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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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2796002 | PMC |
http://dx.doi.org/10.1186/1753-6561-3-s7-s98 | DOI Listing |
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