Experimental overview. A summary of our overall approach is shown. The merits of BMA include that the model is multivariate and considers multiple biomarkers simultaneously; that the uncertainty of gene selection is accounted for by averaging over multiple good models; that posterior probabilities are generated for all selected genes and models; and that it produces a high predictive accuracy with relatively few genes.