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A bayesian approach to replication of linkage findings
Author(s) -
Wang Kai,
Vieland Veronica,
Huang Jian
Publication year - 1999
Publication title -
genetic epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.301
H-Index - 98
eISSN - 1098-2272
pISSN - 0741-0395
DOI - 10.1002/gepi.13701707123
Subject(s) - replication (statistics) , bayesian probability , linkage (software) , locus (genetics) , biology , computational biology , genetics , genetic linkage , computer science , artificial intelligence , gene , virology
A novel Bayesian approach to replication studies, allowing for locus heterogeneity, is introduced. Compared with currently used approaches to replication, it offers a natural way to accumulate evidence across independently collected data sets and yields more interpretable results. Using four replicates (one as initial study and the other three as replication studies) from Problem 2 of the Genetic Analysis Workshop 11 data, we show the performance of this method. All four disease susceptibility loci (D1G009, D1G024, D3G045, D5G035) are identified and accurately mapped, with no false positive signals.