e induced.
Ideally the choice of prior for the marker effect should reflect the genetic 
architecture of the trait, and will vary (perhaps a lot) across traits.

The following prior distributions are provided:
Bayes N: Assigning a Gaussian prior to marker effects implies that the posterior means are the 
BLUP estimates (same as Ridge Regression).
Bayes L: Assigning a double-exponential or Laplace prior is the density used in 
the Bayesian LASSO
Bayes A: similar to ridge regression but t-distribution prior (