Abstract
BackgroundIn this article, I propose a model-selection-free method to map multiple quantitative trait loci (QTL) in variance component model, which is useful in outbred populations. The new method can estimate the variance of zero-effect QTL infinitely to zero, but nearly unbiased for non-zero-effect QTL. It is analogous to Xu's Bayesian shrinkage estimation method, but his method is based on allelic substitution model, while the new method is based on the variance component models.ResultsExtensive simulation experiments were conducted to investigate the performance of the proposed method. The results showed that the proposed method was efficient in mapping multiple QTL simultaneously, and moreover it was more competitive than the reversible jump MCMC (RJMCMC) method and may even out-perform it.ConclusionsThe newly developed Bayesian shrinkage method is very efficient and powerful for mapping multiple QTL in outbred populations.
Highlights
In this article, I propose a model-selection-free method to map multiple quantitative trait loci (QTL) in variance component model, which is useful in outbred populations
In the allelic substitution model, the number of QTL alleles is assumed to be known, and the QTL allelic substitution is estimated by the given linkage phases of parents, which can be inferred from genotypes of family members
It is similar to the recent Bayesian shrinkage estimation methods [15,17,18,19], which are based on the allelic substitution model, whereas my method is based on the variance component model
Summary
I simulated 500 independent full-sib families with 6 individuals in each one, and 3,000 individuals were investigated in my study. For the RJMCMC method, the maximum QTL number and the expected QTL number were the same as the default setup; the prior distribution of the QTL variance, polygenic variance and residual variance followed uniform distribution with endpoint being zero and phenotypic variance; the thinning interval was empirically set as 10; the burn-in period was 1,000 and the length of the complete chain was 201,000, and there were 10,000 samples saved for posterior analysis It took ~ 5 hr for the new and RJMCMC method on a Pentium IV PC with a 2.60-GHz processor and 1.00 GB RAM.
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