Areas under false positive curves for all three strengths of dependency of variance on average spot intensity, and for additional simulations. Areas are normalized so that the highest (worst) possible area is 0.50, the lowest (best) being 0.00. (A) Low strength dependency- the fold change method performed poorest for low prior degrees of freedom, while the simple t-test is poorest with high prior degrees of freedom. IBMT performs minimally better than SMT in this case. Fox performs similarly to fold change (B) Medium strength dependency- Similar to above, but with the advantage of IBMT larger for high prior degrees of freedom (C) High strength dependency- IBMT performs better than all other methods, especially for mid to high prior degrees of freedom. (D) 4-slide simulation- Similar to (C), but with overall poorer performance by the t-test, and slightly more advantage by IBMT. (E) 10-slide simulation- Fox now performs significantly better than fold change, but both have very poor performance for low prior degrees of freedom. IBMT still performs best.