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

1-p

1-p

1-p

QTL-specific effect variance (variance heterogeneity)

Yes

Yes

No

No

Modelling of no-QTL

Not aplicable

Null variance

Tiny variance

Null variance

Estimated parameter

p(uniform prior)

Hyperparameters (assumed known)

df1, S2

df, S, p

df, S, p

df, S

Use Metropolis-Hastings sampler?

No

Yes

No

No


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

Pszczola et al. BMC Proceedings 2011 5(Suppl 3):S1   doi:10.1186/1753-6561-5-S3-S1

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