Table 1 

Bayesian models developed for genomic selection. 

Feature Model 
BayesA 
BayesB 
BayesC (=SSVS stochastic search variable selection) 
BayesCpi 


Probability for a locus to be a QTL 
1 
1p 
1p 
1p 
QTLspecific effect variance (variance heterogeneity) 
Yes 
Yes 
No 
No 
Modelling of noQTL 
Not aplicable 
Null variance 
Tiny variance 
Null variance 
Estimated parameter 
p(uniform prior) 

Hyperparameters (assumed known) 
df^{1}, S^{2} 
df, S, p 
df, S, p 
df, S 
Use MetropolisHastings sampler? 
No 
Yes 
No 
No 


^{1}df=degrees of freedom; ^{2}S=scale parameter, the two parameters of scaled inverted Chisquare distribution (df, S) used as a priori distribution for QTL effect variance 

Pszczola et al. BMC Proceedings 2011 5(Suppl 3):S1 doi:10.1186/175365615S3S1 