Article

A framework for analyzing both linkage and association: an analysis of Genetic Analysis Workshop 16 simulated data

Division of Statistical Genomics, Washington University School of Medicine, 4444 Forest Park Boulevard, Campus Box 8506, St, Louis, Missouri 63108 USA. .
BMC proceedings 12/2009; 3 Suppl 7(Suppl 7):S98. DOI: 10.1186/1753-6561-3-s7-s98
Source: PubMed

ABSTRACT ABSTRACT : We examine a Bayesian Markov-chain Monte Carlo framework for simultaneous segregation and linkage analysis in the simulated single-nucleotide polymorphism data provided for Genetic Analysis Workshop 16. We conducted linkage only, linkage and association, and association only tests under this framework. We also compared these results with variance-component linkage analysis and regression analyses. The results indicate that the method shows some promise, but finding genes that have very small (<0.1%) contributions to trait variance may require additional sources of information. All methods examined fared poorly for the smallest in the simulated "polygene" range (h2 of 0.0015 to 0.0002).

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