Bayesian methods for genomic association of chromosomic regions considering the additive-dominance model

Bayesian approaches applied in association studies select regions of single-nucleotide polymorphisms, indicating genes with important effects. The methods differ terms the distribution assumed for marker Here, we used window posterior probability to detect potential regions. present study evaluated efficiency these identifying located close genes. Data were simulated six scenarios. Considering lack dominance, BayesA was more efficient scenario three QTLs. For scenarios 10 or 100 QTLs, BayesCπ and BayesDπ according false positive rate detection power. presence all similar except accuracy. superior while BRR