linkage / Q000235:genetics*; D005819:Genetic Markers; D006801:Humans; D008962:Models, Theoretical; D011237:Predictive Value of Tests
chemical_list: D005819:Genetic Markers